TRANSCRIPTIONAL REGULATION IN SKELETAL MUSCLE
OF ZEBRAFISH IN RESPONSE TO NUTRITIONAL STATUS,
PHOTOPERIOD AND EXPERIMENTAL SELECTION FOR
BODY SIZE
Ian Porto Gurgel do Amaral
A Thesis Submitted for the Degree of PhD
at the
University of St Andrews
2012
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Transcriptional regulation in skeletal muscle of
zebrafish in response to nutritional status,
photoperiod and experimental selection for body size
Ian Porto Gurgel do Amaral
This thesis is submitted in partial fulfilment for the degree of PhD
at the
University of St Andrews
December of 2011
ITranscriptional regulation in skeletal muscle of
zebrafish in response to nutritional status,
photoperiod and experimental selection for body size
Ian Porto Gurgel do Amaral
This thesis is the result of four years of research under direct supervision
of Prof. Ian A. Johnston, head of the Fish Muscle Research Group. The
experiments of which were performed in the Scottish Oceans Institute of
the University of St Andrews.
December of 2011
II
Declarations
1. Candidate’s declarations:
I, Ian Porto Gurgel do Amaral, hereby certify that this thesis, which is approximately
38,000 words in length, has been written by me, that it is the record of work carried out
by me and that it has not been submitted in any previous application for a higher
degree.
I was admitted as a research student in October, 2007 and as a candidate for the degree
of PhD in Biology in December, 2008; the higher study for which this is a record was
carried out in the University of St Andrews between 2007 and 2011.
Date: 12 of December of 2011 Signature of candidate:
2. Supervisor’s declaration:
I hereby certify that the candidate has fulfilled the conditions of the Resolution and
Regulations appropriate for the degree of PhD in Biology in the University of St
Andrews and that the candidate is qualified to submit this thesis in application for that
degree.
Date: 12 of December of 2011 Signature of supervisor:
3. Permission for electronic publication:
In submitting this thesis to the University of St Andrews I understand that I am giving
permission for it to be made available for use in accordance with the regulations of the
University Library for the time being in force, subject to any copyright vested in the
work not being affected thereby. I also understand that the title and the abstract will be
published, and that a copy of the work may be made and supplied to any bona fide
library or research worker, that my thesis will be electronically accessible for personal
or research use unless exempt by award of an embargo as requested below, and that the
library has the right to migrate my thesis into new electronic forms as required to
ensure continued access to the thesis. I have obtained any third-party copyright
permissions that may be required in order to allow such access and migration, or have
requested the appropriate embargo below.
The following is an agreed request by candidate and supervisor regarding the electronic
publication of this thesis:
Access to all of printed copy but embargo of chapters 3 and 4 of electronic publication of
thesis for a period of 1 year on the following ground: publication would preclude future
publication.
Date: 12 of December of 2011 Signature of candidate:
Date: 12 of December of 2011 Signature of supervisor:
III
To my family
IV
Acknowledgements and Grants
I thank Prof. Ian A Johnston for giving me the opportunity of doing my PhD in his group, which
was a great experience. Prof. Ian helped me in many circumstances before and during my PhD.
Coming to St Andrews was only possible after Prof. Ian helped me in many ways to get the
necessary funding to live here. During my PhD his great intellect and knowledge in the area of
muscle physiology were fundamental for the progression of my work, but I also thank him for
being a very understanding and patient person. I also thank Prof. Ian for his very kind words of
support during the difficult times I encountered during my stay in St Andrews.
I thank Dr. Vera Vieira-Johnston, the first person I met when I arrived in St Andrews in 2007.
Her help with fish husbandry was fundamental for this project. Maybe more importantly, she
was a “foster mother” during my PhD, always helping me during the difficulties in adapting to
living in Scotland. I also thank Vera for her very kind words of support during the difficult times
I encountered during my stay in St Andrews, and for the Brazilian music. My stay in Scotland
would have been much harder without her warm friendship.
I thank Prof. Luiz Bezerra de Carvalho Jr. and Ranilson de Souza Bezerra from the department of
Biochemistry of Universidade Federal de Pernambuco. They were my supervisors during my
undergraduate and master projects. Without their words of advice and good examples I
wouldn’t have pursued a PhD in St Andrews.
I thank present and past member of the Fish Muscle Research Group. Specially Dr. Neil Bower,
Dr. Daniel MacQueen, Dr. Daniel Garcia and Dr. Hung-tai Lee for help and advice during my
experiments. Olivia Mendivil, Clara Col, Tom Ashtom and Dr. Graham Scott are thanked for their
great help in keeping the good mood and for being such great office mates and friends.
I thank my friends Jennifer Cadman, Aidan Marshal, Hannah Laws, Hailey Fowler, Giovanna
Bacchidu, Ann Slimm, Sarah Ryan, Moises Lino e Silva, Renata França and Werlayne Mendes for
being great friends, for the trips we took together, for cooking for me, and for sharing various
moments of happiness during the four years I was in St Andrews.
During my PhD I received scholarships from Alban (E07D402823BR), Sir Harold Mitchel Fund,
University of St Andrews and CAPES (BEX 0449-10-5). The experiments performed in this thesis
were funded by LyfeCycle (FP7-222719).
I will always be grateful to you all
VPublications
 Amaral, I. P. G. and Johnston, I. A. (2011). Insulin-like growth factor (IGF)
signalling and genome-wide transcriptional regulation in fast muscle of zebrafish
following a single-satiating meal. The Journal of Experimental Biology 214, 2125-
2139.
I performed all experiments, which were designed by me and Prof. Ian Johnston.
I wrote the paper under supervision of Prof. Ian Johnston.
VI
Conferences
 Johnston, I.A., Amaral, I.P.G., Vieira-Johnston V.L.A. Annual main meeting of
the Society of Experimental Biology (SEB), Marseille, France. Title: Intra-specific
variation in muscle fibre phenotype. July, 2008. Oral presentation by Johnston,
I.A.
 Amaral, I.P.G. and Johnston, I.A. Post-graduate Conference, University of St
Andrews, Scotland. Title: Molecular control of muscle growth during growth and
life-cycle transitions in aquaculture species. November, 2008. Poster
presentation. This was part of the compulsory training during the PhD.
 Amaral, I.P.G. and Johnston, I.A. Post-graduate Conference, University of St
Andrews, Scotland. Title: Molecular control of muscle growth during growth and
life-cycle transitions in aquaculture species. November, 2009. Oral presentation.
This was part of the compulsory training during the PhD.
 Amaral, I.P.G. and Johnston, I.A. International Congress of Biology of Fish,
Barcelona, Spain. Title: Muscle gene expression analysis of insulin-like growth
factor (IGF) signaling following a single-satiating meal in the zebrafish. July,
2010. Oral presentation.
 Amaral, I.P.G. and Johnston, I.A. Annual main meeting of the Society of
Experimental Biology (SEB), Glasgow, UK. Title: Effects of selection for body size
on early-life traits and gene expression in the skeletal muscle of zebrafish (Danio
rerio). July, 2011. Poster presentation.
 Amaral, I.P.G. and Johnston, I.A. Sussex workshop. Title: Circadian expression of
clock and putative clock-controlled genes in skeletal muscle of the zebrafish
(Danio rerio). July, 2011. Poster presentation by Johnston, I.A.
VII
Index
Section Page
Abstract 1
Chapter 1
1. General Introduction 3
1.1. The zebrafish as a biological model system 3
1.1.1. The zebrafish genome, linkage map and whole genome duplication 4
1.2. Fish Growth and Muscle development 7
1.2.1. Fish growth 7
1.2.2. Structure and function of the adult teleost myotome 8
1.2.3. Zebrafish embryonic development, cell fate map and embryonic cell
layers
11
1.2.4. Transcription factors as master switches during myogenesis 14
1.2.5. Fish myogenesis 17
1.3. Hormonal regulation of growth 22
1.3.1. Growth Hormone (GH) 22
1.3.2. Insulin-like Growth Factors (IGF) pathway 23
1.3.3. Cortisol 24
1.3.4. Thyroid hormones 25
1.3.5. Melatonin and the molecular clock 25
1.4. Biotic and abiotic factors affecting fish growth and myogenesis 28
1.4.1. Temperature 28
1.4.2. Nutrition 29
1.4.3. Photoperiod 30
1.4.4. Genetics 31
1.5. Fish domestication 33
1.6. Objectives 35
VIII
Chapter 2
2. Insulin-like growth factor (IGF) signaling and genome-wide
transcriptional regulation in fast muscle of zebrafish following a single-
satiating meal
36
2.1. Summary 36
2.2. Introduction 37
2.3. Materials and Methods 39
2.3.1. Fish and water quality 39
2.3.2. The single meal experiment 39
2.3.3. Protein extraction 40
2.3.4. Western blotting 40
2.3.5. Total RNA extraction from skeletal muscle and first strand cDNA
synthesis
43
2.3.6. Microarray experiments 43
2.3.7. Primer design and cloning 44
2.3.8. Quantitative PCR (qPCR) 47
2.3.9. Data analysis and statistics 48
2.4. Results 49
2.4.1. Feeding response during the single meal experiment 49
2.4.2. Phosphorylation of the Insulin-like growth factor (IGF) signaling
protein Akt
51
2.4.3. Transcriptional regulation of the Insulin-like Growth Factor (IGF) system 52
2.4.4. IGF hormones 52
2.4.5. IGF receptors (IGFRs) 52
2.4.6. IGF binding proteins (IGFBPs) 52
2.4.7. Genome-wide changes in gene expression with feeding 57
2.4.8. Expression and clustering of candidate nutritionally-regulated
genes
64
2.5. Discussion 71
2.5.1. Transcriptional regulation of the IGF system 71
2.5.2. Genome-wide transcriptional regulation with catabolic to anabolic
transition
73
IX
Chapter 3
3. Circadian expression of clock and putative clock-controlled genes in
skeletal muscle of the zebrafish
77
3.1. Summary 77
3.2. Introduction 78
3.3. Materials and Methods 81
3.3.1. Fish and water quality 81
3.3.2. The circadian rhythm experiment 81
3.3.3. Primer design and screening for circadian expression by qPCR 83
3.3.4. Data analysis and statistics 84
3.4. Results 87
3.4.1. Feeding behaviour 87
3.4.2. Non-circadian gene expression in skeletal muscle 87
3.4.3. Expression of core clock genes in skeletal muscle 91
3.4.4. Putative clock-controlled genes 96
3.4.5. Expression of circadian genes and CCGs under 12: 12h light: dark
photoperiod
96
3.4.6. Gene clustering and correlation analysis 96
3.5. Discussion 101
3.5.1. Expression of core-clock genes in zebrafish skeletal muscle 101
3.5.2. Expression of putative clock-controlled genes in zebrafish skeletal
muscle
103
Chapter 4
4. Experimental selection of zebrafish for body size at age: effects on
early-life history traits and gene expression in skeletal muscle
109
4.1. Summary 109
4.2. Introduction 110
4.3. Materials and methods 113
4.3.1. Fish husbandry and artificial selection for body size 113
4.3.2. Early life-history traits of zebrafish egg and larva 114
X4.3.3. Quantitative PCR (qPCR) of maternal transcripts 115
4.3.4. Fasting-refeeding experiment 117
4.3.5. Statistical analysis and data transformation 117
4.4. Results 120
4.4.1. Effects of selection for body size on growth pattern 120
4.4.2. Effects of selection for body size on early life-history traits of
zebrafish
121
4.4.3. Effects of selection for body size on maternal transcripts 124
4.4.4. Effects of selection for body size on muscle gene expression in
adults
130
4.5. Discussion 136
Chapter 5
5. General Discussion 142
5.1. IGF signalling in zebrafish skeletal muscle 142
5.2. Molecular clock machinery in zebrafish skeletal muscle 146
References 149
XI
List of Figures
Chapter 1 Page
Figure 1.1 – Typical curves of growth (red) and growth rate (blue) of a
zebrafish. 7
Figure 1.2 – Muscle fibre types in a cross-section of adult zebrafish and
myotome structure, and a simplified drawing of the muscle and sarcomere
structure, the contractile unit of skeletal muscle. 10
Figure 1.3 – Zebrafish development from 1-cell to 26-somite stage, with
emphasis in the cell fate map during 50% epiboly and the two embryonic
layers formed during gastrulation. 13
Figure 1.4 – Rotation of the somite during zebrafish embryonic myogenesis. 19
Figure 1.5 – Stratified and mosaic hyperplasia in zebrafish larvae. 20
Figure 1.6 – Comparison between curves of body size and fibre number
recruitment in the zebrafish. 21
Chapter 2 Page
Figure 2.1 – Optimization of protein loading for electrophoresis and
western-blotting. 42
Figure 2.2 – The feeding response of male zebrafish during the course of the
single meal experiment. 50
Figure 2.3 – Phosphorylation of the Insulin-like growth factor signaling
protein Akt in the fast myotomal muscle of male zebrafish during the course
of the single meal experiment. 51
Figure 2.4 – Transcriptional responses of Insulin-like growth factor (IGF)
system genes in the fast myotomal muscle of male zebrafish during the
course of the single meal experiment determined by qPCR. 53
Figure 2.5 – Transcriptional responses of Insulin-like growth factor
receptor and binding protein genes in the fast myotomal muscle of male
zebrafish during the course of the single meal experiment determined by
qPCR. 54
Figure 2.6 – Correlation between log fold changes in mRNA levels of 38
genes from qPCR and microarray experiments from two hybridizations. 66
Figure 2.7 – Hierarchical clustering and heat map of Insulin-like growth
factor (IGF) system gene transcripts and candidate nutritionally regulated
XII
genes identified from microarray experiments over the time course of the
single meal experiment. 67
Figure 2.8 – Expression profiles of ubiquitin ligase genes in male zebrafish
identified from microarray experiments over the time course of the single
meal experiment as determined by qPCR. 68
Figure 2.9 – Expression profiles of candidate nutritionally-regulated genes
in male zebrafish identified from microarray experiments over the time
course of the single meal experiment as determined by qPCR: genes up-
regulated during fasting. 69
Figure 2.10 – Expression profiles of candidate nutritionally-regulated genes
in male zebrafish identified from microarray experiments over the time
course of the single meal experiment as determined by qPCR: genes up-
regulated with feeding. 70
Chapter 3 Page
Figure 3.1 – Experimental design of the continuous darkness photoperiod
experiment. 83
Figure 3.2 - Intestine food content relative to body mass (A) and condition
factor (B) over the 48h of the photoperiod experiment. 88
Figure 3.3 – Heatmap and periodicity parameters calculated for the
screening reactions of the photoperiod experiment. 89
Figure 3.4 - Expression profile of zebrafish orthologues of genes known to
be positive regulators of the circadian pathway in mammals. 92
Figure 3.5 - Expression profile of zebrafish orthologues of genes known to
be negative regulators of the circadian pathway in mammals. 93
Figure 3.6 - Expression profile of zebrafish orthologues of the nuclear
receptor subfamily D, known to be negative regulators of the circadian
pathway in mammals. 95
Figure 3.7 - Expression profile of putative zebrafish clock-controlled genes. 97
Figure 3.8 – Comparison gene expression during continuous darkness and
12: 12h light: dark photoperiods. 98
Figure 3.9 – Heatmap and periodicity parameters calculated for the
individual reactions of the photoperiod experiment. 99
Figure 3.10 – Diagram of the molecular circadian mechanism in the
zebrafish. 107
XIII
Chapter 4 Page
Figure 4.1 – Experimental design for artificial selection and fasting and
refeeding protocols. 119
Figure 4.2 – 4 parameters – Gompertz growth equation. 121
Figure 4.3 - Growth curve from 6 to 390dpf and body mass at 390dpf of the
selected zebrafish lineages. 122
Figure 4.4 – Maternal transcripts of growth hormone and insulin-like
growth factors in zebrafish embryos from S-, U- and L-lineages. 125
Figure 4.5 – Maternal transcripts of receptors of growth hormone and
insulin-like growth factors in zebrafish embryos from S-, U- and L-lineages. 126
Figure 4.6 – Maternal transcripts of insulin-like binding proteins in
zebrafish embryos from S-, U- and L-lineages. 127
Figure 4.7 – Maternal transcripts of myogenic regulatory factors in
zebrafish embryos from S-, U- and L-lineages. 128
Figure 4.8 – Maternal transcripts of “fecundity genes” and their receptors in
zebrafish embryos from S-, U- and L-lineages. 129
Figure 4.9 – Gut food content of S- and L-lineages in response to fasting and
refeeding. 130
Figure 4.10 – Transcription levels that were similar for the S- and L-
lineages were averaged to produce a heatmap of gene expression in
response to fasting and refeeding independent of fish lineage. 133
Figure 4.11 – Differential level of expression of the ligands igf1a and igf2b,
and IGF receptors igf1ar, igf1br and igf2r between the S- and L-lineages in
response to fasting and refeeding. 134
Figure 4.12 – Differential level of expression of the IGF binding proteins
igfbp1a and igfbp1b, the myogenic regulatory factor myoD, and the kruppel-
like factor 11b between the S- and L-lineages in response to fasting and
refeeding. 135
Chapter 5 Page
Figure 5.1 – Role of ornithine decarboxylase (ODC) in the biosynthesis of
polyamines (putrescine, spermidine and spermine). 144
XIV
List of Tables
Chapter 1 Page
Table 1.1 – Comparison of the current state of some genome projects under
investigation by the Sanger Institute, with especial attention to fish
genomes. 6
Chapter 1 Page
Table 2.1 – Sequence and properties of primers used in the experiments of
chapter 2. 45
Table 2.2 – Biometry (mean ± standard deviation) of fish from the single-
meal experiment. 49
Table 2.3 – Filtered gene list from the microarray experiment showing
transcripts up-regulated with fasting in the zebrafish single meal
experiment. 58
Table 2.4 – Filtered gene list from the microarray experiment showing
transcripts up-regulated with feeding in the zebrafish single meal
experiment. 60
Table 2.5 – Enrichment analysis of gene ontology terms for biological
processes associated with genes differentially regulated in response to a
single-satiating meal using the 44K Agilent zebrafish microarray V2. 63
Chapter 1 Page
Table 3.1 – Sequence and properties of primers used in the experiments of
chapter 3. 85
Table 3.2 – Significant positive and negative Spearman’s correlation of gene
expression over the photoperiod experiment. 100
Chapter 1 Page
Table 4.1 – Number of individuals in the zebrafish populations from each
generation produced during this study. 114
Table 4.2 – Sequence and properties of primers used in chapter 4. 116
Table 4.3 - Effects of four rounds of artificial selection for body size of adult
zebrafish on early life-history traits of eggs and larvae. 123
XV
List of Abbreviations
akt v-akt murine thymoma viral oncogene
bHLH basic helix-loop-helix
BM body mass
cAMP cyclic adenosine monophosphate
CCGs clock-controlled genes
cGMP cyclic guanosine monophosphate
DAG diacylglycerol
ECL external cellular layer
FL fork length
GH growth hormone
GHr growth hormone receptor
GO gene ontology
Hh hedgehog
IGF insulin-like growth factor
IGFBP insulin-like growth factor binding protein
MAPK mitogen-activated protein kinase
MBT mid-blastula transition
MPC myogenic precursor cell
MRF myogenic regulatory factor
MT melatonin receptor
mTOR mammalian target of rapamycin
pf post-fertilization
PI3K phosphatidylinositol 3-phosphate kinase
PKC protein kinase C
PRL Prolactin
qPCR quantitative real-time polymerase chain reaction
ROR retinoid orphan receptor
RZR retinoid Z receptor
SL standard length
STAT signal transducers and activators of transcription
SUMO small ubiquitin-like modifier
T3 triiodothyronine
T4 thyroxine
TGF-β transforming growth factor – β 
TL total length
TSH thyroid stimulating hormone
UPR unfolded protein response
WGD whole genome duplication
YSL yolk syncytial layer
1Abstract
In the present study, the ease of rearing, short generation time and molecular research
tools available for the zebrafish model (Danio rerio, Hamilton) were exploited to
investigate transcriptional regulation in relation to feeding, photoperiod and
experimental selection.
Chapter 2 describes transcriptional regulation in fast skeletal muscle following
fasting and a single satiating meal of bloodworms. Changes in transcript abundance
were investigated in relation to the food content in the gut. Using qPCR, the
transcription patterns of 16 genes comprising the insulin-like growth factor (IGF)
system were characterized, and differential regulation between some of the paralogues
was recorded. For example, feeding was associated with upregulation of igf1a and igf2b
at 3 and 6h after the single-meal was offered, respectively, whereas igf1b was not
detected in skeletal muscle. On the other hand, fasting triggered the upregulation of the
igf1 receptors and igfbp1a/b, the only binding proteins whose transcription was
responsive to a single-satiating meal. In addition to the investigation of the IGF-axis, an
agnostic approach was used to discover other genes involved in transcriptional
response to nutritional status, by employing a whole-genome microarray containing
44K probes. This resulted in the discovery of 147 genes in skeletal muscle that were
differentially expressed between fasting and satiation. Ubiquitin-ligases involved in
proteasome-mediated protein degradation, and antiproliferative and pro-apoptotic
genes were among the genes upregulated during fasting, whereas satiation resulted in
an upregulation of genes involved in protein synthesis and folding, and a gene highly
correlated with growth in mice and fish, the enzyme ornithine decarboxylase 1.
Zebrafish exhibit circadian rhythms of breeding, locomotor activity and feeding
that are controlled by molecular clock mechanisms in central and peripheral organs. In
chapter 3 the transcription of 17 known clock genes was investigated in skeletal muscle
in relation to the photoperiod and food content in the gut. The hypothesis that myogenic
regulatory factors and components of the IGF-pathway were clock-controlled was also
tested. Positive (clock1 and bmal1 paralogues) and negative oscillators (cry1a and per
genes) showed a strong circadian pattern in skeletal muscle in anti-phase with each
other. MyoD was not clock-controlled in zebrafish in contrast to findings in mice,
2whereas myf6 showed a circadian pattern of expression in phase with clock and bmal.
Similarly, the expression of two IGF binding proteins (igfbp3 and 5b) was circadian and
in phase with the positive oscillators clock and bmal. It was also found that some
paralogues responded differently to photoperiod. For example, clock1a was 3-fold more
responsive than clock1b. Cry1b did not show a circadian pattern of expression. These
patterns of expression provide evidence that the molecular clock mechanisms in
skeletal muscle are synchronized with the molecular clock in central pacemaker organs
such as eyes and the pineal gland.
Using the short generation time of zebrafish the effects of selective breeding for
body size at age were investigated and are described in chapter 4. Three rounds of
artificial selection for small (S-lineage) and large body size (L-lineage) resulted in
zebrafish populations whose average standard length were, respectively, 2% lower and
10% higher than an unselected control lineage (U-lineage). Fish from the L-lineage
showed an increased egg production and bigger egg size with more yolk, possibly
contributing to the larger body size observed in the early larval stage (6dpf) of fish from
this lineage. Fish from S- and L-lineage exposed to fasting and refeeding showed very
similar feed intake, providing evidence that experimental selection did not cause
significant changes in appetite control. Investigation of the expression of the IGF-axis
and nutritionally-response in skeletal muscle after fasting and refeeding revealed that
the pattern of expression was not different between the selected lineages, but that a
differential responsiveness was observed in a limited number of genes, providing
evidence that experimental selection might have changed the way fish allocate the
energy acquired through feeding. For example, a constitutive higher expression of igf1a
was recorded in skeletal muscle of fish from the L-lineage whereas igfbp1a/b
transcripts were higher in muscle of fish from the S-lineage. These findings demonstrate
the rapid changes in growth and transcriptional response in skeletal muscle of zebrafish
after only three rounds of selection. Furthermore, it provides evidences that differences
in growth during embryonic and larval stages might be related to higher levels of
energy deposited during oogenesis, whereas differences in adult fish were better
explained by changes in energy allocation instead of energy acquisition.
In chapter 5 the main findings made during this study and their impact on the
literature are discussed.
Chapter 1
3
1. General Introduction
1.1. The zebrafish as a biological model system
Fish model species include the fugu (Takifugu rubripes) and the green spotted pufferfish
(Tetraodon nigroviridis), the stickleback (Gasterosteus aculeatus) the medaka (Oryzias
latipes) and the zebrafish (Danio rerio). In addition to having available information
about their genes and genome organization, each of these fish display interesting
characteristics as model species. For example, pufferfish are useful for studies of
genome evolution due to their very compact genome, while stickleback is often used to
model evolution of speciation in response to different environmental variables in
separate populations. Medaka and zebrafish are used in many fields of biology as
laboratory model species due to short generation time, genetic tractability, and ease of
rearing and spawning in a controlled environment.
Among the fish model species zebrafish has attracted the most attention from the
scientific community, resulting in the unravelling of its anatomy, behaviour and
physiology. Although big progress has been made in understanding this model system
much remains to be discovered as evidenced by the recent publication of an atlas of
anatomy and histology of the whole body (Menke et al., 2011) and a 3D reconstruction
of the zebrafish brain (Ullmann et al., 2010). There are many reasons for the great
interest in the zebrafish, but what first made it so attractive to scientists interested in
embryology and development was the transparency of the body during the early-life
stages, which made the observation and characterization of the whole process of body
and organ formation possible using light-microscopy. Apart from some important
differences in physiology, the zebrafish is being more and more used for biomedical
research with focus on human diseases, the reason being that most biological processes
underlying pathogenesis are conserved even between invertebrates and higher
vertebrates and are recapitulated in the fish model (Lieschke and Currie, 2007). Here
again zebrafish excel in being an excellent model due to the low costs when compared
to the mouse model (whose anatomy and physiology is more related to humans), to the
genetic tractability and ease with which phenotypes can be followed visually, without
the need for invasive, costly and time-demanding procedures. The body transparency
Chapter 1
4
during embryonic and larval stages is important in a model in modern biomedical
research allowing for direct observation of mutants and transgenesis, in the latter case
with the use of fluorescent constructs. With effect, the zebrafish model has been
successfully employed in a number of cases to model monogenic (e.g.: muscle dystrophy
and iron-storage disorder) and polygenic human diseases (e.g.: oncogenesis and
infection) making use of forward- and reverse-genetic experiments and transgenesis
[reviewed in (Lieschke and Currie, 2007; Delvecchio et al., 2011)]. Forward-genetic
experiments resulted in a number of mutants being generated that are publicly
available from The Zebrafish Model Organism Database (www.zfin.org) and from the
Zebrafish Mutant Project under development by the Sanger Institute
(http://www.sanger.ac.uk/Projects/D_rerio/zmp/). While the ZFIN mutant fish lines
relies on submission of information on and samples of mutants by the scientific
community, the Sanger initiative set-out to mutate every single protein-coding gene,
with 1,627 genes mutated so far, and make this information publicly available with the
possibility to request mutate alleles from their website. The tractability of zebrafish has
also proven useful in drug-discovery screening in which hundreds of embryos can be
simultaneously exposed to candidate drugs [reviewed in (Lieschke and Currie, 2007)].
In fact, this model is in use by many pharmaceutical industries, including the giant
Swiss-based pharmaceutical company Novartis (Delvecchio et al., 2011).
The zebrafish also has a great potential as a model for experiments in
aquaculture. Advantages include previous studies of its bioenergetics (Chizinski et al.,
2008), behaviour (Miller and Gerlai, 2007), growth (Siccardi et al., 2009) and swimming
metabolism (Plaut and Gordon, 1994) that could be used in comparative studies with
economically important fish for the aquaculture industry. Despite the acceptance and
broad use of the zebrafish in biomedical sciences, the potential of this biological model
is often overlooked in the aquaculture fields of nutrition, growth and disease.
1.1.1. The zebrafish genome, linkage map and whole genome duplication
Without question, the construction of linkage maps and the sequencing of the zebrafish
genome were two important factors that helped the zebrafish model become so
important for research. Linkage maps facilitated the investigation of mutant zebrafish
lines through the use of synteny analysis and permitted a comparative analysis with
Chapter 1
5
other vertebrate genomes (Woods et al., 2000). In addition, genetic maps are important
for the analysis of quantitative trait loci (QTL), in which portions of the genome are
analysed for their influence on a certain trait, and for the study of cis-regulation of
expression among genes. In February 2001 the Sanger Institute started the Zebrafish
genome sequencing project in collaboration with the zebrafish community. Ten years
later, in May 2011 the ninth assembly version was released which shows that the
zebrafish genome is composed of 25 autosomal chromosomes and 1 mitochondrial
chromosome, in a total of 1.7 Giga base-pairs with around 18,000 known protein-coding
genes (Table 1.1).
One known caveat of using zebrafish to model human diseases is that teleosts
have undergone a whole genome duplication (WGD) after radiation of the tetrapods
(Jaillon et al., 2004). WGD events are thought to be one of the possible mechanisms
responsible for increasing the complexity of a genome. Following a WGD event two
copies of every gene are found in the genome and are termed paralogues. Inter- and
intrachromosomal rearrangements (e.g.: fusion and break) and a massive gene loss
occurs in the unstable newly duplicated genome, resulting in the rediploidization of the
genome (Jaillon et al., 2004; Volff, 2005). These genomic rearrangements allow for the
paralogues to take different fates depending on their function and importance for the
organism. While there is a possibility that the organism might benefit from the higher
gene dose, it is believed that only 15% of paralogues are retained in extant species with
most duplicated genes suffering loss of function due to detrimental mutations over
evolutionary time and are lost from the genome (Jaillon et al., 2004). Additionally, in
most cases retained paralogues show a divergence in their genomic sequence that
affects the regulatory, intronic and coding sequences, usually resulting in differences in
regulation of expression and biological activity. In rare events, the divergence in
sequence leads to a beneficial completely new function for one of the paralogues,
termed neofunctionalization (Force et al., 1999). Another possible fate is
subfunctionalization, when two retained paralogues share different aspects of the same
function (Force et al., 1999). It is thought that three main WGD events occurred in the
vertebrates: the first before the lamprey (Petromyzon marinus, considered the least
derived vertebrate), the second before the radiation of cartilaginous and bony fish, and
the third before radiation of the teleosts. Other WGD duplications are thought to have
occurred after radiation of the teleosts which affected several fish lineages, for example
Chapter 1
6
a WGD duplication event is known to have occurred after the radiation of salmonids. A
massive 50% loss of duplicated genes is thought to have occurred after WGD in
salmonids (Allendorf, 1979). This means salmonids may have twice as many paralogues
compared to other teleosts and four times as many as tetrapods. While it is considered a
disadvantage in comparative studies of fish with tetrapods, the WGD events presents
scientists with a unique opportunity to study genome evolution by comparing the
different species that have undergone WGDs with their ancestral species and species
that didn’t experience a WGD. The importance of WGD in fish physiology becomes
obvious when studying polygenic biological processes in which the retained paralogues
may have evolved unique gene regulation and functions.
Table 1.1 – Comparison of the current state of some genome projects under
investigation by the Sanger Institute*, with special attention to fish genomes.
Common name Scientific name Assembly
version
Genome
size (Mega
base-pair)
Known protein-
coding genes
Number of
Genes
(prediction)
C. elegans Caenorhabditis
elegans
WS220 103 20,389 N/A**
Fruitfly Drosophila
melanogaster
BDGP 5.25 168 13,781 19,437
Green spotted
pufferfish
Tetraodon
nigroviridis
TETRAODON 8.0 342 1,794 23,832
Fugu Takifugu
rubripes
FUGU 4.0 393 809 29,699
Stickleback Gasterosteus
aculeatus
BROAD S1 446 14 44,884
Medaka Oryzias
latipes
HdrR 700 1,631 123,380
Lamprey Petromyzon
marinus
PMAR3 831 N/A 161,311
Zebrafish Danio
rerio
Zv9 1,505 18,572 36,628
Human Homo
sapiens
GRCh37.p3 3,280 20,599 46,737
Mouse Mus
musculus
NCBIM37 3,420 21,873 46,375
* data retrieved from http://www.ensembl.org on September 2011.
** N/A – data not available
Chapter 1
7
1.2. Fish Growth and Muscle development
1.2.1. Fish growth
The scope of growth of a fish is a function of the balance of acquisition and expenditure
of energy. During embryonic and larval stages the energy supply comes from the yolk
and is mostly used for development, whereas in juvenile and adult stages it comes from
exogenous feeding and is mostly used for growth. For example, the zebrafish has a
typical growth curve that fits a logistical equation in which an indeterminate growth
pattern is observed [personal observations and (Eaton and Farley, 1974)] (Figure 1.1).
In this type of curve, the growth rate (increment in size per day) increases steadily to
reach a maximum (called point of inflection) at which point the growth rate starts to
decrease. The growth rate and point of inflection are highly dependent on
environmental factors and the genetic background of the fish.
Figure 1.1 – Typical curves of growth (red) and growth rate (blue) of a zebrafish.
0 50 100 150 200 250 300
0
5
10
15
20
25
30
-0.02
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
B
o
d
y
S
iz
e
(m
m
)
Age (dpf)
Inflection
Point
G
ro
w
th
ra
te
(i
n
c
re
m
e
n
t
in
b
o
d
y
s
iz
e
-
m
m
/d
a
y)
Chapter 1
8
1.2.2. Structure and function of the adult teleost myotome
Depending on the degree of phylogenetic complexity and development of the organism,
myotomes can be V or W-shaped segments of horizontally orientated muscle fibres
surrounded by connective tissue (the myocommata, which is analogous to the
epymisium in other vertebrates) (Van Leeuwen, 1999). The connective tissue is
composed of cells (of which fibroblasts are the most abundant) and the extracellular
matrix (composed of proteoglycans and proteins, of which collagen is the main
component) (Velleman, 1999). In adult teleosts, the bulk of the myotome (~90%) is
composed of fast-twitch fibres localized in the medial portion whereas the slow-twitch
fibres are localized laterally and adjacent to the major horizontal septum and account
for most of the remainder of the muscle fibres. In the developing and adult zebrafish
myotomes, intermediate muscle fibres are found at the major horizontal septum
between the regions of slow- and fast-twitch fibres (Johnston et al., 2009) (Figure 1.2).
The organization of the different types of muscle fibres in discrete layers in the
myotome is thought to reflect their distinct recruitment when different speeds are
required (e.g., routine and burst swimming) (Johnston et al., 1977). Slow-twitch fibres
are used for routine swimming, are rich in mitochondria, and have a constant supply of
oxygen due to high vascularization, thus most energy comes from aerobic metabolism
(Johnston et al., 1977; Johnston, 1982; Rome et al., 1984; Luther et al., 1995). On the
other hand, fast-twitch fibres are used in fast-start swimming mostly during prey
capture and evasion, have fewer mitochondria, and most energy comes from anaerobic
metabolism due to the rapid use of energy allied with a low blood supply owing to the
low vascularization of this tissue (Johnston, 1980, 1982; Luther et al., 1995).
Intermediate muscle fibres share some properties from both slow- and fast-twitch
muscle fibres. Thus the three discrete layers of muscle fibres are differentially recruited
in the flowing order as the level of activity increases: slow-, intermediate-, and fast-
twitch muscle fibres (Johnston et al., 1977).
Muscle fibres extend from the posterior to the anterior portion of the myotome
and are inserted in the connective tissue through short tendons (Johnston, 1980;
Yamaguchi et al., 1990). Bundles of muscle fibres are surrounded by the perymisium,
while the endomysium encloses the individual muscle fibres. Individual muscle fibres
contain myofibrils, which contain the basic contractile unit, the sarcomere (Figure 1.2).
Chapter 1
9
When the sarcomere is observed by electron microscopy three vertical lines are
observed: two Z-lines (or Z-discs) flanking each end of the sarcomere and one M-line in
the middle of the sarcomere (Figure 1.2). The Z-line is composed mainly of α-actinin and 
provides support for the horizontal thin filaments which are perpendicularly oriented
towards the M-line in both sides of the Z-line [reviewed in (Craig and Padrón, 2004)].
The M-line is composed of myomesin, M-protein and creatine kinase and provides
support for the horizontal thick filaments which are perpendicularly oriented towards
the Z-line in both sides of the M-line [reviewed in (Craig and Padrón, 2004)]. Titin is a
giant elastic protein that spans from the Z-line to the M-line and closely associates with
the thick filaments, playing a major role in the maintenance of the alignment and
orientation of the thick filaments in the sarcomere (Figure 1.2) (John, 1992). The clear
area observed between the Z- and M-lines is formed by the thin filaments and is called
the I-zone whereas the dark area is formed by thick filaments and is called the A-zone
(Figure 1.2) (Huxley and Hanson, 1954). Hundreds of actin molecules orientated in a
helix form the backbone of the thin filament (the polymer is also called F-actin) with
tropomyosin and troponin attached to the thin filament at regular intervals [reviewed
by (Craig and Padrón, 2004)]. The two latter proteins regulate the contraction
mechanism triggered by Ca2+. The length of the thin filament is thought to be controlled
by a giant protein, nebulin, although this function remains contentious (Figure 1.2)
(John, 1992; McElhinny et al., 2003). The thick filament is mainly composed of myosin
molecules comprising 6 polypeptides (2 heavy chains and 4 light chains), arranged in a
ɑ-helix at the C-terminal (also known as tail) and the globular heads on the N-terminal. 
The assembly of many molecules of myosin in a helical orientation result in the rod
structure of the thick filament formed by the myosin tail on the axis and the head on the
surface. The head region of the myosin molecule has actin-binding and ATPase
properties. Shortening of the sarcomere and muscle contraction is based on the sliding
of the thick and thin filaments which occurs through the interaction of the myosin head
with the actin molecule, in a process that is dependent of Ca2+ and ATP (Huxley and
Hanson, 1954).
Chapter 1
10
Figure 1.2 – (A) Muscle fibre types in a cross-section of adult zebrafish and myotome
structure, and (B) a simplified drawing of the muscle and sarcomere structure, the
contractile unit of skeletal muscle. Muscle structure was adapted from
http://topvelocity.net/why-some-pitchers-throw-harder-than-others/
Chapter 1
11
1.2.3. Zebrafish embryonic development, cell fate map and embryonic cell layers
The myotomes originate from the embryonic somites formed during development of the
embryonic cell layer called mesoderm. In this section the morphogenetic movements
that result in the formation of embryonic cell layers will be summarized using the
staging system described by Kimmel et al. (1995).
After fertilization, the fish egg is composed of a single blastomere (the animal
pole) on the top of the yolk (the vegetal pole) (Figure 1.3). The single blastomere
undergoes a series of synchronous cell divisions, linearly increasing the number of
blastomeres from 2 [around 45min post-fertilization (pf), beginning of the
segmentation period] to 512 (around 2h45min pf, in the middle of the blastula period)
(Figure 1.3). During the 512-cell stage a number of important changes occur in the cell
cycle and zygotic activation: the blastomeres at the margin of the yolk release their
cytoplasm and nucleus into the yolk cytoplasm, originating the yolk syncytial layer
(YSL) which will lie between the yolk cell and the blastomeres; the cell cycle starts to
lengthen and to become asynchronous; the lengthening of the interphase is concomitant
with the increase of production of RNA (zygotic activation) and the motility of cells.
These changes are collectively known as the mid-blastula transition (MBT). It is
believed that maternally-deposited mRNAs control the basic cellular functions prior to
MBT (Pelegri, 2003), but these transcripts are also believed to simply function as a
nutritional reserve (Hunter et al., 2010). In chapter 4 the levels of maternal transcripts
in selectively bred zebrafish are investigated. The progression of the asynchronous cell
divisions after MBT results in the dome stage, when the YSL starts to dome towards the
animal pole and, subsequently, tiers of blastomeres at the margin of the yolk cell
(blastoderm) starts to move towards the vegetal pole (a process that is called epiboly)
(Figure 1.3). When the blastoderm covers 50% of the yolk-cell (50% epiboly) the
blastomeres in the front of migration to the vegetal pole start to involute towards the
medial portion of the yolk-cell and marks the beginning of the gastrula period (~5.3hpf,
Figure 1.3). Injection of blastomeres with tracer dye at this stage allowed for the
construction of a cell fate map for the zebrafish, with the origin of many organs and
structures in the embryo being traced back to specific regions in the blastoderm at the
50%-epiboly stage (Kimmel et al., 1990) (Figure 1.3). The continuation of epiboly
results in the formation of a germ ring, a thick layer of blastomeres concentrated at the
50%-epiboly position. The blastoderm at the germ-ring consists of two layers of
Chapter 1
12
blastomeres: the epiblast and the hypoblast, the two first embryonic cell layers.
Movements of convergence start during the germ-ring stage and subsequently results in
the formation of the shield (Figure 1.3). Movements of convergence entail the migration
of blastomeres from all regions of the blastoderm to the future embryo axis. The region
of the shield will originate the structures of the embryo head, allowing for the
distinction of the future anterior-posterior axis. After the formation of the shield epiboly
resumes and the blastoderm folds back upon itself, separating the epiblast and
hypoblast by a fissure, the Brachet’s cleft, at the 75%-epiboly stage (Figure 1.3). After
the end of gastrulation, three embryonic layers are formed: the ectoderm is originated
from the epiblast and will form the epidermis and central nervous system, while the
mesoderm and endoderm originate from the hypoblast. Lineage tracer dye experiments
reveal that cells from the endoderm will give rise to the intestine and pharynx whereas
the mesoderm will give rise to blood cells, and somites among other structures and
organs (Kimmel et al., 1990).
After completion of epiboly, around 10hpf, the segmentation of the paraxial
mesoderm gives rise to the somites that at this stage have an epithelial aspect, with a
layer of superficial cells surrounding a group of mesenchymal cells. Cell lineage dye
tracing of the mesenchymal cells reveals that they will form the bulk of the myotome
(Kimmel et al., 1995), whereas the cells on the superficial layer adjacent to the
notochord (the medial somitic epithelium), called adaxial cells, are the slow muscle
precursor cells (Thisse et al., 1993) (Figure 1.4). The ventromedial epithelium of the
somites will give rise to sclerotome cells that will migrate between the adaxial cells and
the notochord, and originate the vertebral cartilage and later the axial skeleton (Figure
1.4). A third derivative of the somite, the dermomyotome, is formed from the anterior-
most layer of somitic cells and will form the external cell layer (ECL) (Figure 1.4). The
morphogenetic movements involved in myogenesis and larval myotomal structure
formation will be summarized in section 1.3.6.
Chapter 1
13
Figure 1.3 – Zebrafish development from 1-cell to 26-somite stage, with emphasis in
the cell fate map during 50% epiboly and the two embryonic layers formed during
gastrulation [adapted from (Kimmel et al., 1990; Kimmel et al., 1995)].
Chapter 1
14
1.2.4. Transcription factors as master switches during myogenesis
During myogenesis muscle-specific transcription factors bind to the regulatory
sequences of muscle genes to start specific transcriptional programs that will dictate
the fate of the cells. Specific expression of the transcription factors serves as a molecular
marker of cell lineage and metabolic status and has been fundamental for unravelling
muscle development processes. Knockout and knockdown experiments in the mouse
and zebrafish models, respectively, have been fundamental in the investigation of the
function of the transcription factors in myogenesis by exploring the effects of loss-of-
function of single genes or combination of genes of a pathway. In this section the
fundamentals of knockout and knockdown experiments will be summarized together
with the main evidences on the transcription factors that are important for myogenesis.
The mutation of embryonic stem cells with a vector containing the mutation of
interest is the first step in the production knockout mice [reviewed in (Capecchi, 2005)].
Successful transformation of the target sequence is achieved by homologous
recombination of the vector with the stem cell’s DNA, which can be confirmed by
chemical resistance screening. The mutated embryonic stem cell is then inserted into
blastocysts and transferred to a pseudo-pregnant foster mother whose progeny will be
heterozygous to the mutation and are called chimeras. Homozygous animals carrying
the mutation can be produced by crossing two heterozygous chimeras. Using this
technique the sequence of genes of interest can be specifically targeted and transformed
into non-functional sequences or simply changed to a non-coding sequence (Capecchi,
2005). In morpholino-based knockdown experiments, a morpholino molecule
containing a sequence complementary to the target mRNA blocks its splicing into
mature mRNA and its translation into protein (Summerton and Weller, 1997;
Nasevicius and Ekker, 2000). In contrast with the permanent effects of the knockout
technique, knockdown by morpholino is transient and does not change the genome of
the animal (Lawson and Wolfe, 2011). However, morpholino-based knockdown is still
the technique of choice to investigate gene function in the zebrafish due to the lack of
reverse-genetic techniques that targets specific sequences of DNA. New techniques that
target and change specific genomic sequences in the zebrafish are currently under
development [reviewed in (Lawson and Wolfe, 2011)].
MyoD, myf5, myf6 (also known as mrf4) and myog are members of the family of
basic helix-loop-helix (bHLH) family of myogenic regulatory factors (MRFs) with
Chapter 1
15
fundamental importance for myoblast specification (myoD, myf5 and myf6) and
differentiation (myf6 and myog). Knockout and knockdown experiments show that the
functions of some MRFs are redundant. For example, double knockout of myoD and
myf5 produced mice without myoblasts and skeletal muscle (Rudnicki et al., 1993),
whereas single knockout of either myoD or myf5 produced mice with a muscle
phenotype similar to the wild-type (Braun et al., 1992; Rudnicki et al., 1992). This
redundancy in function of myoD and myf5 was recapitulated in zebrafish embryos using
the morpholino knockdown technology (Hammond et al., 2007; Hinits et al., 2009). In
mice, myf6 functions in specification of myoblasts and their subsequent differentiation
into muscle fibres. Evidence for myf6 role in specification and differentiation came from
knockouts of myoD/myf5 and myog, respectively (Sumariwalla and Klein, 2001; Kassar-
Duchossoy et al., 2004). Morpholino knockdown of myf6 in zebrafish embryos caused
impaired myofibril alignment, causing a loss of fibre integrity and attachment (Wang et
al., 2008). However, the function of myf6 in zebrafish muscle remains contentious since
recent findings do not corroborate the function of myf6 in myofibril alignment (Hinits et
al., 2009). Contrary to the situation in mouse, the zebrafish myf6 does not seem to be
capable of specification of myoblasts as evidenced by lack of myf6 expression in double
knockdown of myoD and myf5 (Hinits et al., 2007). Knockout of myog in mice is lethal
and muscle fibres do not differentiate correctly (Hasty et al., 1993; Nabeshima et al.,
1993). In the zebrafish, double ablation of myoD and myog results in loss of most fast
muscle whereas single myog ablation had almost no effect on fast muscle phenotype,
this led to the conclusion that myog is not essential to differentiation in zebrafish fast
muscle (Hinits et al., 2009).
Other transcription factors play important roles in muscle development. For
example, the myocyte enhancer factor 2 (mef2) is not synthesised until onset of MRF
expression providing evidence that this transcription factor is not fundamental for
muscle specification, but its expression greatly augments the differentiation of the
developing muscle and it is involved in myofibrillar thick filament assembly (Hinits and
Hughes, 2007). In addition, ablation of expression of mef2 in zebrafish embryos led to
impaired posterior somite formation, probably mediated by Hedgehog (Hh) signaling,
defects in sarcomere assembly and impaired cardiac contractility (Wang et al., 2005;
Wang et al., 2006).
Chapter 1
16
Apart from the MRFs other proteins have important functions in muscle
development and growth and have been the focus of attention due to the possibility of
producing animals with increased muscle mass. For example, myostatin is a member of
the transforming growth factor-β (TGF-β) superfamily with potent inhibitory functions 
of myogenesis which affects myoblast proliferation and differentiation (Lee, 2004). In
knockdown experiments in zebrafish, suppression of myostatin expression caused an
increase in myoD and myog expression together with an increase in the number of
somites in early development (Amali et al., 2004) providing evidence of an augmented
myogenesis. More recently, a double-muscle phenotype was observed in adult zebrafish
when myostatin was suppressed using RNA interference technology, resulting in
enhanced expression of myoD, myog, myf5 and myf6 (Lee et al., 2009). In addition,
overexpression of follistatin, a negative regulator of proteins from the TGF-β 
superfamily, including myostatin, produced a significant increase in muscle mass in
rainbow trout and zebrafish mediated by enhanced hyperplasia (Medeiros et al., 2009;
Li et al., 2011).
Chapter 1
17
1.2.5. Fish myogenesis
The organization of the adult myotome in discrete zones with different fibre types is
determined during embryogenesis through complex morphogenetic processes. Most of
what is known about fish myogenesis comes from the zebrafish model. The basic
mechanisms of stem cell commitment to myogenic precursor cells (MPCs), subsequent
differentiation into myoblast and migration and fusion into myotubes are shared among
vertebrates [reviewed in (Johnston, 2006; Johnston et al., 2011)]. Important differences
in myogenesis between fish and other vertebrates include the time of onset of the slow
muscle precursors in fish, adaxial cells, which occurs before complete somite formation,
and continued formation of fast muscle myotubes into adult stages (Rowlerson and
Veggetti, 2001).
Myogenesis can be separated in three different phases: embryonic myogenesis,
stratified hyperplasia and mosaic hyperplasia. Around 10 hours post-fertilization (hpf)
the first somite is formed in the developing zebrafish embryo (Kimmel et al., 1995). The
somites will differentiate into the ECL (also known as dermomyotome), the different
skeletal muscle cells and the axial skeleton.
In zebrafish, myogenesis start in the early segmentation period of the embryonic
development (~10hpf). MPCs flanking the notochord start to express the muscle-
specific transcription factor myoD. Expression of myoD commits the MPCs to a slow
muscle cell lineage fate and these are termed adaxial cells (Devoto et al., 1996). As
somite formation progresses, three discrete cell populations are observed in the somite
during the early segmentation period: the adaxial cells flanking the notochord (which
express pax7 and myoD); the anterior somite localized to the rostral portion of the
somite (which express pax3 and pax7); and the posterior somite localized to the caudal
portion of the somite (expressing pax7, myoD and myog) (Figure 1.4) (Devoto et al.,
1996; Stellabotte and Devoto, 2007). Time-elapsed analysis of single cell migration
shows that during the mid-segmentation period the somite rotates 90º so the anterior
and posterior regions of the early somite become laterally (the dermomyotome) and
medially localized (fast-cell precursors) whereas the adaxial cells (slow-cell precursors)
remain in their initial position (Figure 1.4) (Hollway et al., 2007). At this stage the
notochord secretes glycoproteins from the Hh family, which signals for the adaxial cells
to become slow-fibres. The nascent slow muscle fibres start to express myosin heavy
chain, and change to a more elongated morphology. These are the first cells to show
Chapter 1
18
contractile properties, and are termed pioneer muscle cells (Figure 1.4) (Devoto et al.,
1996). The remainder of slow myoblasts migrate radially away from the medial region
(Figure 1.4). At late-segmentation, the somite rotation and migration of slow myoblasts
are complete, with the fast myoblasts in the most medial region of the somite and
starting to differentiate into fast-twitch myotubes, and the slow myoblasts forming a
layer of cells subcutaneously to the ECL (Hollway et al., 2007; Stellabotte and Devoto,
2007). The ECL will provide the skin and myotomes with MPCs (pax3 and pax7
positive), satellite cells (pax7 positive), and dermal cells (Hollway et al., 2007). The
process of somite formation ends around 24hpf when ~30 somites can be observed in
the zebrafish (Kimmel et al., 1995).
Stratified hyperplasia is observed when MPCs differentiate into myoblasts and
start to form new slow-twitch myotubes mainly in the dorsal and ventral medial regions
(termed germinal zones) whereas myoblasts originate fast-twitch myotubes at the
periphery of the myotome (Figure 1.4) (Rowlerson and Veggetti, 2001). At this stage
two processes are observed: myoblast to myoblast fusion, resulting in new myotubes;
and myoblast to myotube fusion, resulting in myotube maturation. This phase of
myogenesis is so called due to the discrete zones of myotube formation observed
(Figure 1.5). In contrast with the differentiation of adaxial cells into slow myoblasts, the
differentiation of MPCs in the germinal zones into new slow myoblasts is not entirely
dependent on the Hh pathway (Barresi et al., 2001). However, ablation of this pathway
led to formation of fewer slow myotubes when compared to wild-type zebrafish
(Barresi et al., 2001). Stratified hyperplasia accounts for most slow-twitch muscle fibres
produced during the larval stage in many fish, but slow-twitch myotubes continue to
form from the germinal zones throughout the life-cycle of many fish [reviewed in
(Johnston, 2006)].
In the last phase of myogenesis, mosaic hyperplasia, quiescent pax7-positive
cells differentiate into myoblasts and fuse to existing fast-twitch myotubes throughout
the myotome which results in a mosaic of muscle fibres with different diameters (Figure
1.5) (Stellabotte and Devoto, 2007) (Figure 1.5). Most fast muscle fibres that form in the
late larval period and in adult stages are produced through mosaic hyperplasia
(Johnston, 2006), which continues until ~50% of the maximum body length (Johnston
et al., 2009).
Chapter 1
19
Figure 1.4 – Rotation of the somite during zebrafish embryonic myogenesis [adapted
from (Kimmel et al., 1995; Devoto et al., 1996; Hollway et al., 2007; Stellabotte and
Devoto, 2007)].
Chapter 1
20
Figure 1.5 – Stratified and mosaic hyperplasia in zebrafish larvae [adapted from
(Johnston et al., 2009)]. The arrow points to layers of increased fibre diameter and
asterisks marks fibres surrounded by smaller fibres.
Chapter 1
21
The maximum fibre number produced by stratified and mosaic hyperplasia is
positively correlated with fish body size and is influenced by environmental
temperature [reviewed in (Johnston, 2006; Johnston et al., 2011)]. Subsequent increase
in muscle mass is achieved by hypertrophy whereby the muscle fibres expand in
diameter and length by absorbing myoblasts [reviewed in (Johnston et al., 2011)]. This
becomes evident when growth curves are compared to fibre recruitment curves, in
which increments in body size are not followed by significant increments in fibre
number when fish reach 50% of the maximum body size (Figure 1.6)
Figure 1.6 – Comparison between curves of body size and fibre number recruitment in
the zebrafish. Data from growth were obtained from measurements of thousands of
zebrafish kept at 27ºC from embryonic to adult stages (personal observations) and data
for the fibre number curve are derived from (Johnston et al., 2009) (embryonic
temperature of 26ºC, rearing at 26ºC).
0 50 100 150 200 250 300 350 400
0
5
10
15
20
25
30
35
40
Age (dpf)
E
s
tim
a
te
d
T
o
ta
l
L
e
n
g
th
(m
m
)
0
500
1000
1500
2000
2500
3000
3500
4000
E
s
tim
a
te
d
F
ib
re
N
u
m
b
e
r
p
e
r
C
ro
s
s-se
ctio
n
a
lA
re
a
~50% maximum
body size
Chapter 1
22
1.3. Hormonal regulation of growth
Muscle fibres are metabolically active and receive molecular information from other
tissues in the form of macromolecules and metabolites conveying information on
environmental conditions (e.g. photoperiod length and periodicity), and are also
capable of sensing their environment (e.g. nutrient levels and temperature). Mediated
by hormonal signals, the transcriptional activity of muscle fibres is changed in response
to the environment and molecular signals are produced, which will act in other tissues
or locally. The molecular mechanisms triggering transcriptional change by some
hormonal pathways are summarized in this section.
1.3.1. Growth Hormone (GH)
GH, produced in the pituitary gland, is a protein consisting of 191 amino acids with
anabolic effects on metabolism, and its actions are realised by its binding to the
ubiquitously expressed growth hormone receptor (GHr). Binding of GH to GHr on the
plasma membrane triggers receptor dimerization and phosphorylation, with
subsequent phosphorylation of the tyrosine kinases of the Janus Family (JAK).
Phosphorylation of GH receptors and JAK activate several intracellular pathways
including the mitogen-activated protein kinases (MAPK), phosphatidylinositol 3-
phosphate kinase (PI3K), diacylglycerol (DAG), protein kinase C (PKC), intracellular
calcium (Ca2+) and the signal transducers and activators of transcription (STATs) that will
affect the cellular metabolism at many levels [revisited by (CarterSu et al., 1996)]. For
example, the uptake of glucose and control of cell survival are mediated by activation of the
PI3K pathway. While many of these effects will be indirect and mediated by the different
relevant pathways, phosphorylation of STATs (STAT1, STAT3, STAT5) will ultimately
result in activation of GH-dependent gene expression and represent a direct effect of GH
binding on cellular metabolism (Herrington et al., 2000). Some of the anabolic effects of GH
are realised by the activation of the insulin-like growth factor (IGF) pathway (section 1.4.2).
In fish, the level of circulating GH is modulated by many factors including temperature,
salinity, photoperiod, nutrition and stress [reviewed in (Björnsson et al., 2002; Perez-Sanchez
et al., 2002)]. Given its importance for the somatic growth axis, this hormone has been the
focus of a few overexpression experiments, with the results varying from a 2.6- to a 10-fold
increase in body size for the zebrafish and coho salmon (Oncorhynchus kisutch), respectively
Chapter 1
23
(Devlin et al., 1995; Figueiredo et al., 2007). However, overexpression of GH in zebrafish
can result in detrimental effects on the animal such as decreased transcription of the anti-
oxidant defence system and the myogenic factors myoD and myog, and an accelerated
senescence in adult fish (Rosa et al., 2010).
1.3.2. Insulin-like Growth Factors (IGF) pathway
The IGF pathway is composed of two ligands (igf1 and igf2), two receptors (igf1r and
igf2r) and six binding proteins (igfbp1-6). IGFs’ release in target tissue and their binding
to their receptors is modulated by insulin-like growth factors binding proteins (IGFBPs)
and proteases (Duan et al., 2010). Binding of the ligands to igf1r causes phosphorylation
of a series of protein kinases that will ultimately lead to activation of the
PI3K/AKT/mTor pathway, increasing protein synthesis (mediated by AKT and mTor)
and decreasing protein degradation (mediated by AKT and FOXO transcription factor),
thus promoting growth [reviewed in (Glass, 2003, 2005)]. On the other hand, binding to
igf2r leads to lysosomal degradation of the ligand (Lau et al., 1994; Wang et al., 1994)
and seems to be a mechanism of regulation of circulating IGF concentration. While IGF
receptors are ubiquitously expressed, the liver is the main organ that produces
circulating IGFs and IGFBPs. However, IGFs and IGFBPs are also produced by other
peripheral tissues such as skeletal muscle in response to both GH and nutritional stimuli
with possible paracrine and autocrine actions. Due to the whole genome duplication
some teleosts have twice as many components in this pathway when compared to
tetrapods. For example, the zebrafish has 16 known components, compared to 10 found
in the mouse. The IGF system has been proven to be important not only for cellular
growth, but also for normal development of the zebrafish as evidenced by igf1ra/b
knockdown in which the IGF signaling was disrupted, with various detrimental effects
on embryonic development including organ formation and muscle contractility
(Schlueter et al., 2006; Schlueter et al., 2007). In addition, double-knockdown of igf2a/b
caused malformation of the midline, and defects on kidney development (White et al.,
2009). Changes in the level of IGFBP in fish have also been proven to be of importance
for normal development and growth. For example, overexpression of igfbp1 caused
growth retardation and knockdown of this gene during hypoxia decreased the growth
retardation (Kajimura et al., 2005). Knockdown of igfbp2 and igfbp3 caused
Chapter 1
24
cardiovascular defects and retardation of development of pharynx and ear, respectively
(Li et al., 2005; Wood et al., 2005b). However, knockout of single IGFBP genes in mice
resulted in phenotypes not strikingly different from the wild-types [reviewed in (Duan
et al., 2010)]. This suggests some caution is necessary when extrapolating results on the
IGFBPs from the mice model to fish species.
The transcriptional regulation of the IGF pathway in response to nutritional
levels in skeletal muscle and to the genetic background of the zebrafish is the focus of
Chapters 2 and 3, respectively.
1.3.3. Cortisol
Cortisol is a glucocorticoid with anti-inflammatory and catabolic actions produced by
the adrenal gland mainly in response to stressful conditions. Its molecular mechanism
of action starts with the hormone binding to an inactive glucocorticoid receptor (GR) in
the cytoplasm. Activated cortisol-GR complex is capable of causing its anti-inflammatory
actions through a synergistic mechanism that includes (1) a transrepression cascade by
inhibiting a series of kinases (p38, ERK1/2 and JNK) and NF-KappaB, and (2) directly
inhibition of c-Jun- and c-Fos-dependent gene expression that would ultimately lead to
expression of inflammatory cytokines (Barnes, 1998; Labeur and Holsboer, 2010).
Cortisol-GR complexes also have direct activation and repression actions on gene
expression which are realised by dimerization of activated cortisol-GR complexes. The
dimers bind to responsive elements in the DNA and directly repress gene expression
whereas interaction with other transcription factors (e.g., oct1, oct3, STAT5 and CREB)
will activate gene expression (Schoneveld et al., 2004; Labeur and Holsboer, 2010).
Most of what is known of cortisol mechanism of action comes from mammalian model
species, with little information on the molecular pathways conserved in fish. However,
in mammals and fish, cortisol seems to have similar functions during situations of stress
to repress cellular growth, promote protein and glycogen breakdown and increase the
circulating levels of glucose [reviewed in (Mommsen and Moon, 2001)]. For example,
fish exposed to different stressors show increased circulating levels of cortisol (Bernier,
2006). Cortisol, in conjunction with prolactin and GH, is important for seawater and
freshwater adaptation (McCormick, 2001; Sakamoto and McCormick, 2006). In a recent
publication, cortisol was able to decrease the expression of interleukins 6 and 8, two
Chapter 1
25
cytokines involved in inflammatory response, in a rainbow trout macrophage cell line
(Castro et al., 2011) providing evidence of a conserved molecular action of this hormone
in fish.
1.3.4. Thyroid hormones
In response to thyroid-stimulating hormone (TSH) produced by the pituitary gland, the
thyroid produces thyroxine (T4) and triiodothyronine (T3), the thyroid hormones,
which are considered anabolic since it causes a positive nitrogen balance (higher
protein synthesis). They enter the cell cytoplasm through membrane transporters,
where T4 is metabolised into the active T3 by iodothyronine deionidases (type I and II).
In the cytoplasm, T3 can have a non-genomic molecular effect by activating the
PI3K/AKT/mTor pathway (Yen, 2001; Moeller et al., 2006) that will ultimately lead to
protein synthesis. In the nucleus, T3 activates the thyroid receptor/retinoid-x receptor
complex (TR/RXR) which activates transcription of several genes involved in
intermediary metabolism and cellular processes (e.g., carbohydrate and lipid
metabolism, thermogenesis, muscle contraction, growth and cell cycle regulation) (Yen,
2001). Four transcripts for thyroid hormone receptors are found in fish and have
probably arisen from a single gene (Power et al., 2001). Thyroid hormone actions are of
great importance for the somatotropic axis as the thyroid receptors interact with the
promoter of GH (Farchi-Pisanty et al., 1997) and integrates nutrition and other
important physiological and developmental processes such as ossification (Saele et al.,
2003), oocyte growth (Tyler and Sumpter, 1996) and muscle accretion and myofibre
hypertrophy (Yang et al., 2007). Thyroid hormones are also known to play an important
role in metamorphosis of fish and amphibians (Carr and Patino, 2011), and a recent
report shows the importance of the pituitary-thyroid axis in adaptation of stickleback to
freshwater environments (Kitano et al., 2010).
1.3.5. Melatonin and the molecular clock
Light perception is initiated by photoreceptor cells in the retina (common to mammals
and fish) and pineal gland (fish only) mediated by the photopigment rhodopsin (Falcon,
1999; Falcon et al., 2007). The activation of this photopigment triggers a complex
molecular cascade involving several enzymatic steps, of which arylalkylamine-N-
Chapter 1
26
acetyltransferase (aanat) is considered the enzyme catalysing the limiting-rate step that
produces the “time-keeping hormone” melatonin (Falcon et al., 2011). In the absence of
light, aanat transcription is activated which is responsible for the peak levels melatonin
during the night (Besseau et al., 2006; Falcon et al., 2011). In teleosts, two aanat genes
(aanat1 and aanat2) are found and they have probably resulted from gene duplication
(Appelbaum et al., 2006). Melatonin receptors are found in the fish retina and brain,
where it modulates the secretion of GH and prolactin (PRL) in the pituitary (Mazurais et
al., 1999; Falcon et al., 2003). One low-affinity (MT3) and two high affinity (MT1 and
MT2) melatonin receptors have been described in fish (Barrett et al., 2003; Falcon et al.,
2007). The former functions in detoxification processes and apparently does not have
direct effects on somatic growth (Barrett et al., 2003) whereas the latter are seven-
domain transmembrane receptors coupled to G-proteins (Falcon et al., 2007). Binding of
melatonin to high-affinity receptors triggers the activation of several intracellular
pathways including cyclic AMP (cAMP), phospholipase C (PLC) and cyclic GMP (cGMP),
which are capable of depolarizing the cell membrane and causing changes in
transcriptional activity (neuroendocrine actions of melatonin) (Falcon et al., 2007).
Melatonin can also act directly on the nucleus mediated by the Retinoid Z Receptors
(RZR) and Retinoid Orphan Receptors (ROR) (Hardeland, 2009). The rhythmic nocturnal
production of melatonin coupled with its binding to nuclear receptors and subsequent
transcriptional regulation make this hormone the central oscillator of circadian rhythms in
vertebrates, conferring periodicity and rhythmicity to a molecular clock machinery that will,
in turn, drive metabolic rhythmicity.
In addition to melatonin, light entrains an intrinsic and complex clock machinery that
is based on transcriptional and post-translational regulation of protein synthesis. While
melatonin is mainly produced by eyes and pineal tissues (considered the central pacemakers),
the molecular clock components are found in the central pacemakers and in many other
peripheral tissues, and integrates the photoperiod information perceived by the eye and pineal
with metabolism and physiology in peripheral tissues. In mouse, the circadian system is
highly hierarchical, with the central pacemakers entraining and controlling the rhythmicity
and periodicity of peripheral circadian clocks (Ripperger et al., 2011). Research on the
molecular mechanism in the zebrafish points to a more dispersed control of the circadian
clocks as evidenced by a direct photoresponsiveness of internal organs to light (Whitmore et
al., 1998; Weger et al., 2011). The exact mechanisms by which central pacemakers entrain
Chapter 1
27
peripheral clocks remain to be established, but it is thought that a combination of neuronal
and hormonal information (including melatonin and glucocorticoids) is relayed to peripheral
tissues [reviewed in (Takahashi et al., 2008; Dibner et al., 2010)]. The core-clock molecular
machinery is composed of a positive and negative arm that rhythmically control the
transcription of the components of the clock, and an ancillary arm that fine-tunes the
expression of the main oscillators of the main components of the clock machinery. The clock-
drosophila homolog (clock) and the aryl hydrocarbon receptor nuclear translocator-like
(arntl, but commonly known as bmal) are the components of the positive arm of the
mechanism, they form heterodimers and activate the transcription of all core-clock
components genes that are controlled by the clock-mechanism. Clock:bmal heterodimers also
activate transcription of the negative oscillators period (per) and cryptochrome proteins (cry)
which, after translation, form heterodimers in the cytoplasm, translocate to the nucleus and
inhibit transcriptional activation by clock:bmal. The ancillary arm is composed of ROR and
REV-erb, which are, respectively, positive and negative regulators of clock and bmal
transcription. Due to the WGD that occurred at the base of teleost evolution, the zebrafish has
as many as twice the number of copies of each gene in this pathway. In addition, unlike the
mouse molecular clock, expression of two paralogues of negative oscillators namely per2 and
cry1a are directly responsive to light input (Tamai et al., 2007; Vatine et al., 2009), and a
growing number of genes were recently reported as being light-responsive or clock-
controlled in the zebrafish (Weger et al., 2011).
Thus, melatonin and the circadian clock machinery are responsible for the integration
of physiology with the photoperiod, with direct influence on gene expression. The
transcriptional regulation of the circadian machinery and some clock-controlled genes in
skeletal muscle of the zebrafish is described in Chapter 3.
Chapter 1
28
1.4. Biotic and abiotic factors affecting fish growth and myogenesis
Environmental factors are sensed by the organism and trigger an intricate physiological
response leading to an output response mediated by neuroendocrine pathways (e.g.,
modulation of behaviour, respiration, metabolism, sexual maturity, and tissue
differentiation). This change in physiological state in response to environmental
variables is commonly known as phenotypical or developmental plasticity, is limited by
the genetic variation of the population, and can have transient or persistent effects on
the physiology and organism fitness. In this section some abiotic and biotic factors
affecting fish growth and myogenesis will be summarized.
1.4.1. Temperature
Fish, as most biological systems, have an optimum temperature for growth and
development. Exposure to temperatures slightly higher or lower than the optimum will
lead to a decrease in growth due to the compensatory mechanisms elicited by the
change in temperature. However, exposure to temperature much higher or lower than
the optimum might result in malformation and lethality. In addition to the effects on
adult individuals, embryonic temperature causes a persistent effect on final muscle fibre
number in fish. For example, embryonic temperature affects the timing of development
of fish larvae which includes the timing of myogenic progenitor cell recruitment and
differentiation [reviewed in (Johnston, 2006)]. This was demonstrated in a number of
studies in which fish were exposed to a range of temperatures during embryonic
development and then transferred to a single rearing temperature for the remainder of
development and growth (Vieira and Johnston, 1992; Johnston et al., 2001; Xie et al.,
2001; Hall and Johnston, 2003; Fernandes et al., 2006; Macqueen et al., 2008). The
conclusions point to the hypothesis that exposure to different temperatures during a
critical stage of embryogenesis imprints the embryo to have a certain fate dependent on
embryonic temperature, affecting the timing of MRF expression and cell recruitment
(Vieira and Johnston, 1992; Johnston et al., 2001; Xie et al., 2001; Hall and Johnston,
2003; Fernandes et al., 2006; Macqueen et al., 2008).
The exact molecular basis of the changes in growth of adult fish induced by
temperature remains to be established. The GH-IGF axis, an output of various systems
involving acclimation and adaptation to different environmental conditions, is usually
Chapter 1
29
studied to explain the effects of temperature on somatic growth. For example, sunshine
bass, a hybrid fish produced for aquaculture purposes, acclimatized at 25 and 30ºC
(optimum temperature for its growth) had higher levels of plasma igf1 when compared
to fish acclimatized at lower temperatures (Davis and Peterson, 2006). This increase in
igf1 levels were probably due to activation of transcription since the authors did not
find a decreased plasma level of IGF binding proteins. Gabillard et al. (2003) have found
that plasma level of GH was increased without an increased gene expression in the
pituitary. In a recent review Gabillard et al. (2005) have discussed that the temperature-
induced increase in growth affects both embryonic and post-embryonic phases of
development and that this is mediated by the somatotropic axis. For example, higher
expression of igf2 was correlated with an increased growth induced by temperature,
whereas the expression of GH and igf1 were responsible for the growth during post-
embryonic stages (Gabillard et al., 2005). However, because temperature alone can
modulate reaction rates in the organism and oxygen content in the water, it can trigger
many other complex physiological responses unrelated to the GH-IGF axis which affect
physiology at many levels.
(Gabillard et al., 2003)
1.4.2. Nutrition
Nutritional status is a critical factor for fish growth. Food is the unique source for
energy acquisition and molecules which will serve as the building-blocks for developing
and growing tissues. Apart from providing energy, the nutritional status (satiety, food
deprivation, fasting) regulates a number of hormonal pathways that will affect body
growth in a complex fashion. For example, lack of nutrients normally leads to decreased
levels of IGFs and changes muscle metabolism from an anabolic to a catabolic state in
which the energy stores within the body are used for the basic maintenance of the
organism, involving gene regulation and protein phosphorylation cascades (Glass, 2003,
2005). Nutrition affects most hormonal pathways summarized in section 1.4. For
example, food deprivation causes a decrease in circulating thyroid hormones
(MacKenzie et al., 1998) and an increase in circulating levels of GH and cortisol (Shimizu
et al., 2009; Costas et al., 2010). Nutrient deprivation has been fundamental in
discovering the gene and protein networks that are important for the regulation of cell
Chapter 1
30
metabolism in fish (Rescan et al., 2007; Salem et al., 2007; Bower et al., 2008; Bower et
al., 2009; Bower and Johnston, 2010a; Fuentes et al., 2011).
1.4.3. Photoperiod
Photoneuroendocrine regulation is a complex physiological response to an external cue
mediated by several proteins and enzymes (summarized in section 1.4.5.), and plays an
important role in the modulation of somatic growth of fish. Photoperiod effects are
extremely pervasive in fish physiology as evidenced by a circadian rhythm of various
biological processes in rainbow trout (Oncorhynchus mykiss) (Boujard and Leatherland,
1992). The effects of photoperiod manipulation on somatic growth have been reported
in the literature by several researchers. Most of these works studied species dwelling in
environments which experience a strong seasonality in light conditions over the year,
including salmonids. For example, Atlantic salmon (Salmo salar) exposed to continuous
light periods showed an increased body size, growth rate and plasma level of GH
compared to individuals reared under 12: 12h dark: light regimes (Björnsson et al.,
2000; Nordgarden et al., 2006). However, juvenile salmon exposed to constant light
grow well but do not complete the parr-smolt transformation, in a process mediated by
the decreased circulating levels of thyroid hormones, GH and cortisol and local
expression of GHr (Stefansson et al., 2007). In another experiment on photoperiod
manipulation, melatonin plasma levels were directly negatively related to growth rate
levels in rainbow trout without a direct effect on igf1 levels, an important output of the
GH pathway (Taylor et al., 2005).
Photoperiod conditions also alter the final fibre number as evidenced in salmon
exposed to continuous light which had 23% more muscle fibres in early seawater stages
than the group exposed to ambient photoperiod (Johnston et al., 2003). In a recent
publication, pgc1α/β and the MRF myoD were reported as a clock-controlled gene and 
suppression of the positive circadian oscillator clock resulted in reduction of
mitochondrial volume and loss of contractility force, respectively (Andrews et al., 2010).
Thus, photoperiod can alter both embryonic and adult muscle physiology through
mechanisms that are still under investigation.
Chapter 1
31
1.4.4. Genetics
Each one of the physiological responses to environmental conditions is mediated by a
number of proteins, enzymes, transporters, and hormones (i.e., peptides and proteins)
or by its products (enzymatic modification of metabolites). It is not surprising, then, that
variations in the genetic pool and subtle variations in genomic sequence can elicit
differences in biological activity and ultimately physiological responses. These
variations can affect different aspects of the genomic sequence. Alterations in either the
regulatory, intronic and exonic sequences can lead to differences in gene expression (by
modified response cis-regulation), alter transcript stability, and the biological activity
itself, respectively.
Silverstein (2002) used quantitative genetics to study phenotypic variation of
feed intake of channel catfish (Ictalurus punctatus) as related to growth differences and
hypothesized that a difference of around 40% in phenotypic variance (feed intake in
this case) could be attributed to genetic variance. Larsen et al. (2007) studying the gene
expression in two populations of European flounders (Platichthys flesus) found that a
number of genes were differentially expressed between these populations, including
components of the somatotropic axis, with possible effects on fitness traits. Maybe the
most complete examples of scope for differential biological response elicited by genetic
variation comes from the study populations of Fundulus heteroclitus living in a range of
latitudinal clines which differed in environmental temperature. The researchers found
that the activity of lactate dehydrogenase-B (Ldh-B) is important for acclimation and
adaptation of this species to different environmental temperatures (Powers and
Schulte, 1998). It was hypothesised that Ldh-B activity could be regulated at many
levels: post-translational modification (i.e., enzyme phosphorylation and glycosylation),
changes in protein sequence, translation rate, mRNA untranslated sequences (mRNA
stability), alterations in intronic sequences (transcription), and changes in regulatory
DNA sequences (rate of transcription) (Schulte, 2001). Segal et al. (1996) found a high
level of variation in the non-coding (regulatory) sequence of the Ldh-B gene between
the two populations and this variation resulted in a distinct stress response (Schulte,
2001). Whitehead and Crawford (2006) studied the gene expression pattern of 329
genes of central metabolic pathways in five natural populations of F. heteroclitus
subjected to different temperature regimens. They found that 13 of the studied genes
presented a modulation of expression specifically related to temperature and that this
Chapter 1
32
gene expression varied within and among populations. Furthermore, the difference in
expression was related to an adaptive pattern rather than a neutral genetic drift
affecting the fitness of the organisms. Nei (2007) also highlighted the importance of
changes in both protein-coding and regulatory sequences in phenotypic evolution.
It is, thus, essential to identify and study candidate genes responsible for the
phenotypic differences within and among populations. Metabolic and hormonal
pathways represent a possible source of genetic differences that could explain partially
disparate growth rates among individuals.
(Silverstein, 2002)
(Larsen et al., 2007)
(Segal et al., 1996)
(Whitehead and Crawford, 2006)
Chapter 1
33
1.5. Fish domestication
With the decrease in natural populations of fish and with the growing importance of
reducing environmental impacts of human activities, cultured fish is becoming the only
acceptable method of fish meat production. A successful fish culture makes use of the
available information on the fish biology, encompassing water quality and temperature,
embryo and fry rearing, and optimal growth conditions and breeding strategies,
including optimal number of parents contributing to offspring as to maintain genetic
variation. This results in a change from growing in a highly varying environment in
nature to very controlled conditions in hatcheries, with important impacts in embryo
and adult physiology and behaviour, collectively known as domestication.
Domestication is mediated by the gradual change in the genetic pool of the organisms
due to the selective pressures encountered in fish cultures (e.g. absence of predation,
selective breeding, and photoperiod and temperature conditions). Common
physiological and behavioural responses to domestication include increased feeding
rate, decreased stress response and changes in aggression level (Robison and Rowland,
2005). For example, after five generations of selection for fork length of brown trout
(Salmo trutta) a significant increase in growth rate was recorded in the selected lines
owing to the increased feeding rate, with no difference in feed efficiency (Mambrini et
al., 2006). In captive fish the phenotypical changes in response to domestication can
occur rather faster, depending on the selective pressure when breeding animals for a
desired trait. For example, selection for body size of medaka for two generations
resulted in lineages with an inversely proportional growth rate to antagonistic
behaviour relationship (Ruzzante and Doyle, 1991). Despite the importance of
domestication to the aquaculture industry, the genetic variations imposed by captive
breeding and rearing are poorly understood. Experimental selection protocols can be
particularly valuable to this end, but the long generation time of aquaculture species
and high costs of keeping separate lineages for a long time in culture made this
approach underexplored. In a recent publication, domestication and GH-transgenesis of
coho salmon was found to have similar effects on IGF-axis genes in liver and muscle
(Devlin et al., 2009). The zebrafish has emerged as a model for studies of domestication,
in which a similar behavioural response was observed between zebrafish and salmonids
(Robinson and Rowland, 2005). The advantages of using zebrafish in selection
experiments to model domestication are clear, but some are highlighted in that paper.
Chapter 1
34
In addition to being valuable to the aquaculture industry in modelling
domestication responses in teleosts, selected lines of zebrafish could provide a unique
opportunity to model many other aspects in biology. For example, other model species
(e.g. mouse, Drosophila, and C. elegans) are used to investigate the effects of selection on
body composition and longevity. There are many interesting examples in the literature
of successful experimental selection on C. elegans and Drosophila including recent
discoveries of genes related to decreased effects of aging on the body phenotype
(Jenkins et al., 2004; Sarup et al., 2011). While the mouse model currently fulfils the role
of a vertebrate system for experimental selection, the zebrafish might prove valuable in
adding more information on genes associated with desirable traits.
Chapter 1
35
1.6. Objectives
 To characterize the transcriptional regulation of the IGF-system in zebrafish
skeletal muscle after a period of fasting followed by a satiating meal, using
quantitative PCR (qPCR) (Chapter 2);
 To identify genes and pathways involved in the biological process of anabolism
and catabolism observed during feeding and fasting, respectively, using a
genome-wide microarray (Chapter 2);
 To investigate the presence of circadian patterns of expression of the main core-
clock genes in zebrafish skeletal muscle (chapter 3);
 To test the hypothesis that the expression of myogenic regulatory factors,
components of the Insulin-like Growth Factor (IGF) system and other selected
nutritionally responsive genes in zebrafish skeletal muscle are under control of
the circadian clock mechanism (Chapter 3);
 To obtain replicate lineages of zebrafish artificially selected for divergent body
size and model the pattern of somatic growth from embryonic to adult stage
(Chapter 4);
 To examine the effects of short-term artificial selection for body size on early-life
traits of the zebrafish, with special attention to the maternal and embryonic
environment (Chapter 4);
 To investigate the effects of short-term artificial selection for body size on the
transcriptional response to fasting/refeeding in skeletal muscle of the zebrafish
(Chapter 4).
Chapter 2
36
2. Insulin-like growth factor (IGF) signaling and genome-wide
transcriptional regulation in fast muscle of zebrafish following a
single-satiating meal
2.1. Summary
Male zebrafish (Danio rerio, Hamilton) were fasted for 7d and fed to satiation over 3h to
investigate the transcriptional responses to a single meal. The intestinal content at
satiety (6.3% body mass) decreased by 50% at 3h and 95% at 9h following food
withdrawal. Phosphorylation of the insulin-like growth factor (IGF) signaling protein
Akt peaked within 3h of feeding and was highly correlated with gut fullness. Retained
paralogues of IGF hormones were regulated with feeding, with IGF-Ia showing a
pronounced peak in expression after 3h and IGF-IIb after 6h. Igf1 receptor (igf1r)
transcripts were markedly elevated with fasting and decreased to their lowest levels
45min after feeding. Igf1rb transcripts increased more quickly than igf1ra transcripts as
the gut emptied. Paralogues of the insulin-like growth factor binding proteins (IGFBPs)
were constitutively expressed, expect for igfbp1a and 1b transcripts, which were
significantly elevated with fasting. Genome-wide transcriptional responses were
analysed using the Agilent 44k Oligonucleotide microarray and selected genes validated
by qPCR. Fasting was associated with the upregulation of genes for the ubiquitin-
proteasome degradation pathway, antiproliferative and pro-apoptotic genes. Protein
chaperones (unc45b, hspd1, hspa5, hsp90a.1, hsp90a.2) and chaperone interacting
proteins (ahsa1 and stip1) were upregulated 3h after feeding along with genes for the
initiation of protein synthesis and mRNA processing. Transcripts for the enzyme
ornithine decarboxylase 1 showed the largest increase with feeding (11.5-fold) and
were positively correlated with gut fullness. This chapter demonstrates the fast nature
of the transcriptional responses to a meal and provides evidence for differential
regulation of retained paralogues of IGF signaling pathway genes.
Chapter 2
37
2.2. Introduction
Growth hormone (GH) is synthesized, stored and secreted by specialised cells in the
anterior pituitary and plays a central role in controlling feeding behaviour, cell growth,
osmoregulation and reproduction in teleosts (Kawauchi and Sower, 2006). GH acts
directly on muscle through sarcolemmal receptors and indirectly via the production of
insulin-like growth factors (IGFs) in the liver and peripheral tissues which are released
into the circulation (Wood et al., 2005a). IGFs are also produced by paracrine pathways
and are stimulated by amino acid influx into the muscle (Bower and Johnston, 2010b).
In mammals, the IGF system comprises 10 components: 2 hormones (igf1, igf2), two
receptors (igf1r, igf2r) and 6 binding proteins (IGFBPs 1-6) (Duan et al., 2010). IGFBPs
have distinct physiological roles in development and regulate IGF release to tissues in
association with specific proteases (Duan et al., 2010). Binding of igf1 to its receptor
activates several downstream signaling cascades including the PI3K/Akt/TOR and MAP
kinase pathways that are well conserved in fish and mammals (Engert et al., 1996; Duan
et al., 2010). Activation of PI3K/Akt/TOR stimulates a phosphorylation cascade that
increases translation and protein synthesis (Engert et al. 1996; Duan et al. 2010) and
inhibits protein degradation by the 26S proteasome system (Witt et al., 2005). In the
zebrafish (Danio rerio, Hamilton), no fewer than 16 components of the IGF system have
been described (Maures et al., 2002; Maures and Duan, 2002; Chen et al., 2004; Zhou et
al., 2008; Wang et al., 2009; Zou et al., 2009; Dai et al., 2010). The larger number of IGF
components in zebrafish compared to mammals reflects a whole genome duplication
(WGD) that occurred at the base of teleost evolution (Jaillon et al., 2004). It is thought
15% of the duplicated genes or paralogues from this basal WGD have been retained in
extant species (Jaillon et al., 2004). The distinct patterns of tissue expression and
transcriptional regulation of many IGF system paralogues observed in zebrafish
(Maures et al., 2002; Maures and Duan, 2002; Chen et al., 2004; Zhou et al., 2008; Wang
et al., 2009; Zou et al., 2009; Dai et al., 2010) is consistent with either
subfunctionalization or neofunctionalization of these genes.
Fasting-refeeding protocols are commonly used to investigate transcriptional
regulation in the IGF-system in teleosts following the transition from catabolic to
anabolic states (Chauvigne et al., 2003; Salem et al., 2005; Gabillard et al., 2006; Rescan
Chapter 2
38
et al., 2007; Bower et al., 2008). Feeding to satiation after a prolonged fast, results in
increased feeding intensity relative to continuously fed controls and a period of
compensatory or catch-up growth (Nicieza and Metcalfe, 1997). The transcriptional
responses observed in such experiments are dependent on the nutritional state of the
fish prior to fasting, particularly the extent of fat stores, the duration of the fast, body
size and temperature (Johnston et al., 2011). Fish show diurnal rhythms in feeding
behaviour and activity driven by central oscillators in the brain that are synchronised
by environmental cycles and co-ordinated with peripheral clock genes regulating
metabolism (Davie et al., 2009). In aquaculture, meal times entrain biological rhythms
and ready physiological systems in anticipation for processing the food (Sanchez et al.,
2009). As a consequence great care should be taken in designing fasting-feeding
experiments in order to define all experimental variables including the frequency and
timing of feeding in relation to diurnal cycles.
Following the digestion and assimilation of a meal, the organism changes from an
overall catabolic to an anabolic state, utilizing the nutrients from the meal to acquire
energy and synthesize new molecules, characterizing the postprandial period. Currently
there is a lack of studies describing the transcriptional changes during and following a
postprandial period in fish, with most studies focusing on the changes in metabolic rate
(Clark et al., 2010; Vanella et al., 2010) and plasma level of metabolites following
feeding (Eames et al., 2010; Eliason et al., 2010; Wood et al., 2010). In the present
chapter the transcriptional regulation in the fast myotomal muscle of male zebrafish in
response to a single satiating meal delivered at first light was investigated. Expression
of all 16 genes of the IGF-system was investigated by qPCR and supplemented with a
genome-wide survey of transcript abundance using the Agilent 44k oligonuclotide
microarray. Transcript abundance and the phosphorylation of the signaling protein Akt
were determined in relation to the presence of food in the gut as a reference point. The
single-meal experimental design potentially provides greater temporal resolution for
studying transcriptional responses compared to continuous refeeding where early and
late events quickly become confounded. The aim of the chapter was to test the
hypothesis that paralogues of IGF-system genes were differentially regulated with
feeding and to discover novel genes associated with the fasting and fed states in skeletal
muscle.
Chapter 2
39
2.3. Materials and Methods
2.3.1. Fish and water quality
The F5 generation of a wild-caught population of zebrafish (Danio rerio, Hamilton) from
Mymensingh, Bangladesh, was used in this study. All fish were adult males aged 9
months. Prior to the single meal experiment the fish were maintained in a single 50L
tank at 27.6±0.4ºC range and 12:12h dark:light photoperiod and fed bloodworms
(Ocean Nutrition™, Belgium) to satiety twice daily for one week. Nitrite (0 ppm), nitrate
(10-20 ppm), ammonia (0 ppm) and pH (7.6  0.2) were tested during acclimation and
experimental periods using Freshwater Master Test Kit (Aquarium Pharmaceuticals
Inc., Chalfont, PA, USA).
2.3.2. The single meal experiment
Two replicate experiments were carried out three months apart with identical
environmental conditions and food to account for any tank-to-tank variation in the
feeding response. The experimental protocol involved fasting fish for 7 days and then
feeding a single meal of bloodworms delivered over a 3h period, after which any
uneaten food was removed from the tank by siphoning. In the first replicate experiment
7 fish per time-point were sampled and in the second replicate experiment 6 fish per
time-point were sampled at the following times: -156, -24, 0h (prior to the meal), 0.75,
3, 6, 7.5, 9, 11, 24, and 36h (after the meal). The average body mass (g) and standard
length (from tip of snout to last vertebrae, in mm) of the fish was respectively 0.46 
0.02 and 29.8  0.4 (n = 77) (1st replicate experiment) and 0.53  0.016 and 32.6  0.3 (n
= 66) (2nd replicate experiment) (Mean  SE). Fish were humanely killed by an overdose
of ethyl 3-aminobenzoate methanesulphonate salt (MS-222) (Fluka, MO, USA). Fast
skeletal muscle was dissected from the dorsal epaxial myotomes, flash frozen in liquid
nitrogen and stored at -80ºC prior to total RNA and protein extraction. The digestive
tract was dissected and fixed in 4% (m/v) paraformaldehyde for later quantification of
intestine content to the nearest milligram. Fixation was necessary to prevent tissue loss
during dissection and to achieve an accurate quantification of intestine content. Since
the nature of the tissue and food were the same for all samples, any shrinking caused by
Chapter 2
40
fixation should be proportional to the amount of material and was not considered in the
interpretation of the results. All experiments and animal handling were approved by the
Animal Welfare and Ethics Committee, University of St Andrews and conformed to UK
Home Office guidelines.
2.3.3. Protein extraction
Total protein was extracted from fast skeletal muscle from 5 randomly selected fish per
time-point in each of the independent experiments. 30mg of tissue was homogenised in
Lysing Matrix D (Qbiogene, CA, USA) in a FastPrep® machine (Qbiogene) using 350µL of
25 mmol.L-1 MES (2-morpholino-ethanesulfonic acid monohydrate) pH 6.0 containing 1
mol.L-1 NaCl, 0.25% (m/v) CHAPS, DNA/RNA nuclease (Invitrogen) and protease
inhibitor cocktail (Invitrogen, CA, USA) .
2.3.4. Western blotting
The optimal protein amount to be used for electrophoresis separation and transfer was
empirically determined by applying from 10 to 60µg of protein of a reference sample in
duplicates and analysing the densitometry of the ponceau S staining (Figure 2.1A,B).
TotalLab software (Nonlinear Dynamics, Newcastle upon Tyne, UK) was used to analyse
the densitometry of bands from ponceau S staining and western-blots. Protein
saturation was observed when more than 30µg of protein was loaded in the gel. The
optimal amount was 20µg considering both ponceau S staining linearity (Figure 2.1B)
and total protein availability for the experiment. The membranes used for optimal
protein loading determination included a reference sample treated with calf intestinal
alkaline phosphatase (A2356, Sigma) to confirm that the antibody targeted the
phosphorylated moiety of the protein of interest (Figure 2.1C). Actin intensity was
better correlated with ponceau S staining when compared to GAPDH (Figure 2.1C) and
was used to normalize differences in protein loading. Dephosphorylation of P-AKT
significantly decreased its detection by P-AKT specific antibody (Figure 2.1C), while no
change in detection was observed for actin antibody in the dephosphorylated sample
(Figure 2.1C), confirming the specificity of the P-AKT antibody to the phosphorylated
moiety of AKT.
Chapter 2
41
Samples (20µL, containing 20µg of protein) were added to 6µL of a solution
containing 5µL of 5-times concentrated protein loading buffer and 1µL 20-times
concentrated reducing agent (Fermentas, Vilnius, Lithuania), heated for 5min at 95C,
loaded in NuPAGE® Novex 4-12% Bis-Tris gels (Invitrogen) and ran at 120V. A protein
ladder from 10 to 250 kDa (Fermentas) and a reference sample were loaded in all gels
to estimate the molecular weight of proteins of interest and serve as a normalization
sample, respectively. Proteins separated by electrophoresis were transferred to a PVDF
Immobilon-P Transfer Membrane (Millipore, MA, USA) at 25V for 105min. Successful
protein separation and transfer were confirmed by Ponceau S staining (Sigma). PVDF
membranes were blocked overnight at 10C using 5% (m/v) non-fat milk (AppliChem,
Darmstadt, Germany) prepared in PBS (Sigma) containing 0.1% (v/v) Tween 20
(Sigma). Blocked membranes were incubated overnight at 10C with the following
primary antibodies (IgGs): P-Akt (1:1,000 dilution (v/v), Cell Signaling #4060, MA,
USA), Akt (1:1,000 (v/v), Cell Signaling #2966), Actin (1:20,000 (v/v), Sigma A2066),
and GAPDH (1:30,000 (v/v), Sigma G9545). Probed membranes were incubated at 20C
for one hour with the secondary antibody against mouse or rabbit IgG conjugated to
horseradish peroxidase (both from Sigma and used at 1:60,000 (v/v)). Positive
reactions were recorded by exposing Hyperfilm ECL (Amersham, Buckinghamshire, UK)
to the membranes after incubation for one minute with ECL Western Blotting Detection
Reagents (Amersham) at room temperature. Experimental variations in the
electrophoresis and transfer were normalized using a reference sample common to all
membranes. The fold-change in phosphorylation of Akt in each time-point was
compared to the samples from -159h.
Chapter 2
42
Figure 2.1 – Optimization of protein loading for electrophoresis and western-blotting.
Determination of the optimal amount of protein for SDS-PAGE separation and antibody
detection linearity by ponceau S staining (A,B) and comparisons of ponceau S staining
with western-blotting intensity signals (C). A considerably lower signal was observed
for P-AKT after submitting the sample to de-phosphorylation() in comparison to the
untreated sample ().
A
B C
Chapter 2
43
2.3.5. Total RNA extraction from skeletal muscle and first strand cDNA synthesis
Total RNA was extracted by homogenisation in Lysing Matrix D (Qbiogene) using 1mL
of TRI reagent (Sigma) in a FastPrep® machine (Qbiogene). The RNA concentration,
260/280 and 260/230 ratios were measured using a NanoDrop® spectrophotometer
(Thermo Fisher Scientific, Loughborough, UK) and were between 1.5-2.0 and >2
respectively. RNA integrity was also checked by agarose gel electrophoresis. A
Quantitect Reverse Transcription Kit (Qiagen, Hilden, Germany) was used to produce
first strand cDNA from 0.6µg of total RNA following the manufacturer’s instructions.
2.3.6. Microarray experiments
Microarray experiments were carried out by an Agilent-certified microarray service
provider (Microarray Centre, University Health Network, Toronto, Canada) using the
Dual-Mode Gene Expression Analysis Platform (Agilent Technologies) in a 4x44K slide
format (Zebrafish (v2) Gene Expression Microarray). RNA from time-points 3h and 6h
were hybridized with the RNA from the 0h sample to identify differentially regulated
genes in 7d fasted fish following a single satiating meal. The 3h samples coincided with
50% of maximum gut fullness (Figure 2.2). Six phenotypic replicates from each group
were used. R version 2.9n.0 with arrayQualityMetrics_2.2.0 and limma_2.18.0 was used
for quality analysis of microarray data. Microarray results were also analysed using
GeneSpring® v7. The intensities of spots among arrays was normalised using the
AQuantile method and intensities were log transformed prior to performing a T-test
using the Benjamini & Hochberg method for multiple testing correction (Benjamini and
Hochberg, 1995). A list of differentially regulated genes was built by screening against
the following criteria: > 2-fold change in expression, B-value statistic > 0 and an
adjusted P-value < 0.05. Blast2GO software was used to analyse the gene ontology (GO)
terms of the differentially expressed genes. GO enrichment analysis of the annotated
genes was performed with the GOSSIP tool using Blast2GO software. The European
Bioinformatics Institute Miame ArrayExpress accession number for the microarray
experiment is E-MEXP-2887.
Chapter 2
44
2.3.7. Primer design and cloning
Transcript sequences from the Ensembl database (release 55) (www.ensembl.org) were
used to design primer pairs for each gene in Table 2.1. Primers were designed using
NetPrimer (http://www.premierbiosoft.com/netprimer/index.html, Premier BioSoft,
CA, USA). Where possible the primer pairs were designed so that at least one primer
spanned an exon-exon boundary (otherwise primers pairs were in different exons),
with a Tm close to 60ºC. First strand cDNA from muscle was used as a template to
synthesise PCR products for cloning. The PCR reaction mixture contained 1.5 mmol.L-1
MgCl2, 1x NH4 buffer, 0.25µL BioTaq™ DNA polymerase (Bioline, London, UK), 0.2
mmol.L-1 dNTP (Promega, WI, USA), 1µL cDNA and 0.5 µmol.L-1 of each primer
(Invitrogen) and the following thermal cycling conditions were employed: denaturation
for 5min at 95ºC followed by 36 cycles of 30s at 95ºC, 30s at 60ºC, and 30s at 72ºC, final
elongation of 5min at 72ºC. After agarose gel electrophoresis the products of expected
size were extracted and purified using a QIAquick Gel Extraction Kit (Qiagen) and
cloned using a StrataClone™ PCR Cloning Kit (Stratagene, CA, USA) according to the
manufacturer instructions. Positive clones were picked after 16h of growth at 37ºC in
LB-agar plates containing ampicillin (0.1mg/mL) and transferred to 96 well plates
containing LB-broth and ampicillin (0.1mg/mL). After 16h of growth at 37ºC colony-
PCR was performed to confirm the sequence of the insert using Big Dye terminator
sequencing (Applied Biosystems, CA, USA) at the University of Oxford (T3 and T7
primers were used to confirm the sequence in both directions). The clones bearing
plasmids with the expected insert were grown in 5mL LB-broth and plasmids were
purified using a QIAprep Spin Miniprep Kit (Qiagen). The plasmid concentration,
260/280 and 260/230 ratios were measured using a NanoDrop® instrument and were
higher than 1.8 and 2.0, respectively.
Chapter 2
45
Table 2.1 – Sequence and properties of primers used in the experiments of chapter 2.
Ensembl gene symbols, forward (f) and reverse (r) primer sequences, product size, product
melting temperature (Tm), amplification efficiency (E), linearity of standard curve and
Ensembl gene ID are shown.
Ensembl
Gene f/r Primer 5'-3' sequence
Product
Size (bp)
Tm
(ºC)
E
(%) R2 Ensembl Gene ID
Reference genes selected from the microarray experiment
tomm20b f: GCTGCTGGCTCAGGGAGACTATG 170 86.2 103.8 0.999 ENSDARG00000044636
r: CGCTGACGATACGCTGGCTG
rpl7a f: CCCATTGAGCTGGTGGTGTTCT 216 84.8 96.2 0.999 ENSDARG00000019230
r: ACGGATCTCCTCATATCTGTCATTGTA
lman2 f: GGATCGCTCCTTTCCATACATTTC 176 81.7 104.7 0.999 ENSDARG00000061854
r: CCACCATTATCGTGAGTCTGCCT
si:ch211-
273k1.4 1 f: GCTGTTTTTGTGAAGGAGTGTGGTC 193 82.4 98.5 0.998 ENSDARG00000033259
r: TTTCCCAAACAAGCGTCATCTCTG
Genes up-regulated during fasting selected from the microarray experiment
odc1 f: CGACTGTGCCAGCAAAACGG 201 85.7 103.5 1.000 ENSDARG00000007377
r: CGGAGAACCAGCTTGGCATTT
hsp90a.1 f: TGGCGAACTCAGCGTTTGTG 259 83.3 100.6 0.997 ENSDARG00000010478
r: ACGGTGACCTTCTCAATCTTTTTG
fkbp5 f: GACACAGTATTTCAAGGCAGGACG 215 84.3 99.2 0.999 ENSDARG00000028396
r: CCAGCTCCATTACCTTGTTGCAG
sae1 f: GCAAGTGCTTCTGAAGTTTCGC 232 83.6 106.3 0.999 ENSDARG00000010487
r: CTGAGACAGCGCCTTGACAATC
hsp90a.2 f: CTGGAGAAGAAAGTGGAGAAGGTCA 367 85.4 102.0 0.998 ENSDARG00000024746
r: CCTCATCAATGCCTAAGCCCAG
foxo1a f: GCGGGCTGGAAGAACTCAATCA 219 85.1 101.7 0.999 ENSDARG00000063540
r: CACCCTGAAGAGCCAGCTTTTTCT
Genes down-regulated during fasting selected from the microarray experiment
klf11b f: GCCCCAGTCGCCAGTATCTTC 240 86.8 97.8 0.999 ENSDARG00000013794
r: GGTTTCTCTCCTGTATGGGTTCTGA
nr1d1 f: GAAGGCTGGAACATTTGAGGTC 228 83.3 101.2 0.999 ENSDARG00000033160
r: GCAGACACCAGGACGACCG
cited2 f: AGCGGAGAGGGGAATGGTAGAC 264 84.8 103.4 0.998 ENSDARG00000030905
r: CGGGCAGGCAAGTTTCCATT
bbc3 f: GGGACAATTCAGGAACAGAACAGGA 222 86.8 95.2 0.999 ENSDARG00000069282
r: GCGGGACGGCATTCCTCTG
znf653 f: GCCATCAGCAGTTTCCAGAATCAT 255 81.9 100.7 0.999 ENSDARG00000093469
r: CTGATACCCACATATCTCACATTGTAATG
hsf2 f: CCTTCTGGGCAAAGTTGAGCTG 194 80.3 100.2 0.997 ENSDARG00000053097
r: GCTGCTTGTCTGTGTTTTCTGAATC
Reference genes selected from the literature
ef1a f: GAGGAGTGATCTCTCAATCTTGAAAC 191 83.8 101.0 0.999 ENSDARG00000020850
r: CCCTTGCCCATCTCAGCG
Chapter 2
46
Table 2.1 (continuation)
Ensembl
Gene f/r Primer 5'-3' sequence
Product
Size (bp)
Tm
(ºC)
E
(%) R2 Ensembl Gene ID
Reference genes selected from the literature (continuation)
rpl13a f: AAAATTGTGGTGGTGAGGTGTG 183 81.5 100.3 0.998 ENSDARG00000044093
r: GGTTTTGTGTGGAAGCATACCTCT
Bactin2 f: CCCAAACCCAAGTTCAGCC 112 83.0 100.5 0.999 ENSDARG00000037870
r: GAAGACAGCACGGGGAGCA
b2m f: GGGGAAAGTCTCCACTCCGAAA 166 81.7 102.7 0.997 ENSDARG00000053136
r: CAGGTCGGTCTGCTTGGTGTCC
usp5 f: GACCCGGAAAACACAGAAGGAG 101 79.5 102.9 0.999 ENSDARG00000014517
r: CAAACCCTCCCTCAATACCAATG
tbp f: CCTGCGAATTATCGTTTACGTCTTTT 151 81.7 98.4 0.999 ENSDARG00000014994
r: CCCTGTGGAGATGCCAGACCT
cyp1a f: GACCTATTCGGAGCCGGTTTCG 120 82.8 103.7 1.000 ENSDARG00000026039
r: CCCGATCTTTTCATCCAATTCTCTTTG
IGF pathway components
igf1a 2 f: GCATTGGTGTGATGTCTTTAAGTGTA 188 87.1 95.9 1.000 ENSDARG00000094132
r: GTTTGCTGAAATAAAAGCCCCT
igf1b 2 f: GGCTTTTACATAGGCAAACCTGGAG 166 84.8 NA NA ENSDARG00000058058
r: GCAGCACAGATGCAGGGACAT
igf1ra f: GCCCGTGGAGAAGTCTGTGG 154 81.3 98.0 0.999 ENSDARG00000027423
r: GTGTGCGAAAGTGTTCCTGGTT
igf1rb f: CACAACTACTGCTCCAAAGAACTGA 238 83.8 94.5 0.999 ENSDARG00000034434
r: GCCTGTCTGGAGGTCTGGGA
igf2a f: GAAACACGAACAACGATGCG 346 82.8 91.8 1.000 ENSDARG00000018643
r: AGTACTTCACATTTATGGTGTCCTTG
igf2b f: ACAGACAGTTTCGTAAATAAGGTCATAA 236 85.5 97.0 0.999 ENSDARG00000033307
r: CAACACTCCTCCACAATCCCAC
ig2ir f: ACCCCTGTCCTCAAGTAACAGAT 176 80.1 99.4 0.998 ENSDARG00000006094
r: TTGCACACCGTCAGTACAAAAG
igfbp1a f: ACTGGTGGAACAGGGTCCCT 158 82.1 98.0 1.000 ENSDARG00000014947
r: CTAGAGATGATTCGCACTGTTTGATT
igfbp1b f: GCTCATCCAGCAGGGTCCG 151 83.5 101.2 0.999 ENSDARG00000038666
r: CGACACACACTGTTTGGCCTTG
igfbp2a f: GGGAAGTCAGCGGTGAGGTG 196 83.0 100.8 0.999 ENSDARG00000052470
r: TGCTGGCACTGGCTCTGTTTA
igfbp2b f: GTCAGCAGCACACAGTGGAGAAGTA 188 82.5 99.7 0997 ENSDARG00000031422
r: GCTCCTGTTGACACTGGCTCTG
igfbp3 f: AATGAATATGGCCCATGTCGT 146 80.9 101.2 0.999 ENSDARG00000014859
r: CCTTTGGATGGACTGCACTGT
igfbp5a f: ACAACAAGCTAAGCTCGGTCCA 209 81.0 100.5 0.998 ENSDARG00000039264
r: TAGAGGGCTTACACTGTTTGCG
igfbp5b f: GCACCCACCCATTGATCGT 241 82.8 95.3 0.999 ENSDARG00000025348
r: CCTTCTGCACGGACCAAATTC
Chapter 2
47
Table 2.1 (continuation)
Ensembl
Gene f/r Primer 5'-3' sequence
Product
Size (bp)
Tm
(ºC)
E
(%) R2 Ensembl Gene ID
IGF pathway components (continuation)
igfbp6a f: CCCTCCGCCTACAGACTATGA 180 83.1 100.7 0.997 ENSDARG00000070941
r: GACGAGCGACACTGCTTCCT
igfbp6b f: CGTTGGGGGAGCCCTGCG 201 82.3 96.9 0.998 ENSDARG00000090833
r: GAGCCTTTTCCATTTCACCACTGT
Muscle-specific ubiquitin ligases
fbxo32 f: GAGCACCAAAGAGCGTCAT 154 82.8 105.6 0.999 ENSDARG00000040277
r: CACTCCACTCAGAGAAGGCAG
trim63 f: CCTGGCTTTGAGAGTATGGACC 225 80.1 102.5 0.999 ENSDARG00000028027
r: GCCCCTTGCCTCACAGTTAT
Muscle structural proteins
tnni2a.4 f: GCAGACAAGGAGATTGAGGATCTG 199 83.8 101.7 0.998 ENSDARG00000029069
r: GTTCTACAGACTCCTCCTTGACCTCC
mylz2 f: GGAGAGAAGTTGAAGGGTGCTGAC 154 83.8 103.9 1.000 ENSDARG00000053254
r: GATTCTTCATCTCCTCTGCGGTG
1 Orthologue of the gene dis3l2 in various species.
2 According to Zou et al. (2009) the genes igf1 and igf3 annotated in the zebrafish ensembl database V58
are two paralogues of the igf1 gene and should be named igf1a and igf1b, respectively.
2.3.8. Quantitative PCR (qPCR)
All protocols and reporting of qPCR assays adhered to “Minimum Information for
Publication of Quantitative Real-Time PCR experiments” guidelines (Bustin et al., 2009).
The qPCR reaction mixture contained 7.5µL 2x Brilliant II SYBR® QPCR Low ROX Master
Mix (Stratagene), 6µL 40-fold diluted cDNA, 0.25 µmol.L-1 each primer and nuclease-free
water (Qiagen) to a final volume of 15µL in 96 well plates (Stratagene). The reactions
were performed in a Stratagene MX3005P machine (initial activation at 95ºC for 10 min,
followed by 40 cycles of 30s at 95ºC, 30s at 60ºC and 30s at 72ºC) and the fluorescence
results collected after the elongation step (72ºC) were recorded by the MxPro software
v4.10 (Stratagene). Negative controls were included and ran in duplicate, and contained
either all components of the reverse transcription mixture, except reverse transcriptase
(no reverse transcriptase control) or water instead of a cDNA template (no template
control). After the qPCR a dissociation curve (from 55 to 95ºC) was performed to verify
the presence of a single peak. The specificity of each qPCR assay was also validated by
sequencing transformants for each qPCR product. Absolute copy number of each gene
Chapter 2
48
was calculated based on a standard curve of at least 6 orders of magnitude prepared
with the plasmids which was also used to analyse the efficiency of each primer pair
(Table 2.1). The threshold of fluorescence (for dRn values) used for determination of
the quantification cycle (Cq) was set to 1.0 for all plates to allow for comparison
between plates. Comparison between plates was possible after normalization to six
samples loaded on all plates.
Six reference genes selected from the literature (ef1a, rpl13a, bactin2, b2m, usp5, tbp and
cyp1a) and four selected from the microarray experiment (tomm20b, rpl7a, lman2,
dis3l2) were analysed using Genorm v3.5 (Vandesompele et al., 2002) with M set to
<1.5. The two genes with the most stable level of expression across the experimental
conditions were ef1a and lman2 (M=0.4). The expression of genes of interest was
normalized to the geometric average of the two most stable genes and gene expression
was reported as arbitrary units (a.u.).
2.3.9. Data analysis and statistics
All data was analysed for normal distribution and equality of variance. Normally
distributed data was analysed using ANOVA followed by Tukey post-hoc tests using
PASW Statistics 18 (SPSS Inc., Chicago, Illinois, USA). Kruskal-Wallis non-parametric
tests followed by Conover post-hoc tests were used for the data that was not normally
distributed using BrightStat software (Stricker, 2008). There was no statistically
significant difference in the standard length, body mass, intestine content or normalised
gene expression between the two replicate experiments (P>0.05). Therefore, the results
from both experiments were combined to facilitate their interpretation, resulting in
n=13 per time-point (i.e., 7 fish from the first replicate experiment plus 6 from the
second replicate). In order to combine the data from mRNA levels from both
experiments, the results of gene expression from the second replicate experiment were
normalised to the average value of 7 samples from the first replicate experiment which
had been included from the cDNA synthesis step onwards. Correlation of gene
expression from both qPCR and microarray experiments was analysed by Spearman’s
correlation test using PASW Statistics 18 (SPSS Inc.). Clustering of gene expression was
performed using PermutMatrix
(http://www.lirmm.fr/~caraux/PermutMatrix/EN/index.html).
Chapter 2
49
2.4. Results
2.4.1. Feeding response during the single meal experiment
Fish were continuously fed to satiation and then fasted for 7d prior to feeding a single
meal over 3h. Three samples were taken during the fast: -156, -24 and 0h,
corresponding to 9h, 144h and 168h after the last food. Only traces of food remained in
the gut after 9h of fasting (-156h time-point), corresponding to 0.1% of body mass, with
only bile observed with more prolonged fasting (-24 and 0h time-points). The maximum
average gut fullness, equivalent to 6.3% of body mass, was observed at 0.75h (45min)
after food became available, indicating satiety had been reached. Intestinal contents had
decreased by 50% three hours after food was withdrawn and 95% of the food ingested
had been assimilated or excreted by 9h (Figure 2.2). No significant statistical difference
was observed for either standard length (SL), body mass or condition factor (Table 2.2).
Table 2.2 – Biometry (mean  standard error, n=7) of fish from the single-meal
experiment.
Time (h) SL* Body Mass (mg) Condition Factor (K)
-159 30.4a ± 2.6 530a ± 110 1.01a ± 0.11
-24 30.6a ± 2.7 460a ± 120 0.87a ± 0.09
0 31.6a ± 3.6 460a ± 140 0.77a ± 0.07
0.75 33.7a ± 2.6 580a ± 140 0.84a ± 0.04
3 30.4a ± 2.4 460a ± 120 0.85a ± 0.10
6 32.1a ± 4.0 550a ± 180 0.88a ± 0.09
8 29.2a ± 2.8 420a ± 120 0.88a ± 0.06
9 31.2a ± 3.5 490a ± 140 0.86a ± 0.07
12 30.8a ± 3.3 480a ± 140 0.86a ± 0.11
24 32.1a ± 3.9 520a ± 170 0.83a ± 0.08
36 31.4a ± 2.0 470a ± 80 0.81a ± 0.07
* SL had a strong positive linear correlation with fork length (FL=1.14×SL+0.9, r2=0.98, p<0.001) and total
length (TL=1.14×SL+2.71, r2=0.98, p<0.001); a strong exponential correlation between SL and body mass
(BM) was also recorded in this experiment (BM=0.097×SL2.48, r2=0.84, p<0.001). Values followed by a
different letter means statistically different means (analysed by ANOVA with Tukey post-hoc tests, p=0.05
for both tests).
Chapter 2
50
Figure 2.2 – The feeding response of male zebrafish during the course of the single
meal experiment. The upper panel shows the micro-dissection of a representative
intestine for each sample point. Gut fullness reached a maximum after 45min, indicating
satiety. The relative intestinal content (% maximum fullness, lower panel) is shown
throughout the experiment together with the dark: light cycle. Values represent Mean ±
s.e.m., n = 13 fish per sample. Different letters signify statistically different means at
0.05 significance level.
Chapter 2
2.4.2. Phosphorylation of the Insulin-like growth factor (IGF) signaling protein Akt
In fast myotomal muscle the protein Akt showed a marked increase in phosphorylation
to peak levels within 3h of the start of feeding and became steadily dephosphorylated as
the intestine emptied (Figure 2.3). The level of the protein load control actin and the
dephosphorylated AKT did not change significantly over the course of the experiment
(Figure 2.3).
Figure 2.3 – phorylation of the Insulin-like growth factor
the fast myotomal muscle of male zebrafish during the cou
experiment (solid squares). Insert shows a representative Wes
antibody. The grey line represents the average gut fullness il
Values represent Mean ± s.e.m., n = 5 fish per sample. D
statistically different means at 0.05 significance level.
-160 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35
0
20
40
60
80
100
120
1
2
3
4
5
6
7
8
b
b
b
a
a
a a
a
a
G
u
t
fu
lln
e
ss
(%
)
a
F
o
ld
-c
h
a
n
g
e
in
p
h
o
sp
h
o
ry
la
ti
o
n
o
f
A
k
t
Time (h)
LightLight DarkLight Dark
P-AKT
Total AKT
Actin
-1
5
9
h
-2
4
h
3
h
6
h 7
.5
h
1
2
h
2
4
h
3
6
h
0
h 0
.7
5
h40signaling protein Akt inPhos51
rse of the single meal
tern Blot with the P-Akt
lustrated in Figure 2.2.
ifferent letters signify
Chapter 2
52
2.4.3. Transcriptional regulation of the Insulin-like Growth Factor (IGF) system
The expression of all the paralogues of IGF-system genes was determined by qPCR
including igf1, igf2, IGF-receptors and IGF binding proteins. In many cases retained
paralogues of IGF system components showed distinct patterns of transcriptional
regulation over the course of the experiment. Changes in transcript levels could be
directly attributed to feeding since marked responses were largely present in only the
first of two light: dark cycles following the meal.
2.4.4. IGF hormones gene expression
Igf1a expression was correlated with, but lagged behind gut fullness showing a distinct
peak 3h after the start of feeding (P<0.05) (Figure 2.4A). The igf1b paralogue was not
detected in fast myotomal muscle after 35 cycles of PCR (Figure 2.4D). Igf2b expression
was also increased following feeding, showing peak expression 3h later than igf1a
(Figure 2.4B). The igf2a paralogue was 3.7 times more abundant than the igf2b
transcripts at 0h and was constitutively expressed during the experiment with no
discernible pattern in relation to feeding (Figure 2.4C-D).
2.4.5. IGF receptors (IGFRs) gene expression
Igf1ra receptor expression increased more than 2.7-fold between 9h and 168h fasting,
decreased to its lowest levels 45min after feeding and then showed variable though still
depressed expression over the next 36h (Figure 2.5A). Igf1rb paralogue expression was
inversely related to gut fullness showing a more than 3.3-fold decrease within 45min of
feeding, returning to levels not significantly different to fasting after only 12h (Figure
2.5B). Igf1rb transcripts were more abundant than igf1ra transcripts over the single
meal experiment, with 7.4 more copies at the start of feeding (Figure 2.5E). Transcripts
of the single retained paralogue of the igf2 receptor gene showed no consistent changes
in expression over the fasting-feeding-fasting cycle (Figure 2.5C).
2.4.6. IGF binding proteins (IGFBPs) gene expression
The two retained paralogues of igfbp1 (1a and 1b) showed similar changes in
expression over the experiment with high levels during prolonged fasting (144-168h), a
Chapter 2
53
marked reduction in transcript abundance within 45min of the start of feeding and
variable, but generally low levels over the following 36h (Figure 2.5D,E). Expression of
igfbp1a was considerably higher than igfbp1b over the experiment, with a 12.4 times
greater copy number at 0h (Figure 2.5F). The remaining IGF binding proteins (igfbp2a,
b; igfbp3; igfbp5a, b; and IGFBP6a, b) showed no consistent change in expression in
response to a single satiating meal (Figure 2.5G-L).
Figure 2.4 – Transcriptional responses of insulin-like growth factor (IGF) system genes
in the fast myotomal muscle of male zebrafish during the course of the single meal
experiment determined by qPCR (solid squares): Hormone transcripts (A) igf1a, (B)
igf2b, and (C) igf2a and (D) copy number of igf1a, igf1b, igf2a and igf2b. The grey line
represents the average gut fullness illustrated in Figure 2.2. Values represent mean ±
s.e.m., n = 13 fish per sample. Different letters signify statistically different means at
0.05 significance level.
Transcript
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Chapter 2
54
Figure 2.5 – Transcriptional responses of insulin-like growth factor receptor and
binding protein genes in the fast myotomal muscle of male zebrafish during the course
of the single meal experiment determined by qPCR. IGF receptors (A, B, C), igfbp1a/b (D,
E), copy number of igf1ra, igf1rb, igfbp1a and igfbp1b (F) and transcription level of
IGFBPs-2 – 6 (G-M). The grey line represents the average gut fullness illustrated in
Figure 2.2. Values represent mean ± s.em., n = 13 fish per sample. Different letters
signify statistically different means at 0.05 significance level (see text for details).
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Chapter 2
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Figure 2.5 (continuation)
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Chapter 2
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Figure 2.5 (continuation)
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Chapter 2
57
2.4.7. Genome-wide changes in gene expression with feeding
In order to identify some nutritionally-responsive candidate genes for further
investigation whole genome microarray analysis was performed. Total RNA from
maximally fasted fish (0h) was hybridised with RNA from fish sampled 3h and 6h after
the initiation of feeding. Genes were considered differentially regulated if they showed a
higher than 2.0-fold change in expression, a B value higher than zero, and were
significant at the P-value < 0.05 level following correction for multiple comparisons. The
hybridisations of fasting and 6h fed samples produced a relatively short gene list and no
genes that were not represented in the hybridisation of fasting and 3h fed samples and
are not considered further. Fast skeletal muscle from zebrafish fasted for 7d had 56 up-
regulated genes (Table 2.3) and 91 down-regulated genes (Table 2.4) compared to fish
fed to satiation over 3h. 45 of the up-regulated genes in fasting and 79 of the up-
regulated genes with feeding had associated gene ontology (GO) terms. For the genes
up-regulated with fasting GO term analysis revealed a significant enrichment of terms
associated with catabolic processes, ubiquitin ligase activity and positive regulation of
endothelial cell differentiation, including the genes btg1 and btg2 which have
antiproliferative properties (Winkler, 2010) (full listing in Table 2.5). Analysis of the
genes up-regulated with feeding showed enrichment for GO terms such as unfolded
protein binding, protein folding, endoplasmic reticulum lumen, protein maturation,
chaperone binding, sarcomerogenesis, myosin filament assembly, collagen biosynthesis
and regulation of the JAK-STAT cascade (full listing in Table 2.4). The gene showing the
largest fold change of 32.2 with fasting (Table 2.3) coded for a novel protein with ~23%
identity to the mammalian orthologue of harbinger transposase derived 1 (harbi1)
which is thought to have nuclease activity (Kapitonov and Jurka, 2004). The list of genes
up-regulated with feeding included many chaperone genes (unc45b, ptges3, serpinh1),
heat shock protein (hsp90a.1, hsp90a.2, hspd1, hspa5) and heat shock protein-associated
genes (ahsa1, calrl and stip1) (Table 2.4). Feeding was also associated with enrichment
of the interleukin-20 receptor binding GO term (Table 2.5) and increased il34
expression (Table 2.4).
Chapter 2
58
Table 2.3 – Filtered gene list from the microarray experiment showing transcripts up-
regulated with fasting in the zebrafish single meal experiment.
Gene symbol Gene description Fold change
(Mean ± SE,
n=6)
Adjusted
P-value
1 Novel gene Novel gene 32.2 ± 10.4 0.048
2 zgc:86757 murf1 (muscle-specific RING finger protein 1) 25.4 ± 7.6 0.022
3 fbxo32 (MAFbx) F-box protein 32 17.9 ± 5.7 0.040
4 pdk2 Pyruvate dehydrogenase kinase 2 16.9 ± 3.8 0.022
5 zp2 Zona pellucida glycoprotein 2.3 13.8 ± 5.6 0.049
6 h1m Linker histone H1M 12.8 ± 4.2 0.049
7 si:ch211-284a13.1 Novel protein (Si:ch211-284a13.1) 12.5 ± 2.6 0.022
8 klf11b Kruppel-like factor 11b 11.0 ± 0.7 0.020
9 zgc:162945 Hypothetical protein LOC560936 9.8 ± 2.9 0.032
10 bbc3 BCL2 binding component 3 9.4 ± 3.1 0.038
11 si:ch211-63o20.5 Hypothetical protein LOC566703 9.3 ± 1.6 0.022
12 ypel3 Protein yippee-like 3 8.7 ± 2.8 0.037
13 cited2 Cbp/p300-interacting transactivator, with Glu/Asp-rich carboxy-
terminal domain, 2 8.6 ± 1.8 0.022
14 nr1d1 Nuclear receptor subfamily 1, group D, member 1 8.5 ± 1.7 0.023
15 ccng2 Cyclin G2 7.6 ± 1.2 0.022
16 gbp Glycogen synthase kinase binding protein 7.6 ± 1.6 0.049
17 gpr137ba G protein-coupled receptor 137ba 7.2 ± 1.8 0.048
18 si:dkey-42i9.4 B-cell translocation gene 1-like 6.9 ± 1.1 0.025
19 zgc:100920 Hypothetical protein LOC445241 6.6 ± 2.2 0.049
20 LOC566363 Mucin 3-like 6.3 ± 2.1 0.049
21 zgc:55582 Myomegalin 5.9 ± 1.0 0.028
22 slc16a9a Solute carrier family 16 (monocarboxylic acid transporters),
member 9a 5.6 ± 1.2 0.032
23 rab40b RAB40B, member RAS oncogene family 5.4 ± 0.6 0.025
24 TCEANC Transcription elongation factor A (SII) N-terminal and central
domain containing 5.4 ± 1.0 0.040
25 zgc:77714 Carboxy-terminal domain RNA polymerase II polypeptide A small
phosphatase 2 5.3 ± 0.9 0.040
26 stk11ip Serine/threonine kinase 11 interacting protein 5.3 ± 0.6 0.025
27 btg2 B-cell translocation gene 2 5.2 ± 1.2 0.049
28 LOC794083 Pyruvate dehydrogenase kinase 2-like 5.2 ± 1.1 0.040
29 vgll2b Vestigial like 2b 5.2 ± 1.4 0.047
Chapter 2
59
Table 2.3 (continuation)
Gene symbol Gene description Fold change
(Mean ± SE,
n=6)
Adjusted
P-value
30 hsf2 Heat shock factor 2 5.1 ± 0.6 0.023
31 znf653 Zinc finger protein 653 5.1 ± 0.8 0.025
32 heca Headcase homolog 4.8 ± 0.8 0.036
33 per1b Period homolog 1b 4.5 ± 0.8 0.048
34 zgc:92851 Jun dimerization protein 2 4.4 ± 1.1 0.049
35 pcmtd2 Protein-L-isoaspartate (D-aspartate) O-methyltransferase domain
containing 2
4.3 ± 0.6 0.036
36 LOC559993 Similar to THAP domain containing, apoptosis associated protein 1 4.3 ± 0.7 0.042
37 brms1l Breast cancer metastasis-suppressor 1-like protein 4.0 ± 0.7 0.048
38 usf1 Upstream transcription factor 1 3.9 ± 0.7 0.042
39 ubr1 Ubiquitin protein ligase E3 component n-recognin 1 3.8 ± 0.5 0.040
40 vsg1 Vessel-specific 1 3.7 ± 0.7 0.048
41 si:dkey-86e18.1 Hypothetical protein LOC557342 3.6 ± 0.4 0.040
42 slc25a1 Solute carrier family 25 (mitochondrial carrier; citrate transporter),
member 1
3.6 ± 0.6 0.048
43 si:ch73-138e16.8 Hypothetical protein LOC100006084 3.4 ± 0.5 0.049
44 n4bp2 NEDD4 binding protein 2 3.4 ± 0.4 0.040
45 fbxo25 F-box only protein 25 3.4 ± 0.4 0.042
46 ccdc149 Coiled-coil domain containing 149 3.2 ± 0.4 0.050
47 npl N-acetylneuraminate lyase (NALase)(EC 4.1.3.3)(N-
acetylneuraminic acid aldolase)(N-acetylneuraminate pyruvate-
lyase)(Sialic acid lyase)(Sialate lyase)(Sialate-pyruvate lyase)(Sialic
acid aldolase)
3.2 ± 0.4 0.050
48 zgc:110708 Hypothetical protein LOC553793 3.1 ± 0.4 0.048
49 mtus1a Mitochondrial tumor suppressor 1 homolog A 3.1 ± 0.4 0.050
50 zgc:171727 Hypothetical protein LOC799470 3.1 ± 0.2 0.040
51 id2b Inhibitor of DNA binding 2, dominant negative helix-loop-helix
protein, b
3.0 ± 0.3 0.048
52 nbr1 Neighbor of BRCA1 gene 1 3.0 ± 0.4 0.048
53 gmcl1 Germ cell-less homolog 1 (Drosophila) 3.0 ± 0.3 0.049
54 LOC799552 Hypothetical protein 2.9 ± 0.2 0.045
55 zgc:163003 Inactive Ufm1-specific protease 1 2.9 ± 0.2 0.047
56 spns1 Protein spinster homolog 1 (Spinster-like protein) 2.8 ± 0.2 0.047
Chapter 2
60
Table 2.4 – Filtered gene list from the microarray experiment showing transcripts up-
regulated with feeding in the zebrafish single meal experiment.
Gene symbol Gene description Fold change
(Mean ± SE,
n=6)
Adjusted
P-value
1 odc1 Ornithine decarboxylase 1 11.5 ± 2.8 0.022
2 pptc7 Protein phosphatase PTC7 homolog 10.5 ± 1.8 0.022
3 ctsll Cathepsin L, like 9.9 ± 3.2 0.027
4 ddx5 DEAD (Asp-Glu-Ala-Asp) box polypeptide 5 9.8 ± 3.4 0.038
5 pdip5 Protein disulfide isomerase-related protein 9.5 ± 1.9 0.025
6 si:ch211-76m11.7 si:ch211-76m11.7 9.0 ± 2.5 0.038
7 mylk4 Myosin light chain kinase family, member 4 8.9 ± 3.1 0.040
8 mfsd2b Major facilitator superfamily domain-containing protein 2-B 8.0 ± 1.1 0.022
9 zgc:110154 Eukaryotic translation initiation factor 4E-like 7.9 ± 2.0 0.038
10 fkbp5 FK506 binding protein 5 7.7 ± 2.2 0.040
11 rcn3 Reticulocalbin 3, EF-hand calcium binding domain 7.5 ± 2.3 0.048
12 dyrk2 Dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 2 7.5 ± 2.1 0.028
13 calrl Calreticulin like 7.2 ± 2.2 0.049
14 ahsa1 AHA1, activator of heat shock protein ATPase homolog 1 7.0 ± 1.2 0.025
15 eif4a1a Eukaryotic translation initiation factor 4A, isoform 1A 6.8 ± 1.3 0.025
16 klf13l Kruppel-like factor 13 like 6.8 ± 1.9 0.049
17 LOC792864 Similar to Dual specificity protein phosphatase 13 (Testis- and
skeletal-muscle-specific DSP) (Dual specificity phosphatase SKRP4) 6.6 ± 1.5 0.049
18 slc25a25 Calcium-binding mitochondrial carrier protein SCaMC-2-A (Small
calcium-binding mitochondrial carrier protein 2-A)(Solute carrier
family 25 member 25-A) 6.5 ± 1.5 0.049
19 LOC100332265 Adaptor-related protein complex 1 associated regulatory protein-
like 6.3 ± 1.0 0.025
20 mid1ip1 MID1 interacting protein 1 5.9 ± 0.7 0.025
21 zgc:73230 Hypothetical protein LOC406311 5.8 ± 0.9 0.032
22 hsp90a.1 Heat shock protein HSP 90-alpha 1 5.7 ± 0.6 0.022
23 ctrl Chymotrypsin-like 5.7 ± 1.3 0.045
24 hsp90a.2 Heat shock protein 90-alpha 2 5.6 ± 0.7 0.025
25 foxo1a Forkhead box O1 a 5.4 ± 0.7 0.025
26 zgc:110801 Protein phosphatase 5, catalytic subunit 5.3 ± 1.6 0.049
27 zgc:158222 Adenosylhomocysteinase 5.3 ± 1.0 0.040
28 syncripl Synaptotagmin binding, cytoplasmic RNA interacting protein, like 5.1 ± 1.0 0.045
29 dnaja4 DnaJ (Hsp40) homolog, subfamily A, member 4 5.1 ± 0.6 0.025
Chapter 2
61
Table 2.4 (continuation)
Gene symbol Gene description Fold change
(Mean ± SE,
n=6)
Adjusted
P-value
30 fam69b Family with sequence similarity 69, member B 5.0 ± 0.9 0.048
31 s1pr2 Sphingosine 1-phosphate receptor 2 (S1P receptor
2)(S1P2)(Sphingosine 1-phosphate receptor Edg-5)(S1P receptor
Edg-5) 5.0 ± 1.1 0.048
32 pias4 Protein inhibitor of activated STAT, 4 5.0 ± 0.9 0.042
33 lmnb1 Lamin B1 5.0 ± 1.2 0.049
34 ehmt1b Euchromatic histone-lysine N-methyltransferase 1b Fragment 4.9 ± 0.3 0.022
35 smyd1b SET and MYND domain containing 1b 4.8 ± 0.8 0.032
36 LOC100006303 Novel protein similar to glutaminase (Gls) 4.8 ± 1.2 0.048
37 hspd1 Heat shock 60 kD protein 1 4.7 ± 1.0 0.042
38 slmo2 Slowmo homolog 2 4.6 ± 1.0 0.048
39 abcf2 ATP-binding cassette, sub-family F 4.6 ± 0.9 0.042
40 zgc:92429 Hypothetical protein LOC445063 4.6 ± 0.7 0.040
41 kctd20 Potassium channel tetramerisation domain containing 20 4.5 ± 0.5 0.026
42 ppig Peptidylprolyl isomerase G 4.5 ± 0.9 0.049
43 g3bp1 Ras-GTPase-activating protein SH3-domain-binding protein 4.4 ± 0.9 0.042
44 slc4a2a Solute carrier family 4, anion exchanger, member 2a 4.4 ± 0.4 0.025
45 LOC100150539 Novel protein similar to vertbrate adenylate cyclase 9 (ADCY9)
Fragment 4.3 ± 0.9 0.050
46 sulf1 Sulfatase 1 4.3 ± 0.9 0.048
47 sae1 SUMO-activating enzyme subunit 1 (Ubiquitin-like 1-activating
enzyme E1A) 4.3 ± 0.5 0.028
48 zgc:85702 Hypothetical protein LOC321718 4.2 ± 0.7 0.042
49 abcb10 ATP-binding cassette, sub-family B (MDR/TAP), member 10 4.2 ± 0.9 0.048
50 ranbp1 RAN binding protein 1 4.1 ± 0.4 0.028
51 dazap1 Dazap1 protein Fragment 4.0 ± 0.7 0.049
52 il34 Interleukin 34 4.0 ± 0.6 0.040
53 frzb Frizzled-related protein 3.8 ± 0.4 0.037
54 zgc:113183 SWI/SNF-related, matrix-associated actin-dependent regulator of
chromatin, subfamily a, containing DEAD/H box 1 3.8 ± 0.5 0.041
55 smarca5 SWI/SNF related, matrix associated, actin dependent regulator of
chromatin, subfamily a, member 5 3.8 ± 0.7 0.049
56 agr2 Anterior gradient 2 homolog 3.7 ± 0.5 0.047
57 zgc:136374 2'-phosphodiesterase 3.7 ± 0.5 0.040
Chapter 2
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Table 2.4 (continuation)
Gene symbol Gene description Fold change
(Mean ± SE,
n=6)
Adjusted
P-value
58 stip1 Stress-induced-phosphoprotein 1 (Hsp70/Hsp90-organizing
protein) 3.7 ± 0.6 0.048
59 si:ch211-
132p20.4
Sodium-coupled neutral amino acid transporter 2 (Amino acid
transporter A2)(System A amino acid transporter 2)(System N
amino acid transporter 2)(System A transporter 1)(Solute carrier
family 38 member 2) 3.7 ± 0.4 0.038
60 zgc:172028 ADP-ribosylation factor 6-like 3.6 ± 0.6 0.048
61 zgc:153972 Transmembrane and coiled-coil domain family 1 3.5 ± 0.6 0.049
62 zgc:153290 Coiled-coil domain containing 51 3.5 ± 0.5 0.045
63 zgc:114204 Golgi transport 1 homolog B 3.5 ± 0.2 0.032
64 zgc:86751 Hypothetical protein LOC415227 3.4 ± 0.5 0.048
65 ppp4cb Serine/threonine-protein phosphatase 4 catalytic subunit B (PP4C-
B)(EC 3.1.3.16) 3.3 ± 0.5 0.048
66 LOC558153 Adaptor-related protein complex 2, alpha 1 subunit-like 3.3 ± 0.4 0.048
67 cmpk UMP-CMP kinase (EC 2.7.4.14)(Cytidylate kinase)(Deoxycytidylate
kinase)(Cytidine monophosphate kinase)(Uridine monophosphate
kinase)(Uridine monophosphate/cytidine monophosphate
kinase)(UMP/CMP kinase)(UMP/CMPK) 3.3 ± 0.5 0.049
68 si:ch211-253h3.1 si:ch211-253h3.1 3.3 ± 0.5 0.049
69 hspa5 Heat shock 70kDa protein 5 3.3 ± 0.3 0.045
70 slc38a4 Solute carrier family 38, member 4 3.3 ± 0.2 0.039
71 ncl1 Nicalin-1 Precursor (Nicastrin-like protein 1) 3.2 ± 0.2 0.039
72 ssrp1a Structure specific recognition protein 1a 3.2 ± 0.4 0.044
73 zgc:153327 Arginine-rich, mutated in early stage tumors 3.2 ± 0.3 0.041
74 lamb1 Laminin, beta 1 3.2 ± 0.3 0.041
75 zgc:77244 Potassium channel tetramerisation domain containing 5 3.2 ± 0.5 0.050
76 zgc:158393 Hypothetical protein LOC564849 3.2 ± 0.4 0.048
77 zgc:171630 Serine (or cysteine) proteinase inhibitor, clade H, member 1 3.2 ± 0.4 0.047
78 unc45b Unc-45 (C. elegans) related 3.1 ± 0.2 0.040
79 zgc:153981 Muscle-restricted dual specificity phosphatase 3.1 ± 0.2 0.041
80 sf3b4 Splicing factor 3b, subunit 4 3.1 ± 0.4 0.048
81 thoc6 THO complex 6 homolog (Drosophila) 3.0 ± 0.4 0.050
82 pl10 pl10 3.0 ± 0.3 0.047
Chapter 2
63
Table 2.4 (continuation)
Gene symbol Gene description Fold change
(Mean ± SE,
n=6)
Adjusted
P-value
83 tram1 Translocating chain-associating membrane protein 1 3.0 ± 0.3 0.048
84 zgc:56005 Oxidative stress induced growth inhibitor 1 3.0 ± 0.3 0.049
85 prelid1 PRELI domain containing 1 3.0 ± 0.2 0.044
86 per2 Period homolog 2 3.0 ± 0.3 0.048
87 si:ch211-59d15.5 YLP motif containing 1 2.8 ± 0.1 0.042
88 snrnp40 Small nuclear ribonucleoprotein 40 (U5) 2.8 ± 0.1 0.042
89 ehd1 EH-domain containing 1 2.8 ± 0.3 0.048
90 si:ch211-286m4.4 Exportin-T (tRNA exportin)(Exportin(tRNA)) 2.8 ± 0.2 0.049
91 alg9 Asparagine-linked glycosylation 9 protein 2.7 ± 0.3 0.050
Table 2.5 – Enrichment analysis of gene ontology terms for biological processes associated with
genes differentially regulated in response to a single-satiating meal using the 44K Agilent zebrafish
microarray V2. Only the most-specific terms are shown in the table.
GO
Identifier
GO Term Number of genes
differentially
expressed
FDR*
Enriched with fasting
GO:0043632 modification-dependent macromolecule catabolic process 8 0.031
GO:0045603 positive regulation of endothelial cell differentiation 2 0.052
Enriched with feeding
GO:0042026 protein refolding 3 0.004
GO:0051604 protein maturation 3 0.035
GO:0030241 skeletal muscle thick filament assembly 2 0.035
GO:0034619 cellular chaperone-mediated protein complex assembly 2 0.035
GO:0042517 positive regulation of tyrosine phosphorylation of Stat3
protein 2 0.035
GO:0048769 sarcomerogenesis 2 0.035
GO:0046425 regulation of JAK-STAT cascade 3 0.042
GO:0045618 positive regulation of keratinocyte differentiation 2 0.045
GO:0045606 positive regulation of epidermal cell differentiation 2 0.054
GO:0070096 mitochondrial outer membrane translocase complex
assembly 2 0.068
* FDR – false discovery rate.
Chapter 2
64
2.4.8. Expression and clustering of candidate nutritionally-regulated genes
A selection of candidate nutritionally-regulated genes comprising 8 genes up-regulated
with fasting (fbxo32, trim63, klf11b, nr1d1, cited2, bbc3, znf653, hsf2) and 6 genes up-
regulated with feeding (odc1, fkbp5, sae1, foxo1a, hsp90a.1, hsp90a.2) plus some
contractile protein genes (mylz2 and tnni2a.4) was further investigated using qPCR. The
log fold-change in expression of all the genes assayed by qPCR showed a good
correlation with the microarray experiment (R = 0.79; P<0.001; n = 76) (Figure 2.6).
Genes from the IGF pathway and those selected from the microarray experiment formed
five major clusters (Figure 2.7). Cluster I contained genes up-regulated with feeding,
with low levels of expression during prolonged fasting (-24 and 0h) and intermediate
levels of expression from 9 to 36h (igf1a, hsp90a.1, odc1, foxo1a, igfbp6a, igf2b, sae1 and
fkbp5). Cluster II comprised genes that were down-regulated at -159h and from 0.75 to
9h, with upregulation during prolonged (-24 and 0h) and early fasting (12-36h) (igf1ra,
igf2r, igf1rb, fbxo32, trim63, klf11b, bb3 and znf653). Cluster III contained genes that
were only up-regulated with prolonged fasting (144 and 168h) and just after the
beginning of feeding (45 min), with low expression at other time points (tnni2a.4,
hsp90a.2, nr1d1, igfbp1a, hsf2 and igfbp1b). Cluster IV comprised genes with high
expression during prolonged fasting, low expression whilst the intestine was full (0.75
to 6h), and intermediate levels of expression from 7.5 to 36h (igf2a, igfbp3 and cited2).
Cluster V comprised genes with high expression with prolonged fasting, but with
intermediate level of expression during feeding and early fasting (mylz2, igfbp5b,
igfbp2b, igfbp5a, igfbp2a, igfbp6b). Genes pairs that showed strong significant
correlations (R>0.7, p<0.05, n=126) were considered candidates for co-regulation of
expression. Eight strong positive correlations were found and included hsf2 versus
nr1d1 (R=0.83; P<0.001) and fbxo32 (R= 0.78; P<0.001); bbc3 versus znf653 (R=0.76;
P<0.001) and klf11b (R= 0.75; P<0.001); fbxo32 versus trim63 (R= 0.73; P<0.001); and
bbc3 versus cited2 (R= 0.73; P<0.001) and fbxo32 (R= 0.72; P<0.001). The only strong
negative correlation found was between odc1 and bbc3 (Cluster II).
All 8 of the candidate genes up-regulated with fasting in the microarray
experiments were validated by qPCR. The expression of the muscle-specific ubiquitin
ligases, MAFbx/Atrogin-1 (annotated with the synonym fbxo32 in the zebrafish genome
assembly) and MURF1 (annotated as trim63) was highly sensitive to nutritional status.
mRNA transcripts for fbxo32 and trim63 increased 13.3 and 2.7-fold, respectively,
Chapter 2
65
between 9h and 144h of fasting and were down-regulated by 55% (fbxo32) and 77%
(trim63) in the 45min sample after feeding, with lowest levels observed after 6h (Figure
2.8A, B). Expression of both genes started to increase soon after food was cleared from
the intestine and mRNA levels were at 168h fasting levels by 36h after the meal (Figure
2.8A, B).
Four genes (bbc3, cited2, znf653 and klf11b) had expression patterns that were
inversely correlated with gut fullness. Transcript abundances were lowest 45min to 3h
after feeding and rapidly increased as the gut emptied (Figure 2.9A-D). nr1d1 and hsf2
mRNA levels increased ~130 and ~21-fold between 9h and 144h of fasting,
respectively, and were strongly down-regulated with feeding and showed a transient
increase in levels 15h after the intestine was empty (Figure 2.9E, F). Three of the
selected genes up-regulated with feeding in the microarray experiment showed
expression patterns related to gut fullness. fkbp5 and odc1 showed a peak of expression
coincident with the presence of food in the intestine corresponding to a 5.6 and 17.2-
fold increase in transcript abundance relative to maximal fasting values, respectively
(Figure 2.10A, B). sae1 showed a ~6.5-fold increase in expression 6 to 9h after the start
of the meal and a steady decline to levels not significantly different from fasting values
by 36h (Figure 2.10C).
Chapter 2
66
Figure 2.6 – Correlation between log fold changes in mRNA levels of 38 genes from
qPCR and microarray experiments from two hybridizations: 0 with 3h () and 0 with 6h
samples () (Spearman’s correlation test, n=76, r2=0.79, p<0.001).
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
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Log fold change Microarray
Chapter 2
67
Figure 2.7 – Hierarchical clustering and heat map of Insulin-like growth factor (IGF)
system gene transcripts and candidate nutritionally regulated genes identified from
microarray experiments over the time course of the single meal experiment. The roman
numbers indicate clusters discussed in the text. Rows (mRNA transcripts) in the
heatmap are standardised to have mean of zero and standard deviation of one (i.e.
standard score normalisation). Red and green shading respectively indicates the highest
and lowest expression levels as indicated in the scale bar at the bottom of the figure.
Each block represents the average standard-score normalisation for the 13 fish sampled
at each time point in the experiment.
Chapter 2
Figure 2.8 – Expre
from microarray ex
determined by qPC
MAFbx (fbxo32) an
grey line represent
mean ± s.e.m., n =
means at 0.05 signif
B
A
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.)ssion profiles of ubiquitin ligase genes in male zebrafish identified
periments over the time course of the single meal experiment as
R (solid squares): Genes up-regulated during fasting (A) Atrogin 1-
d (B) Muscle-specific RING finger protein 1 - MURF1 (trim63). The
s the average gut fullness illustrated in Figure 2.2. Values represent
13 fish per sample. Different letters signify statistically different
ance level.
LightLight DarkLight Darkic68
Chapter 2
69
Figure 2.9 – Expression profiles of candidate nutritionally-regulated genes in male
zebrafish identified from microarray experiments over the time course of the single
meal experiment as determined by qPCR (solid squares): genes up-regulated during
fasting: (A) BCL2 binding component 3 (bbc3), (B) Cbp/p300-interacting transactivator,
with Glu/Asp-rich carboxy-terminal domain, 2 (cited2), (C) zinc finger protein 653
(znf653), (D) Kruppel-like factor 11b (klf11b), (E) nuclear receptor subfamily 1, group
d, member 1 (nrld1), and (F) heat shock factor 2 (hsf2). The grey line represents the
average gut fullness illustrated in Figure 2.2. Values represent Mean ± s.e.m., n = 13 fish
0
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FE
Chapter 2
per sample. Different letters signify statistically different means at 0.05 significance
level.
Figure 2.10 – Expression profiles of candidate nutritionally-regulated genes in male
zebrafish identified from microarray experiments over the time course of the single
meal experiment as determined by qPCR (solid squares): Genes up-regulated with
feeding (A) FK506 b nding protein 5 (fkbp5) (B) Ornithine decarboxylase 1 (odc1) and
(C) SUMO-activating
A
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Time (h)i70
enzyme subunit 1 (sae1). The grey line represents the average gut
Chapter 2
71
fullness illustrated in Figure 2.2. Values represent mean ± s.e.m., n = 13 fish per sample.
Different letters signify statistically different means at 0.05 significance level.
2.5. Discussion
2.5.1. Transcriptional regulation of the IGF system
Transit of food through the gastrointestinal system and phosphorylation of the IGF-
pathway signaling protein Akt provide a context for interpreting the transcriptional
response to a single satiating meal in the absence of information on plasma hormone
and amino acid levels in small tropical fishes. In a previous fasting-refeeding study on
the rainbow trout, Oncorhynchus mykiss, maximum plasma insulin and amino acid levels
were recorded 30min and 2.5h after feeding and were quickly followed by
phosphorylation of several kinases indicating activation of the TOR signaling pathway
(Seiliez et al., 2008). Amino acids and insulin also rapidly increase the level of
circulating IGFI in brown trout (Banos et al., 1999). In the present experiments with
zebrafish, 50% of the food ingested had been processed and eliminated within 3h after
the start of feeding and the gut was empty after 9h (Figure 2.2). Akt showed a significant
increase in phosphorylation within 45min, with peak levels at 3h of feeding and became
dephosphorylated over a similar time course to the elimination of food from the gut
(Figure 2.3). Changes in muscle mRNA levels also mostly took place with a time course
of hours and were generally quicker than described in the literature for larger
temperate fish species maintained at lower temperatures (Chauvigne et al., 2003;
Bower et al., 2008).
The first aim of this chapter was to test the hypothesis that retained paralogues
of IGF-system genes were differentially regulated following transition from a catabolic
to an anabolic state. Fasting has been shown to result in an upregulation of muscle igf1
receptors in a number of teleost species and is probably a response to a decrease in
circulating IGF hormone levels (Chauvigne et al., 2003; Gabillard et al., 2006; Bower et
al., 2008; Bower and Johnston, 2010a). In rainbow trout, prolonged fasting resulted in
an upregulation of igf1ra, but not igf1rb (Chauvigne et al., 2003) whereas in zebrafish
both IGFR paralogues were upregulated (Figure 2.5A, B). However, zebrafish igf1rb
increased more rapidly following gut emptying than igf1ra reaching fasting levels >36h
and <25h respectively (Figure 2.5A, B), indicating differential regulation of igf1 receptor
Chapter 2
72
paralogues. Functional characterisation studies of the igf2r in fish are scarce and its role
in the response to nutrient levels is not yet clear. In Atlantic salmon, igf2r transcripts
were significantly upregulated with prolonged fasting and downregulated after 7 days
of refeeding (Bower et al., 2008). In this study there was no discernible pattern of
transcriptional regulation of igf2r over the experiment. Muscle IGF hormone transcript
levels showed distinct peaks within a few hours of feeding (Figure 2.4A, B). In the case
of igf1a peak values were found within 3h of feeding and had declined to fasting levels
before the gut was emptied (<5h) (Figure 2.4A). In contrast, igf2b transcripts reached a
peak 6h after feeding and were not significantly different to fasting levels by 9h (Figure
2.4B). Igf1b transcripts were not detected in fast muscle whereas the igf2a paralogue
was constitutively expressed and showed no consistent change in expression over the
fasting-feeding-fasting cycle associated with a single meal. In vitro studies with Atlantic
salmon (Salmo salar) myocytes have shown synergistic effects of insulin, igf1 and amino
acids on muscle igf1 transcript abundance, indicating multiple pathways leading to igf1
transcription (Bower and Johnston, 2010b). In mammals, the binding of IGFs to the igf1r
induces its auto-phosphorylation resulting in the activation of several down-stream
signal transduction cascades via adaptor molecules such as the insulin receptor
substrate 1 (IRS-1) which has multiple tyrosine phosphorylation sites (Duan et al.,
2010). Igf1 stimulates growth via effects on protein synthesis (Rommel et al., 2001),
myoblast proliferation and differentiation acting through distinct signaling pathways
(Ren et al., 2010). The effective concentration of IGFs in the muscle is regulated by 6
IGF-binding proteins (IGFBPs) which are degraded by specific proteases to release the
hormone to target sites (Wood et al., 2005a). Evidence, largely from mammals,
indicates that IGFBPs can inhibit and/or potentiate IGF actions depending on the
cellular context and/or environmental conditions (Duan et al., 2010). In Atlantic
salmon, the transition from maintenance to fast growth was associated with a
constitutive upregulation of igfbp4, a transient increase in igfbp5.1, and a
downregulation of igfbp2.1 (Bower et al., 2008). The two retained zebrafish paralogues
of igfbp1 had similar expression in the single meal experiment with high transcript
abundance during fasting, a marked reduction in mRNA levels within 45min of feeding
and variable, but generally low level of expression over the following 36h (Figure 2.5D).
Mammalian studies indicate that in addition to its role as a modulator of igf1
availability, igfbp1 has putative IGF-independent biological activities through
Chapter 2
73
interaction with cell-surface integrins, with putative direct effects on the
PI3K/AKT/mTOR pathway (Wheatcroft and Kearney, 2009). There was no evidence for
the transcriptional regulation of igfbp2a, b, igfbp3, igfbp5a, b, igfbp6a and b paralogues
with feeding in the present experiments. Although experimental context may explain
some of these differences in IGFBP expression it is clear that there are lineage-specific
differences in IGF binding protein function and regulation within the teleosts. For
example, igfbp4 is not represented in the current Danio rerio genome assembly
(http://www.sanger.ac.uk/Projects/D_rerio/) and is probably absent from the
zebrafish lineage. These results at least indicate that caution is needed in inferring
similar functions of IGFBPs between teleost lineages and certainly between teleosts and
mammals. Overall the conclusion is that following WGD some of the retained paralogues
of IGF-system genes show differential transcriptional regulation with fasting and
refeeding in skeletal muscle, but that complex patterns of regulation have evolved
between and within lineages.
2.5.2. Genome-wide transcriptional regulation with catabolic to anabolic transition
Microarray experiments provided a snapshot of the fast muscle transcriptome during
fasting and at the point IGF transcripts reached their maximum abundance following
feeding. The screening criteria used to build lists of differentially regulated genes were
apparently robust since all 14 genes tested were validated by qPCR and were well
correlated (R=0.79, Figure 2.6). Fasting in zebrafish (Figure 2.8A, B) and Atlantic
salmon (Bower et al., 2008; Bower and Johnston, 2010a) is associated with a large
increase in the abundance of E3 ubiquitin ligases MURF1 and atrogin-1/MAFbx
transcripts. In mammals, the ubiquitin substrate recognition system has been
implicated in specific degradation of myoD (Tintignac et al., 2005; Finn and Dice, 2006)
and other promyogenic transcription factors (Finn and Dice, 2006). Two substrate
recognition components of the ubiquitin ligase system, F-box only protein 25 (fbxo25)
and RAB40B, member RAS oncogene family (rab40b), were also highly up-regulated
with fasting in zebrafish fast muscle (Table 2.3). Two genes with putative roles in
autophagy were found to be up-regulated during food deprivation [microtubule-
associated protein 1 light chain 3 beta (map1lc3b) and neighbour of BRCA1 gene (nbr1)]
(Table 2.3). It is known that myofibrillar proteins are degraded to provide a source of
Chapter 2
74
amino acids for energy metabolism during prolonged fasting in teleosts (Johnston and
Goldspink, 1973). However, the relative importance of the ubiquitin-proteasome
degradation pathway, autophagy and other classes of proteases in mediating protein
breakdown during normal protein turnover and short periods of fasting remains to be
established. Cell cycle arrest and apoptosis also seems to be an important response in
adapting to periods of limited energy supply in zebrafish as evidenced by the
upregulation of antiproliferative protein gene transcripts [B-cell translocation gene 1
and 2 (btg1 and 2), THAP domain-containing protein 1 (thap1) and pro-apoptotic genes
(bbc3 and klf11b)] (Table 2.3).
Transition to an anabolic state 3h after the meal resulted in major changes in the
muscle transcriptome. Feeding was associated with the upregulation of transcripts for
chaperone proteins (unc45b, ppig, pdip5, dnaja, stip1) including various heat shock
proteins and associated proteins (hsp90a.1, hsp90a.2, hsdp1, hspa5) (Table 2.4).
Molecular chaperones are essential for both the folding and maintenance of newly
translated proteins and the degradation of misfolded and destabilized proteins (Zhao
and Houry, 2007). In zebrafish, the chaperones hsp90a and unc45 are coregulated and
involved in the folding of the globular head of myosin during myofibrillargenesis,
associating with the Z line once myofibrillar assembly is completed (Etard et al., 2008).
The sequencing of subtractive cDNA libraries from fast skeletal muscle of Atlantic
salmon fed either maintenance or satiating rations also revealed that expression of
chaperone proteins indicative of unfolded protein response (UPR) pathways such as
dnaj4, hspa1b, hsp90a and chac1 was an early response to increased food intake and
growth (Bower and Johnston, 2010a). Accumulation of unfolded proteins can occur
when the amounts of newly synthesised proteins exceeds that of the protein folding
capacity of the endoplasmic reticulum (Okada et al., 2002). Taken together these results
indicate that an increase in protein chaperone gene expression and activation of UPR
pathways is a general response of teleost skeletal muscle following the transition from a
catabolic to anabolic state.
The largest increase in transcript abundance found with feeding was for the gene
coding the enzyme ornithine decarboxylase 1 (odc1) (11.5-fold). Ornithine
decarboxylase, a key metabolic enzyme of the polyamine biosynthesis pathway, also
showed an increase in activity after feeding in fasted rat tissues (Moore and Swendseid,
1983). Polyamines have a number of biological functions including cell growth and
Chapter 2
75
apoptosis and act in a concentration-dependant manner (Larqué et al., 2007). The
anabolic state was associated with enrichment of GO terms for mitochondrial
translocase activity, initiation of protein synthesis [e.g. eukaryotic translation initiation
factor 4A isoform 1A (eif4a1a), dual-specificity tyrosine-(Y)-phosphorylation regulated
kinase 2 (dyrk2)] and mRNA processing, maturation and export protein genes [e.g.
DEAD (Asp-Glu-Ala-Asp) box polypeptide 5 (DDX5) and small nuclear ribonucleoprotein
40 (U5) (snrnp40)]. Furthermore, pias4 and sae1, which are involved in the post-
translational conjugation of SUMO (small ubiquitin-like modifier) to target proteins,
were up-regulated with feeding. Sumoylation of proteins may affect their stability,
localization and activity (Geiss-Friedlander and Melchior, 2007). In contrast to the
ubiquitin-conjugated proteins, sumo-conjugated proteins are not targeted for
degradation and indeed sumoylation may function as an antagonist pathway to the
ubiquitin-proteasome pathway (Desterro et al., 1998; Hay, 2005).
Feeding was also associated with significant changes in the expression of genes
that may function as epigenetic switches coding for proteins that modify chromatin
structure and alter the expression of suites of other genes. For example, SET and MYND
containing protein 1b (smyd1b) transcripts increased 4.8-fold between the fed and
fasted states (Table 2.4). Smyd1 functions as a transcriptional repressor in mouse
cardiac muscle (Gottlieb et al., 2002) and is required for normal skeletal muscle
development in zebrafish (Tan et al., 2006). In the present study feeding also resulted
in a 4.9-fold increase in transcript abundance for the euchromatic histone-lysine N-
methyltransferase 1b fragment gene (ehmt1b). The human orthologue of ehmt1b was
found to be part of the E2F6 complex and is probably involved in the silencing of MYC-
and E2F-responsive genes (Ogawa et al., 2002), and is thought to play a role in G0/G1
cell-cycle transition.
The recruitment and hypertrophy of fast myotomal muscles in zebrafish was shown
to be typical of teleosts (Johnston et al., 2009). The present study also demonstrates the
utility of the zebrafish for mechanistic studies on the regulation of growth signalling
pathways in teleost muscle providing the advantages of a sequenced genome,
commercially available molecular resources and low husbandry costs due to the small
body size. However, caution should be applied in extrapolating all results from model to
aquaculture fish species in the light of evidence for lineage-specific patterns of
paralogue retention (Macqueen and Johnston, 2008a, 2008b) and IGFBP gene
Chapter 2
76
expression (this chapter). The single meal paradigm also provides an interesting
alternative to the use of continuous feeding regimes to investigate transcriptional
regulation during the transition from a catabolic to an anabolic state.
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77
3. Circadian expression of clock and putative clock-controlled genes
in skeletal muscle of the zebrafish
3.1. Summary
To identify circadian patterns of gene expression in skeletal muscle, adult male zebrafish
were acclimated for two weeks to a 12:12h light:dark photoperiod and then exposed to
continuous darkness for 86h with ad libitum feeding. The increase in gut food content
associated with the subjective light period (SLP) was much diminished by the third cycle
enabling feeding and circadian rhythms to be distinguished. Expression of zebrafish
paralogues of mammalian positive regulators of the circadian mechanism (bmal1, clock1
and rora) followed a rhythmic pattern with a ~24h periodicity. Peak expression of rora
paralogues occurred at the beginning of the SLP [Zeitgeber time (ZT)07 and ZT02 for
roraa and rorab] whereas the highest expression of bmal1 and clock paralogues occurred
12h later (ZT13-15 and ZT16 for bmal and clock paralogues). Expression of the negative
oscillators cry1a, per1a/1b, per2, per3, nr1d2a/2b, and nr1d1 also followed a circadian
pattern with peak expression at ZT00-02. Expression of the two paralogues of cry2
occurred in phase with clock1. Duplicated genes had a high correlation of expression
except for paralogues of clock1, nr1d2 and per1, with cry1b showing no circadian pattern.
The highest expression difference was 9.2-fold for the positive regulator bmal1b and 51.7-
fold for the negative oscillator per1a. Out of 32 candidate clock-controlled genes, only
myf6, igfbp3, igfbp5b and hsf2 showed circadian expression patterns. Igfbp3, igfbp5b and
myf6 were expressed in phase with clock1 and had an average of 2-fold change in
expression from peak to trough whereas hsf2 transcripts were expressed in phase with
cry1a and had a 7.2 fold-change in expression. The changes in expression of clock and
clock-controlled genes observed during continuous darkness were also observed at
similar ZTs in fish exposed to a normal photoperiod in a separate control experiment. The
role of circadian clocks in regulating muscle maintenance and growth are discussed.
Chapter 3
78
3.2. Introduction
Teleost fish show pronounced circadian rhythms of foraging behaviour and locomotor
activity that are driven by central oscillators in the brain, synchronised by light cycles (del
Pozo et al., 2011), and modulated by a variety of environmental cues including
temperature (Lahiri et al., 2005) and food availability (Sanchez et al., 2009; Sanchez and
Sanchez-Vazquez, 2009). The rhythm and period of circadian biological processes are
driven by a complex molecular clock machinery which is highly conserved across the
animal kingdom. Knowledge about basic clock mechanisms and functions are largely
derived from studies in Drosophila (Plautz et al., 1997; Peschel and Helfrich-Forster,
2011) and mice (Ripperger et al., 2011), with increasing interest in the zebrafish model
(Danio rerio) [reviewed in (Vatine et al., 2011)]. The molecular clock involves
transcription-translation and post-translational feedback loops, for example in mammals
the transcription factor bmal1 forms a dimer with another PAS domain protein, clock, to
activate period (per1 and per2) and cryptochrome (cry1 and cry2) genes (Ripperger et al.,
2011). Per and cry proteins are translocated into the cell nucleus where they inhibit their
own transcription. Secondary feedback loops involving the rora (transcriptional activator
of bmal1) and rev-erbα genes (nr1d1, transcriptional repressor of bmal1) act to stabilise
the clock mechanism whereas post-translational modifications of the per-cry dimer are
required to set the period of the rhythm (Takahashi et al., 2008). In mice, light
information received by the eyes travels to the suprachiasmatic nucleus which
synchronizes the central and peripheral molecular clocks in a hierarchical manner [cf.
(Ripperger et al., 2011)], i.e. peripheral clocks are entrained and synchronized to the
central pacemaker. Studies in the teleosts have demonstrated that the pineal gland is the
central photoreceptive organ, which contains intrinsic circadian oscillators that drive the
rhythmic secretion of melatonin in response to light input [cf. (Cahill, 2002; Falcon et al.,
2011)]. The role of the pineal as a hierarchical master clock in fish has been under
discussion since observations that dissected zebrafish peripheral tissues (heart and
kidney) and cells in cultures can be directly entrained by light and show a robust
circadian rhythm (Whitmore et al., 1998). There is a growing body of information on
zebrafish genes whose expression is inducible by light (Tamai et al., 2007; Vatine et al.,
2009; Weger et al., 2011). Of particular interest is the observation that two main
oscillators of the circadian rhythm namely per2 and cry1a are inducible by light and that
Chapter 3
79
deletion or mutation of the light responsive elements from the promoter of these genes
cause disruption of the clock mechanism (Tamai et al., 2007; Vatine et al., 2009). Thus, the
peripheral clock mechanism in fish has some similarities with that in Drosophila, which is
directly responsive to light (Plautz et al., 1997). However, it remains to be determined
whether enough light reaches the internal organs of adult zebrafish to render them
photoreceptive and photoresponsive, and how the putative in vivo peripheral
entrainment to light interacts with the neuroendocrine signals from the pineal.
Microarray studies have identified several hundred genes with circadian patterns
of expression in mouse liver and skeletal muscle (Miller et al., 2007). Genes that are under
control of the clock mechanism are referred to as clock controlled genes (CCGs), which are
responsible for the integration between the clock mechanism and other physiological
pathways, and ultimately orchestrate the biological output of the circadian pathway. For
example, the positive oscillator of the stabilizing loop nr1d1 has been shown to play an
important role in the genomic recruitment of histone deacetylase 3 (hdac3) in mouse liver
(Feng et al., 2011). Hdac3 functions in lipid homeostasis and absence of nr1d1 caused
impaired lipid metabolism with subsequent changes in the phenotype of the liver (Feng et
al., 2011). The clock mechanism is also important for the physiology of other peripheral
tissues and has been shown to play a pivotal role in maintaining muscle phenotype in the
mouse (Andrews et al., 2010). In this tissue, the clock gene controls the expression of
myoD, a member of the myogenic regulatory factor family, which functions in muscle
determination and differentiation (McCarthy et al., 2007; Andrews et al., 2010). The
absence of a functional clock mechanism in this tissue led to reduced force generation and
reduced mitochondrial volume, mediated by the CCGs myoD and pcg1a/β respectively
(Andrews et al., 2010).
Zebrafish have many advantages as a model system for investigating circadian
clocks, including transparent embryos which facilitate the imaging of fluorescent reporter
genes in vivo and the ease of performing large-scale forward genetic screens (Vatine et al.,
2011). Danio is a diurnal fish that is mostly active during the subjective light phase of the
photoperiod, with clear differences in locomotor activity and spawning behaviour
between the dark and light phases (Hurd et al., 1998; Blanco-Vives and Sanchez-Vazquez,
2009). Teleost fish underwent whole genome duplication early in their evolution, and
subsequent differential patterns of gene loss have resulted in lineage-specific differences
Chapter 3
80
in the paralogues retained (Wang, 2008b). For example, the zebrafish and Tiger pufferfish
(Takifugu rubripes) have three clock genes whereas the stickleback and Japanese Medaka
fish have two (Wang, 2008b). Additional copies of bmal1, cry1, cry2, per1, rora, and rev-
erbβ (nr1d2) genes have also been described for zebrafish (Kobayashi et al., 2000; Flores
et al., 2007; Wang, 2008a; Wang, 2009). The expression pattern of the main oscillators of
the circadian rhythm in zebrafish have been investigated in the retina, brain, pineal gland,
and Z3 cell line [reviewed in (Vatine et al., 2011)].
The main objective of the present chapter was to provide a detailed description of
the expression of 17 clock genes and their paralogues in zebrafish skeletal muscle.
Circadian patterns of expression were determined in relation to the subjective light cycle
in fish exposed to 3-4 cycles of continuous darkness. Using qPCR and a robust
normalisation strategy, the hypothesis that the expression of myogenic regulatory factors,
components of the insulin-like growth factor (IGF) system and other selected nutritionally
responsive genes in skeletal muscle is under control of the circadian clock mechanism
was also investigated.
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81
3.3. Materials and Methods
3.3.1. Fish and water quality
The F8 generation of a wild-caught population of zebrafish [Danio rerio (Hamilton 1822)]
from Mymensingh, Bangladesh was used. All fish were adult males aged 10 months [total
length (TL) = 38.1 ± 0.2mm and body mass (BM) = 496 ± 8mg (mean ± s.e.m, N=130)]. The
source colony and experimental animals were kept in a stand-alone freshwater
circulating system, which included a UV water sterilising device and biological, chemical
and particle filters. Nitrite (0 ppm), nitrate (10-20 ppm), ammonia (0 ppm) and pH (7.6 
0.2) were tested during acclimation and experimental periods using a Freshwater Master
Test Kit (Aquarium Pharmaceuticals Inc., Chalfont, PA, USA). All experiments and animal
handling were approved by the Animal Welfare and Ethics Committee, University of St
Andrews and conformed to UK Home Office guidelines.
3.3.2. The circadian rhythm experiment
140 male fish from the same breeding stock were transferred to 4 separate tanks (N=35
per tank, 50L freshwater) maintained at 27.6 ± 0.3ºC range, in a 12:12h light:dark
photoperiod and fed bloodworms (Ocean Nutrition™, Belgium) to satiety twice daily. Fish
were acclimated for 2 weeks in the experimental tanks under the same environmental
conditions as the source colony. The lights were switched-off at the beginning of a light
cycle (10a.m.) to start the experiment (referred to as cycle 1: time 0h, C1:ZT00) and
continuous darkness was maintained for 86h, corresponding to three complete light-dark
cycles of the acclimation period (Figure 3.1). 10 fish were randomly sampled from one of
the 4 tanks every 4h from C2:ZT02 to C4:ZT02, resulting in 13 time-points (N=130 fish),
using a very dim torch-light directed to the floor. The fish were not disturbed during
sample collection as no sudden change in activity was observed. After collection at each
time-point additional bloodworms were offered to the fish to make sure food was
available at all times across the experiment. This experimental design reduced the
possibility of stress due to excessive handling since each tank was disturbed only every
16h. In addition, no maintenance was necessary for the duration of the acclimation and
experimental periods due to the automatic filtration system which prevented the creation
of external cues to which the fish could respond. The fish were killed by an overdose of
Chapter 3
82
ethyl 3-aminobenzoate methanesulphonate salt (MS-222) (Fluka, St Louis, MO, USA) and
had their TL and BM measured. Condition factor was calculated as
K=[(BM/100)/(TL/10)^3]. Fast skeletal muscle was dissected from the dorsal epaxial
myotomes, flash frozen in liquid nitrogen and stored at -80ºC prior to total RNA
extraction. The digestive tract was dissected and fixed in 4% (m/v) paraformaldehyde for
later quantification of intestine content to the nearest milligram. A control experiment
under normal 12:12h light: dark photoperiod was performed eight months later using the
F9 generation of fish, which were 11 months old. In this experiment the fish were
collected at two time-points (ZT02 and ZT14) after two weeks of acclimation under the
same environmental conditions as the continuous dark experiment. These time-points
were chosen to confirm that either the maximum or minimum of expression observed in
skeletal muscle under continuous darkness photoperiod also occurred under the normal
12:12h light:dark photoperiod. The sampling and data collection were as described for
the continuous darkness experiment. Total RNA extraction and first strand cDNA
synthesis were as described in section 2.3.5.
Chapter 3
83
Figure 3.1 – Experimental design of the continuous darkness photoperiod experiment:
male fish from the source colony of zebrafish (N=140), kept at 27.6±0.3ºC range in a
12:12h light:dark photoperiod and fed bloodworms twice daily, were transfered to four
separate tanks with the same environmental conditions as the source colony (N=35 fish
per tank). After two weeks of acclimation, 10 fish were randomly collected after 38h in
continuous darkness every 4h for 48h until 86h of continuous darkness, resulting in 13
time-points (N=130 fish). Condition factor, gut food content and gene expression in
skeletal muscle (by qPCR) were determined for each fish. A complete 12:12h light: dark is
considered one cycle and times from ZT0 to ZT12 and ZT12 to ZT24 represent the
subjective light and dark period of the cycle, respectively.
3.3.3. Primer design and screening for circadian expression by qPCR
Primer pairs were designed for 16 genes described as core-clock genes in other
vertebrate models and tissues (bmal1a, bmal1b, clock1a, clock1b, cry1a, cry1b, cry2a,
cry2b, per1a, per1b, per2, per3, roraa, rorab, nr1d2a, and nr1d2b), and 4 myogenic factors
genes (myoD, myog, myf5, and myf6) as described in section 2.3.7 (Table 3.1). Previously
validated primer pairs for 15 genes of the IGF pathway (igf1a, igf2a, igf2b, igf1ra, igf1rb,
igf2r, igfbp1a, igfbp1b, igfbp2a, igfbp2b, igfbp3, igfbp5a, igfbp5b, igfbp6a, and igfbp6b), 2
ubiquitin ligases genes (MAFbx and trim63), and 12 nutritionally responsive genes [odc1,
Chapter 3
84
hsp90a.1, fkbp5, sae1, hsp90a.2, foxo1a, klf11b, nr1d1 (known to be a circadian oscillator) ,
cited2, bbc3, znf653, and hsf2) were also used (Table 2.1).
The qPCR reagents and conditions were as described in section 2.3.8. and followed
the MIQE guidelines (Bustin et al., 2009). After the qPCR a dissociation curve (from 55 to
95ºC) was performed to verify the presence of a single peak. The specificity of each qPCR
assay was also validated by directly sequencing the qPCR products in both directions. The
efficiency of each primer pair was calculated by the LinReg software (Ruijter et al., 2009)
(Table 3.1) and used to calculate arbitrary mRNA copy numbers. Four reference genes
[ef1a, bactin2, lman2 (Table 2.1), and gapdh (Table 3.1)] were analysed using Genorm
v3.5 (Vandesompele et al., 2002) with M set to <1.5. The two genes with the most stable
level of expression across the experiment were ef1a and bactin2 (M=0.3). The expression
of genes of interest was normalized to the geometric average of the two most stable genes
and gene expression was reported as arbitrary units (a.u.).
Genes were screened for circadian expression using pools containing equal
amounts of cDNA from 10 fish per time-point. Transcript levels were analysed using the
ARSER algorithm (Yang and Su, 2010) with period window of 20-28h and a false
discovery rate (FRD) set to 0.05 (Benjamini and Hochberg, 1995). Individual reactions
were carried out for all genes that passed these screening criteria for rhythmic expression
plus cry1b and nrld2a (two genes paralogous to core-clock genes). The screening step was
robust since: (a) the results of mRNA levels calculated by the screening and individual
reactions were highly correlated (Spearman’s correlation test, N=500, R=0.85, p<0.001);
and (b) periodicity parameters calculated by the ARSER algorithm using the results from
the individual reactions resulted in values very similar to those calculated for the
screening reactions.
3.3.4. Data analysis and statistics
All data was analysed for normal distribution and equality of variance. Normally
distributed data was analysed using ANOVA followed by Tukey post-hoc tests using PASW
Statistics 18 (SPSS Inc., Chicago, Illinois, USA). Kruskal-Wallis non-parametric tests
followed by Conover post-hoc tests in BrightStat software (Stricker, 2008) were used for
the data that was not normally distributed. Hierarchical clustering of gene expression and
heat-maps were produced using PermutMatrix
Chapter 3
85
(http://www.lirmm.fr/~caraux/PermutMatrix/EN/index.html). Correlation of mRNA
levels between genes was analysed by Spearman’s correlation test in SPSS.
Table 3.1 – Sequence and properties of primers used in the experiments of chapter 3.
Ensembl gene symbols, forward (f) and reverse (r) primer sequences, product size,
product melting temperature (Tm), calculated efficiency (E) and Ensembl gene ID are
shown.
Ensembl
Gene
symbol
f/r Primer 5'-3' sequence Product
Size (bp)
Tm
(ºC)
E Ensembl Gene ID
Reference gene
gapdh f: TAACGGATTCGGTCGCATTG 226 83.6 105.3 ENSDARG00000043457
r: GGCTGGGTCCCTCTCGCTA
Core circadian genes
per1b f: CCTCCTGAGTCAGATATCGTAATGG 324 85.0 96.2 ENSDARG00000012499
r: GCAGCGCACACCTCTTGATAA
per1a f: GTTCGAACGAGTCCGCTAAATG 256 85.3 99.6 ENSDARG00000056885
r: TGTCATTGGTTTCCTGGGCTT
per2 f: GTGGAGAAAGCGGGCAGC 252 87.4 95.9 ENSDARG00000034503
r: GCTCTTGTTGCTGCTTTCAGTTCT
per3 f: CCACAGCCTGAGTCCGAAGTC 300 87.8 98.0 ENSDARG00000010519
r: CCCCTCTGTGATGTGAATGTGC
roraa f: GCATGTCACGTGACGCGGT 424 87.1 96.1 ENSDARG00000031768
r: TGGGCCAGATGTTCCAACTCA
rorab f: AGCATTGGGCTGTGATGATCTT 241 82.8 96.5 ENSDARG00000001910
r: ACAGACAAGCTTAGTTAGAATTCCCTC
nr1d1 f: GAAGGCTGGAACATTTGAGGTC 228 83.3 104.2 ENSDARG00000033160
r: GCAGACACCAGGACGACCG
nr1d2a f: CATGTCAAGAGACGCCGTGC 478 87.0 96.1 ENSDARG00000003820
r: GGGACAAACCAGATGTGCTCG
nr1d2b f: GCACCTGGTCTGCCCGA 207 83.8 100.5 ENSDARG00000009594
r: CGGACCACCAGCACCTCA
clock1a f: GGTTCAAGGACAGGGTTTACAGATG 280 87.3 100.0 ENSDARG00000011703
r: GGTCGACCTCTGAGACTGCTGG
clock1b f: GAGAGTACAGGGACCTCAGATGATC 268 85.6 96.1 ENSDARG00000003631
r: ATACACAGGACCGCACTGAGTTAC
Chapter 3
86
Table 3.1 (continuation)
Ensembl
Gene
symbol
f/r Primer 5'-3' sequence Product
Size (bp)
Tm
(ºC)
E Ensembl Gene ID
Core circadian genes (continuation)
bmal1a f: GTCACAGACAAGTGCTACAGATGCG 261 82.1 102.5 ENSDARG00000006791
r: TCCCTCCGCCATCTCCTGA
bmal1b f: TGACGGCTCAGGGAAAACC 305 86.1 99.3 ENSDARG00000035732
r: GAGAATTGTCACTTAAAATGGAGCTG
cry1b f: CTACAGGAAGGTAAAGAAGAACAGCA 340 85.3 92.6 ENSDARG00000011583
r: CAACAACTCCTCAAACACCTTCAT
cry1a f: CTACAGGAAGGTCAAAAAGAACAGC 334 87.1 99.1 ENSDARG00000045768
r: CTCCTCGAACACCTTCATGCC
cry2a f: GGACCAATACACCAGCACCAG 245 83.6 99.7 ENSDARG00000069074
r: CAGCAAGTGTCCTGCCATGTC
cry2b f: ATCGTCTTATACAGGGGTCAGGAG 287 87.3 98.9 ENSDARG00000091131
r: CTTCCCGCCTCTCGTTGTC
Myogenic regulatory factors
myoD f: CGTCCACCAACCCGAACC 270 82.8 102.9 ENSDARG00000030110
r: TCCGTGCGTCAGCATTTGG
myog f: ACATACTGGGGTGTCGTCCTCTA 209 86.5 97.92 ENSDARG00000009438
r: CCACTGGAGTCGCCTCTGTT
myf5 f: CAGAGAGCATGGTTGACTGCAAC 243 83.3 96.44 ENSDARG00000007277
r: TTGGACTGTCTGGAGAACTGCAC
myf6 f: CAACGAAGCTTTTGACGCG 291 83.8 92.44 ENSDARG00000029830
r: AACACGGCTCCTTCTCTATGACC
Chapter 3
87
3.4. Results
3.4.1. Feeding behaviour
Fish continued to eat during the experiment, but showed a marked change in feeding
behaviour between C2 and C3, resulting in a decoupling of feeding activity from the light:
dark cycle of the acclimation period. Gut food content (% body mass) was ~1.5 at
C2:ZT02, increased to ~3.7 at C2:ZT10 and then declined to 0.8 at C2:ZT22. The food
content of the gut only showed modest increase to ~1.4 during what would have been the
light period of C3, declining to ~0.3 at C4:ZT02, indicating a marked reduction of foraging
behaviour (Figure 3.2A). In the control experiment, a very similar pattern was observed
with an increase of ~2-fold in gut food content from ZT02 (1.1%) to ZT14 (2.1%) under a
12:12h light: dark photoperiod (Figure 3.2A). No clear pattern was observed for condition
factor among the time-points over the experiment (Figure 3.2B).
3.4.2. Non-circadian gene expression in skeletal muscle
25 out of 32 of the non-clock genes screened showed no evidence for circadian patterns of
expression (sae1, odc1, hsp90a.2, klf11b, foxo1a, fkbp5, cited2, bbc3, znf653 MAFbx, myf5,
myoD, myogenin, igf1a, igf2a, igf2b, igf1ra, igf1rb, igf2r, igfbp1a, igfbp1b, igfbp2a , igfbp2b,
igfbp5a, and igfbp6b) (Figure 3.3). In addition, trim63, hsp90a.1, and igfbp6a passed the
screening criteria, but failed to show strong evidence for circadian expression based on
the individual reactions (adjusted-r2 lower than 0.3 and FDR higher than 0.07). Cry1b was
the only zebrafish paralogue of a core-clock gene that had a non-circadian pattern of
expression (Figure 3.3).
The transcription levels of some genes were significantly correlated with the food
content in the gut. Transcripts of igf1rb, MAFbx, bbc3, igf1ra, igfbp5a, and igf2b were
negatively correlated (Spearman’s correlation < -0.5, P<0.05) whereas odc1, igf2a,
igfbp2b, and sae1 were positively correlated with gut food content (Spearman’s
correlation > 0.5, P<0.05).
Chapter 3
Figure 3.2 - I
over the 48h
photoperiod f
and food cont
The subjective
gray backgrou
Different lette
stands for “tim
B
A
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
In
te
st
in
e
F
o
o
d
C
o
n
te
n
t
R
e
la
tiv
e
to
B
o
d
y
M
a
ss
(%
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
C
o
n
d
it
io
n
F
a
c
to
r
(K
)
ZT
TD
Cycle
10
74 8662 78 8270 DarkLight6654 5846 5038 42
14 0202 18 2210 14020618 22
C3
1402 06
C4 ControlC2ntestine food content relative to body mass (A) and condition factor (B)
of the photoperiod experiment. Fish kept in a 12:12h light:dark
or two weeks were exposed to complete darkness and condition factor
ent was calculated for 10 fish every 4h until 86h of continuous darkness.
light and dark periods of the photoperiod are represented by white and
nd respectively. Values are mean ± s.e.m., N=10 fish per time-point.
rs represent statistically different means (P<0.05). TD and ZT in the X-axis
in continuous darkness” and “Zeitgeber time”, respectively.e88
Chapter 3
89
Figure 3.3 – legend on next page
Chapter 3
90
Figure 3.3 – Heatmap and periodicity parameters calculated for the screening reactions
of the photoperiod experiment. The upper left panel shows the gut content relative to
body mass over the 48h of the photoperiod experiment (the subjective light and dark
period of the photoperiod are represented by numbers with yellow and gray
background, respectively). TD and ZT in the X-axis stands for “time in continuous
darkness” and “Zeitgeber time”, respectively. The heatmap shows the hierarchical
clustering (McQuitty’s method) of normalized mRNA levels for each transcript over the
continuous darkness photoperiod – mean equals to zero and standard deviation equals
to 1. Shades of yellow represent upregulation and shades of cyan represent
downregulation. Each block represents the mean of duplicate qPCRs of a pool
containing cDNA from 10 fish. Some of the periodicity parameters calculated by the
ARSER algorithm are shown on the right (period window set to 20-28h). FDR stands for
false discovery rate.
Chapter 3
91
3.4.3. Expression of core clock genes in skeletal muscle
The expression of zebrafish paralogues of the positive oscillators of the circadian
mechanism (bmal1 and clock1) and the transcription activator of bmal1 (rora) followed a
circadian pattern in skeletal muscle. The 2 paralogues of bmal1 and clock1 were
expressed in phase with each other showing peak expression at ZT14 (Figure 3.4A-D).
bmal1a and bmal1b showed an 8.5-fold change in expression between maximum and
minimum values (Figure 3.4A,B). In contrast, clock1a was more responsive to the light:
dark cycle than clock1b showing a 6.0- and 2.2-fold change in expression respectively
(Figure 3.4C,D). The highest expression of the two paralogues of the rora gene (roraa and
rorab), known to activate bmal1 in mammals, occurred in a different phase from bmal1
and clock1, with an ~4.5-fold change in expression of both paralogues between maximum
(at ZT02) and minimum (Figure 3.4E,F).
With the exception of cry1b, the expression of the negative oscillators determined
in this study (cry1a, cry2a, cry2b, per1a, per1b, per2, per3, nr1d1, nr1d2a and nr1d2b)
followed a circadian pattern. Expression of cry1a gene peaked at ZT02 (~4.0-fold
upregulation) (Figure 3.5A). In contrast to the expression of cry1a, the expression of the
two paralogues of the cry2 gene (cry2a and cry2b) occurred in phase with bmal1 and
clock1, with both paralogues showing similar amplitude of expression in relation to the
photoperiod (Figure 3.5B,C).
The transcript levels of all four per genes assayed (per1a, per1b, per2, and per3)
occurred in phase with the negative oscillator cry1a. A small shift in the phase of
expression was observed among the per genes: per1b and per3 mRNA levels were at their
highest four hours later than the peak expression of per1a and per2 genes (Figure 3.5D-
G). The fold-change in transcription level of the per1a (~51.7-fold) and per3 (~23-fold)
were among the highest of all circadian genes studied (Figure 3.5D,G).
Expression of the nuclear receptors genes nr1d1, nr1d2a, and nr1d2b, which
belong to the negative loop of transcriptional regulation of the circadian rhythm in
mammals, also occurred in phase with expression of the cry1a gene (Figure 3.6A-C). Peak
expression of nr1d1 was ~47-fold higher than its lowest expression (Figure 3.6A). A
relatively weak, but significant, negative correlation was found between the expression of
this gene and food gut content (R=-0.56, P=0.040). The maximum change in expression of
nr1d2a (~7.3-fold) was significantly higher than for nr1d2b (~2.3-fold) (Figure 3.6B,C).
Chapter 3
92
Figure 3.4 - Expression profile of zebrafish orthologues of genes known to be positive
regulators of the circadian pathway in mammals. The subjective light and dark periods of
the photoperiod are represented by white and gray background respectively. Transcript
levels of the paralogues (A) bmal1a, (B) bmal1b, (C) clock1a, and (D) clock1b were highest
during the beginning of the subjective nigh period. Conversely, transcription of the (E)
roraa and (F) rorab paralogues was highest during the subjective light phase. Values are
mean ± s.e.m., N=10 fish per time-point. Different letters represent statistically different
means (P<0.05). TD and ZT in the X-axis stands for “time in continuous darkness” and
“Zeitgeber time”, respectively. The dashed lines represent the intestine food content.
A B
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Figure 3.5 – legend on next page.
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94
Figure 3.5 - Expression profile of zebrafish orthologues of genes known to be negative
regulators of the circadian pathway in mammals. The subjective light and dark periods of
the photoperiod are represented by white and gray background respectively. At the
beginning of the subjective dark phase of the photoperiod the expression of (A) cry1a was
at its lowest while expression of (B) cry2a, (C) cry2b was at its highest. Expression of the
per genes was very similar, with (D) per1a and (F) per2 highest expression occurring four
hours earlier than expression of (E) per1b and (G) per3. Values are mean ± s.e.m., N=10
fish per time-point. Different letters represent statistically different means (P<0.05). TD
and ZT in the X-axis stands for “time in continuous darkness” and “Zeitgeber time”,
respectively. The dashed lines represent the intestine food content.
Chapter 3
95
Figure 3.6 - Expression profile of zebrafish orthologues of the nuclear receptor subfamily
D, known to be negative regulators of the circadian pathway in mammals. The subjective
light and dark periods of the photoperiod are represented by white and gray background
respectively. Expression of (A) nr1d1, (B) nr1d2a, and (C) nrd1d2b occurred in phase with
one another, but the nr1d2a paralogue seems to be more responsive to changes in
photoperiod than the nr1d2b paralogue. Values are mean ± s.e.m., N=10 fish per time-
point. Different letters represent statistically different means (P<0.05). TD and ZT in the
X-axis stands for “time in continuous darkness” and “Zeitgeber time”, respectively. The
dashed lines represent the intestine food content.
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96
3.4.4. Putative clock-controlled genes
Expression of two IGF-binding proteins (igfbp3 and igfbp5b) and one myogenic regulatory
factor (myf6) occurred in phase with the paralogues of the positive oscillators bmal1 and
clock1, with an average of ~2.0-fold regulation (Figure 3.7A-C). Expression of the heat
shock transcription factor 2 gene (hsf2) occurred in phase with cry1a and other genes that
belong to the negative arm of the transcriptional regulation network of the circadian
rhythm (Figure 3.7D). Transcripts of this gene were ~7.0-fold higher at ZT02 than ZT14
(Figure 3.7D).
3.4.5. Expression of circadian genes and CCGs under 12: 12h light: dark photoperiod
The pattern of gene expression in skeletal muscle under a normal photoperiod was
similar to the one observed under a continuous darkness condition (Spearman’s
correlation coefficient = 0.699, P<0.001). However, the amplitude of expression between
the light and dark periods was higher in skeletal muscle subjected to a normal
photoperiod when compared to the continuous darkness expression (Figure 3.8).
3.4.6. Gene clustering and correlation analysis
The 20 genes found to have a circadian rhythm of expression could be grouped in two
major clusters (Figure 3.9). Cluster I comprises genes with peak expression around the
middle of the subjective dark photoperiod and included bmal1a, bmal1b, cry2a, clock1b,
myf6, clock1a, cry2b, igfbp3, and igfbp5 (Figure 3.9). Transcript level of paralogue genes
in this cluster were highly positively correlated, the two paralogues of the bmal1 gene
had the highest correlation coefficient (R=0.92, P<0.001), followed by the paralogues for
the clock gene (R=0.84, P<0.001) and lowest correlation was found for the two
paralogues of the cry2 gene (R=0.76, P=0.002) (Table 3.2). Genes with peak expression
during the last time-point of the subjective dark photoperiod and the two time-points
from the subjective light photoperiod were grouped in cluster II (cry1a, hsf2, per1b,
per3, nr1d2b, roraa, rorab, nr1d1, per1a, per2, nr1d2a) (Figure 3.9). In this cluster, only
the paralogues of the rora gene had highly significant positive correlation in mRNA
levels (R=0.79, P=0.001) (Table 3.2). Weak, but statistically significant, negative
correlations were found between gut food content and transcription level of per1a (R=-
Chapter 3
0.57, P=0.040) and nr1d1 (R=-0.56, P=0.040). No significant positive correlation was
found between the expression of circadian genes and gut food content.
Figure 3.7 - Expression profile of putati e zebrafish clock-controlled genes. The
subjective light and dark periods of the photoperiod are represented by white and gray
background respectively. Expression of (A) igfbp3, (B) igfbp5b, and (C) myf6 occurred in
phase with one another and with known positive oscillators of the circadian rhythm
Expression of (D) hsf2 was at its highest at the beginning of the light phase of the
photoperiod, in phase with known negative oscillators of the circadian rhythm. Values
are mean ± s.e.m., N=10 fish per time-point. Different letters represent statistically
different means (P<0.05). TD and ZT in the X-axis stands for “time in continuous
darkness” and “Zeitgeber time”, respectively The dashed lines represent the intestine
A B
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Figure 3.8 – Comparison gene expression during continuous darkness and 12: 12h
light: dark photoperiods. AM and PM refers to ZT02 (two hours after lights on) and
ZT14 (two hours after lights off), respectively. Results of intestine content from the
C2ZT02 and C2ZT14 from the continuous darkness were compared to the two time-
points of the control experiment (A) (N=10 per time-point per experiment). The results
of gene expression from the time-points 38, 62 and 86h of darkness were averaged and
considered as the result of ZT02 (AM) of the continuous darkness experiment (N=30)
whereas the averaged results of time-points 50 and 74h of darkness were considered
the ZT14 (PM) (N=20) and compared to the two time-points of the control experiment
(N=10 per time-point). Columns and error bars represent average and s.e.m.,
respectively. The pattern of gene expression in skeletal muscle under a normal
photoperiod was similar to the one observed under a continuous darkness condition
(Spearman’s correlation coefficient=0.699, P<0.001)
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.)
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per1b
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myog
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hsp90a.2
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murf1
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AM PM
Non-circadian / Non-CCGs
Negative Oscillators
CCGs
Positive Oscillators
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Figure 3.9 – Heatmap and periodicity parameters calculated for the individual reactions
of the photoperiod experiment. The upper left panel shows the gut content relative to
body mass over the 48h of the photoperiod experiment (the subjective light photoperiod
are represented by numbers with yellow background and the dark photoperiod by gray
background). TD and ZT in the X-axis stands for “time in continuous darkness” and
“Zeitgeber time”, respectively. Expression of genes that passed the screening step was
quantified by qPCR for each individual fish in relation to the photoperiod. The heatmap
shows the hierarchical clustering (McQuitty’s method) of normalized mRNA levels for
each transcript over the complete darkness photoperiod – mean equals to zero and
standard deviation equals to 1. Shades of yellow represent upregulation and shades of
cyan represent downregulation. Each block represents the mean of mRNA level of 10 fish
quantified by qPCR. Some of the periodicity parameters calculated by the ARSER
algorithm are shown on the right (period window set to 20-28h). FDR stands for false
discovery rate.
Chapter 3
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Table 3.2 – Significant positive and negative Spearman’s correlation of gene expression
over the photoperiod experiment. Only correlations higher than 0.75 are shown.
Positive Correlations Negative Correlations
Genes
Spearman's
Correlation p-value
Genes
Spearman's
Correlation p-value
bmal1a clock1b 0.96 0.000 bmal1b per1b -0.94 0.000
bmal1a cry2a 0.96 0.000 clock1a per3 -0.92 0.000
bmal1b cry2a 0.96 0.000 bmal1a per2 -0.90 0.000
bmal1b clock1b 0.95 0.000 hsf2 bmal1b -0.90 0.000
clock1b cry2a 0.94 0.000 clock1b per1b -0.90 0.000
clock1a bmal1b 0.92 0.000 clock1a per1b -0.90 0.000
bmal1a bmal1b 0.92 0.000 bmal1a per1b -0.89 0.000
hsf2 per1b 0.91 0.000 bmal1a hsf2 -0.89 0.000
hsp90a.1 rorab 0.90 0.000 bmal1a per1a -0.88 0.000
per3 per1b 0.90 0.000 cry2b per3 -0.88 0.000
bmal1a myf6 0.89 0.000 cry2a per1b -0.88 0.000
hsf2 per1a 0.88 0.000 igf2a nr1d2a -0.87 0.000
cry2b clock1a 0.87 0.000 per2 cry2a -0.87 0.000
cry2a myf6 0.86 0.000 hsf2 cry2a -0.87 0.000
per1a per2 0.85 0.000 clock1b per2 -0.87 0.000
clock1a cry2a 0.85 0.000 hsf2 clock1b -0.85 0.000
clock1b myf6 0.85 0.000 cry2b per1b -0.85 0.000
clock1a clock1b 0.84 0.000 per1a clock1b -0.84 0.000
per1a nr1d1 0.84 0.000 bmal1b per2 -0.84 0.000
cry2b bmal1b 0.84 0.000 clock1a cry1a -0.83 0.000
per3 rorab 0.84 0.000 per3 bmal1b -0.83 0.000
hsp90a.1 per3 0.82 0.001 per1a cry2a -0.81 0.001
bmal1b myf6 0.82 0.001 per1a myf6 -0.81 0.001
hsp90a.1 cry1a 0.82 0.001 hsp90a.1 clock1a -0.80 0.001
cry1a per2 0.81 0.001 per1b myf6 -0.80 0.001
per2 per1b 0.81 0.001 bmal1b cry1a -0.80 0.001
hsf2 per2 0.81 0.001 clock1a rorab -0.79 0.001
rorab roraa 0.80 0.001 cry2b hsf2 -0.78 0.002
per3 cry1a 0.80 0.001 cry1a cry2a -0.78 0.002
bmal1a clock1a 0.79 0.001 per1a bmal1b -0.76 0.002
igf1a hsp90a.1 0.79 0.001 per3 clock1b -0.76 0.002
cry1a per1b 0.78 0.002 hsf2 myf6 -0.76 0.002
hsf2 per3 0.77 0.002 nr1d1 roraa -0.76 0.002
cry2b cry2a 0.76 0.002 cry2b hsp90a.1 -0.76 0.003
igfbp3 clock1a 0.76 0.002 per2 myf6 -0.76 0.003
igf2a roraa 0.76 0.003 hsf2 clock1a -0.76 0.003
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3.5. Discussion
Danios show an endogenous circadian nocturnal feeding behaviour when under a 12: 12h
light: dark photoperiod (del Pozo et al., 2011). In the present study, however, continuous
darkness led to an inhibition of the feeding response by the third subjective light cycle, as
evidenced by direct observation of the food present in the gut, enabling the
transcriptional responses due to feeding and circadian rhythmicity to be distinguished.
Feeding activity in teleosts initiates well characterised transcriptional responses (Rescan
et al., 2007; Bower et al., 2008; Amaral and Johnston, 2011). Transcripts for the ubiquitin
ligase MAFbx, insulin-like growth factor-1 receptors (igf1ra, igf1rb) and the mitochondrial
pro-apoptotic BCL2 binding protein component 3 (bbc3) were inversely correlated with
gut food content (Figure 3.3) as previously reported (Amaral and Johnston, 2011). In
contrast, transcripts for ornithine decarboxylase (odc1) and sumo-activating enzyme
(sae1), previously shown to be positively correlated with gut food content (Amaral and
Johnston, 2011), had peak expression during the subjective light phase of the 2nd diurnal
cycle and reduced expression throughout the whole of the 3rd diurnal cycle (Figure 3.3).
3.5.1. Expression of core-clock genes in zebrafish skeletal muscle
Bmal1 and clock are considered the central oscillators of the circadian mechanism due
to their ability to bind to E-box elements and activate the transcription of most of the
core-clock genes (Figure 3.10). In zebrafish skeletal muscle the expression of the
respective paralogues of the two positive oscillators (bmal1a, bmal1b, clock1a and
clock1b) clustered together (Figure 3.9) and were highly correlated (Table 3.2). The
results of the present study are very similar to the expression pattern described in
organs that are considered central pacemakers of the zebrafish clock mechanism
(Whitmore et al., 1998; Cermakian et al., 2000).
Period proteins (per 1, 2 and 3) together with the cryptochrome proteins 1 and 2
are responsible for the negative loop of the circadian mechanism (Vatine et al., 2011). In
addition, period proteins have been shown to be important for maintaining the pace of
the clock machinery (Hastings et al., 2007; Vatine et al., 2009). Among the period genes
assayed in cultured zebrafish cells only per2 expression was inducible by light (Tamai et
al., 2007) (Figure 3.10). In skeletal muscle of the zebrafish per1a and per2 showed peak
expression at the end of the subjective dark period (ZT22) whereas Per1b and Per3
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showed highest expression at the start of the light period (ZT02) (Figure 5D-G).
Interestingly, expression of per3 in the zebrafish skeletal muscle was similar to that
found in Z3 zebrafish cells (Pando et al., 2001) and in the retina and optic tectum of the
nocturnal flatfish Solea senegalensis (Martín-Robles et al., 2011), with highest
expression at around ZT02 (Figure 5G). The observation that diurnal and nocturnal fish
have the same pattern of expression in central and peripheral tissues might be valuable
in investigating its function.
The paralogues of both cry1 and cry2 have been demonstrated to inhibit bmal:
clock-directed transcriptional activation (Vatine et al., 2011). Cry1a is considered to act
on the core clock machinery and was the only transcript from the cryptochrome genes
whose expression was induced by light in zebrafish cell cultures (Tamai et al., 2007)
(Figure 3.10). The expression of cry1a, cry2a and cry2b in skeletal muscle (Figure 5A-C)
were similar to that described in the eye and brain of the zebrafish (Kobayashi et al.,
2000), considered central organs of the circadian mechanism. The difference in phase of
expression of cry1a and paralogues of the cry2 in the muscle were as previously
described in the eye and brain (Kobayashi et al., 2000), with peak expression of cry1a
occurring at ZT02 and cry2 paralogues at ZT14. Expression of cry1b in the muscle
(Figure 3.3), however, did not follow the circadian pattern described for the central
organs (Kobayashi et al., 2000). Furthermore, cry2 genes in zebrafish (Figure 5B,C) and
mouse muscle are expressed in anti-phase (McCarthy et al., 2007). In the current model
of the circadian clock in the zebrafish cry1 and cry2 proteins forms hetero-dimers that
translocate to the nucleus where they inhibit the bmal:clock-dependent transcriptional
activation (Vatine et al., 2011). In the skeletal muscle, however, the cry1b might not be
part of the pool of cry proteins available to form dimers with per proteins (Figure 3.10).
The nr1d1, nr1d2 and ror genes code for nuclear receptors involved in the
stabilizing loop of the circadian clock mechanism (Emery and Reppert, 2004; Vatine et
al., 2011) (Figure 3.10). The rev-erbɑ and β receptors, coded by the zebrafish nr1d1 and
nr1d2 respectively, are considered constitutive transcriptional repressors of bmal1
whereas ror genes are transcriptional activators of bmal1 (Guillaumond et al., 2005)
(Figure 3.10). In addition, nr1d1 has been recently suggested to act as a transcriptional
repressor for the bmal1 partner, clock (Crumbley and Burris, 2011), regulating the
transcription of both positive main oscillators of the circadian mechanism (Figure 3.10).
In zebrafish skeletal muscle, the expression of nr1d2 and rora clustered together with
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cry1a (Figure 3.9). However, nr1d1, nr2d2a and nr2d2b transcripts levels peaked at the
end of the subjective dark period (ZT22) while transcripts of roraa and rorab were at
their highest levels at the beginning of the subjective light period (ZT02-04) (Figure
3.9). This small difference in phase of expression of the two components of the
stabilizing loop might reflect their tight control of regulation over the circadian
mechanism which is reflected in the activation/repression of bmal1 and clock1
expression. In addition to their role in regulation of circadian rhythm, these genes are
known transcription factors for genes involved in lipid metabolism (Duez and Staels,
2008). In the present study, a negative correlation was found between expression of
nr1d1 in skeletal muscle and gut food content in accordance with previous findings
(Amaral and Johnston, 2011). It is plausible that nrld1 may play a role in integrating
circadian and metabolic rhythms in skeletal muscle.
3.5.2. Expression of putative clock-controlled genes in zebrafish skeletal muscle
In the zebrafish, the insulin-like growth factor pathway is comprised of four ligands
(igf1a, igf1b, igf2a and igf2b), their respective receptors (igf1ar, igf1br and igf2r) and nine
igf-binding proteins (igfbp1a, igfbp1b, igfbp2a, igfbp2b, igfbp3, igfbp5a, igfbp5b, igfbp6a
and igfbp6b). Interaction between the ligands and igf1-receptors ultimately leads to
tissue growth, with the binding proteins playing important roles in regulating the
concentration of the ligands in the plasma and their release in target tissues. A previous
work has shown that igf1a and igf2b are upregulated during feeding while igf1ra, igf1rb,
igfbp1a and igfbp1b are upregulated during fasting (Amaral and Johnston, 2011). In the
present study, expression of two insulin-like growth factor binding proteins genes (igfbp3
and igfbp5b) was rhythmic and peaked at the onset of the dark phase (ZT14), in phase
with the positive oscillators bmal1 and clock1 (Figure 3.9). Changes in mRNA expression
have been shown to be propagated to the protein level in hundreds of genes in another
teleost, Fundulus heteroclitus (Rees et al., 2011). Thus, large changes in transcript levels
are likely to be reflected in protein levels with effects on biological functions. Over-
expression, knockdown and knockout systems have been previously employed to study
the biological importance of the igf-binding proteins in skeletal muscle [reviewd in (Duan
et al., 2010)]. Most circulating IGF in the plasma is found to be conjugated to igfbp3, and
this binding protein serves as a modulator of the IGF action in target tissues by prolonging
hormone half-life (Firth and Baxter, 2002; Yamada and Lee, 2009). Igfbp3 also has IGF-
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independent actions in inhibiting cell proliferation in cancer lines (Yamada and Lee,
2009). Igfbp5 is known to play a crucial role in muscle growth and differentiation
[reviewed in (Duan et al., 2010)] and circadian expression of this growth-related gene has
been previously reported in the skeletal muscle of mouse (Miller et al., 2007). Given the
importance of igfbp3 and igfbp5 in the growth axis and the involvement of the clock
pathway in the cell cycle a plausible hypothesis is that the cyclic expression of these two
IGF binding proteins is related to the local regulation of cell-cycle and growth.
Myogenic regulatory factors (myoD, myf5, myf6 and myogenin) (MRFs) are a class
of helix-loop-helix transcription factors that play a pivotal role in myogenesis (Hinits et
al., 2007; Chen and Tsai, 2008; Chong et al., 2009). Myf6 (also known as MRF4) was shown
to function in myogenic determination and differentiation in myf5:myoD double knockout
mouse (Kassar-Duchossoy et al., 2004). Myf6 was found to play an important role in
muscle fibre alignment in zebrafish embryos, using the morpholino technique to
knockdown two splice-variants of myf6 transcripts (Wang et al., 2008). In the present
study, the expression of myf6 was not correlated with food intake in C3, but it did exhibit
a circadian expression pattern peaking in phase with bmal1 and clock1 at the beginning of
the subjective dark period (Figure 3.7C). Similar circadian patterns of myf6 expression
were reported previously in skeletal muscle of the horse, a mammalian species with
higher physical activity during daylight hours (Martin et al., 2010). In the mouse, myoD is
a direct target of clock and bmal, which bind in a rhythmic fashion to the core enhancer in
the myoD promoter (McCarthy et al., 2007; Andrews et al., 2010). ClockΔ19 and Bmal1-/-
mutants showed similar phenotypes to myoD-/- mutants with reduced force generating
capacity relative to wild-types due to a disruption of myofilament organisation (Andrews
et al., 2010). In contrast, no evidence was found for circadian expression of myoD in
zebrafish (Figure 3.3). It is plausible that the well-known redundancy of MRFs may have
resulted in lineage-specific differences in their regulation by clock genes. A plausible
hypothesis would be that the rhythmic expression of myf6 in zebrafish muscle parallels
that described for myoD in mouse muscle, with potential effects on the maintenance of
myofibrillar structure.
The rhythmic expression of the chaperone transcriptional regulator hsf2 was
previously described in the pineal tissue of chicken (Hatori et al., 2011) and zebrafish
larvae (Weger et al., 2011). The expression of two chaperone genes (hsp90a.1 and
hsp90a.2) in zebrafish skeletal muscle showed no discernible pattern of periodicity with
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respect to photoperiod, while expression of hsf2 was rhythmic and peaked at onset of
lights on, in phase with the negative oscillator cry1a (Figures 3.3 and 7D). The role of hsf2
as a clock-controlled gene in the circadian output is not known, but evidence from
experiments with chicken point to the activation of specific stress-response factors in
response to light (Hatori et al., 2011). In zebrafish larvae expression of hsf2 was
concomitant with expression of genes involved in the response of oxidative stress and
chaperone genes (Weger et al., 2011). Exposure to light is known to cause oxidative stress
through production of hydrogen peroxide in zebrafish cells (Hirayama et al., 2007;
Hirayama et al., 2009) with subsequent activation of stress-responsive genes, including
the (6-4) pyrimidine-pyrimidone dimer DNA photolyase involved in DNA repair
(Hirayama et al., 2009). The production of hydrogen peroxide and subsequent activation
of stress-responsive genes and the MAPK signalling pathway has recently been
considered one of the potential mechanisms that render peripheral tissues to be
photoreceptive and photoresponsive, since these events regulate transcription of cry1a in
the zebrafish with noticeable effects on the circadian mechanism (Hirayama et al., 2007;
Hirayama et al., 2009; Vatine et al., 2011).
In the present chapter the expression of the main oscillators of the clock
mechanism in the skeletal muscle of the zebrafish was characterized (Figure 3.10). Most
of these genes had a similar expression pattern to that described for the central organs
(retina and brain) of the circadian mechanism [reviewed in (Vatine et al., 2011)]. In
addition, evidence is provided that differences exist in the responsiveness of clock1 and
nr1d2 paralogues to circadian stimuli and the loss of a circadian rhythm for cry1b in
skeletal muscle. Finally, gene expression of two igf-binding proteins (igfbp3 and igfbp5b)
and a myogenic regulatory factor (myf6) involved in IGF-mediated growth and terminal
muscle differentiation in fish, respectively, were identified as clock-controlled gene in
zebrafish skeletal muscle. This finding points to an important physiological role of the
clock mechanism in regulating muscle mass homeostasis through integration with the IGF
pathway and MRFs. These studies provide a foundation for investigating the integration
of the clock system with physiological processes in teleosts. In addition, the finding that
the circadian expression of many genes in this peripheral tissue is similar to those
described for organs considered central photoreceptive and pacemakers of the circadian
mechanism is valuable for future investigations on the hierarchy of the systemic clock, i.e.,
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the integration between the neuroendocrine signals from the pineal, the central
pacemaker organ, and peripheral clocks in fish.
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F
ig
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Figure 3.10. Diagram of the molecular circadian mechanism in the zebrafish. Bmal and
clock genes are considered the central oscillators of this pathway due to their ability to
modulate the expression of the remaining components through a transcription-
translation regulation mechanism. In the zebrafish bmal1a, bmal1b, bmal2, clock1a,
clock1b and clock2 form heterodimers in the nucleus and activate the expression of
period (per) and cryptochrome (cry) genes. The expression of bmal1a, bmal1b, clock1a
and clock1b were highly correlated in skeletal muscle and occurred in phase with each
other. From the four cry genes investigated in this study, only cry1b did not follow a
circadian expression. Per and cry proteins are components of the negative arm of the
circadian pathway due to their ability to form dimers in the cytoplasm, translocate to the
nucleus and represses the activation of expression by bmal: clock heterodimers. In
mammals, after translocation to the nucleus the cry protein dissociates from the cry: per
complex and directly represses the expression of clock. The expression of the negative
oscillators per and cry in skeletal muscle of the zebrafish followed a circadian pattern that
is very similar to the one described for organs considered master regulators of the
circadian rhythm (retina and brain). Similarly, the expression of roraa, rorab, nr1d1,
nr1d2a and nr1d2b followed a circadian rhythm of expression in zebrafish skeletal
muscle. In the present experiment, the circadian expression in response to the
photoperiod from the gene expression was distinguished from expression due to
rhythmic feeding. This diagram was produced based on the recent review on the zebrafish
clock mechanism (Vatine et al., 2011), on the information on the circadian pathway for
mammals from Applied Biosystems
(http://www5.appliedbiosystems.com/tools/pathway/), and on the results of the present
study.
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4. Experimental selection of zebrafish for body size at age: effects on
early-life history traits and gene expression in skeletal muscle
4.1. Summary
In the present study the short generation time of the zebrafish (Danio rerio) was
exploited to investigate the effects of selection for body size at age on early life-history
traits and on the transcriptional response to a growth stimulus in skeletal muscle of
adult fish. A wild-derived population of zebrafish was subjected to four rounds of
artificial selection to produce fish divergently selected for small (S-lineage) and large
body size (L-lineage) at 90 days post-fertilization. A third lineage was produced in
which fish were not selected (U-lineage). Standard length and body mass of fish from
the L-lineage was 5.1 and 15.7% higher than fish from the U-lineage and 12.3 and 41.9%
higher than fish from the S-lineage. Egg volume from the S-lineage was 5.9% smaller
with 4.5% less yolk than the other lineages. The levels of a limited number of maternal
transcripts in the 2-4 cell stage embryos were affected by the artificial selection. For
example, eggs from the L-lineage showed higher transcript levels for igf1b, igf2a, GH-
receptors, igf1ar and igf2r. Larvae from the L-lineage were significantly larger, but
survivorship at the end of the first month was not affected by the selection regimen. The
pattern of expression of 11 nutritionally-responsive genes and 8 genes from the insulin-
like growth factor pathway was similar in skeletal muscle of adult fish from S- and L-
lineages in response to fasting and refeeding. However, 9 (igf1a, igf2a, igf1ar igf1br,
igf2r, igfbp1a, igfbp1b, klf11b and myod) of the 32 genes studied showed a significantly
different response to either fasting or refeeding between the S- and L-lineages. This
difference in expression could not be explained by different levels of acquired
nutritional energy since the two lineages showed a very similar feed intake. The change
in expression also seems to be directional according to the observed phenotype. For
example, fish from the L-lineage showed higher expression of igf1a (constitutive
expression) and igf1 receptors (mainly during satiation periods) whereas fish from the
S-lineage showed higher constitutive expression of igbp1a/b transcripts.
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4.2. Introduction
Somatic growth is a very complex trait since it involves all metabolic pathways that
control energy acquisition (food ingestion) and energy expenditure (food assimilation,
locomotion, reproduction, and maintenance of the existing body mass). Endocrine
pathways play a crucial role in orchestrating the energy utilization in these different
biological processes. Thus, inheritable variations in the gene and regulatory sequence of
genes of endocrine pathways are good candidates for explaining differences in growth
trajectory within and between populations. Experimental selection of model organisms
like C. elegans, Drosophila and mice has been proved a valuable tool for the investigation
of molecular mechanisms underlying changes in phenotype (e.g. thermal tolerance,
body composition and longevity). For example, body fat and growth rate of mice have
been correlated to leptin and growth hormone (GH) genes using lineages divergently
selected for voluntary locomotor activity (Girard et al., 2007) and body composition
(Bunger and Hill, 1999), respectively.
In fish, experimental selection has been mainly used to investigate the effects of
domestication on behaviour and growth, the latter being an important consideration in
commercial fish culture. For example, after 16 generations of selection for rapid growth,
domesticated coho salmon (Oncorhynchus kisutch) grew faster than unselected strains
with satiation feeding, possibly due to the higher feed intake and feed conversion
efficiency (Neely et al., 2008). However, changes in phenotype due to high experimental
selection pressure can occur rather faster as evidenced by a change in behaviour after
four generations of selection for growth rate in Atlantic silverside (Menidia menidia),
when a higher feed intake was recorded for the selected lineage (Lankford et al., 2001;
Chiba et al., 2007). More recently, experimental selection has been used as a tool to
investigate the molecular mechanisms underlying the physiological changes leading to
different phenotypes of selected lines. In many cases, the GH-IGF pathway is
investigated as the main underlying endocrine mechanism of differences in growth
observed between selected lineages due to the direct and indirect anabolic effects of GH.
The indirect effects of GH are mainly realised by the IGF pathway, in which igf1 and igf2
are the ligands. Binding of the IGF ligands to igf1r leads to phosphorylation of the
PI3K/AKT/mTOR pathway which is responsible for the activation of expression of
growth-related genes and repression of transcription of genes that function in protein
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111
degradation, resulting in the anabolic effects of IGF (Rommel et al., 2001). However,
binding of IGFs to igf2r results in lysosomal degradation of the ligand and is probably a
mechanism of regulating the concentration of circulating IGFs (Lau et al., 1994; Wang et
al., 1994). The availability of circulating IGFs and its binding to the respective receptors
is also regulated by the IGF-binding proteins (IGFBPs) (Wood et al., 2005a). Thus,
changes in the GH-IGF axis might explain some of the effects of domestication observed
in selective breeding programs in fish culture. For example, channel catfish (Ictalurus
punctatus) selected for fast growth for two generations had lower plasma cortisol levels
and higher muscle igf2 mRNA than fish selected for slow growth, leading to the
conclusion that the differences in growth were partially explained by the GH-IGF and
stress axis (Peterson et al., 2008). A microarray experiment comparing wild-type coho
salmon with a GH-transgenic and domesticated fish (12 generations) found that
transcriptional responses were similar in the two latter strains compared to the wild-
type fish, leading to the hypothesis that domestication affected similar downstream
components as in GH-transgenic fish (Devlin et al., 2009). Changes in the components of
the GH-IGF axis can also explain decreased growth phenotypes. For example, the
investigation of the transcriptional responses to fasting and feeding in five dwarf
populations compared to two generalist populations of Arctic charr (Salvelinus alpinus)
reported a higher expression of igfbp4 and lower expression of mTOR and 4e-bp-1 (two
proteins that regulate protein synthesis) in the dwarf populations, leading to the
conclusion that parallel adaptive changes in gene expression occurred in the dwarf
populations (Macqueen et al., 2011).
The zebrafish (Danio rerio) is an excellent model for experimental selection due
to its short generation time, available knowledge on its development and physiology,
and extensive available molecular tools. In addition, the transcriptional regulation of the
IGF system in skeletal muscle have been recently characterized in the zebrafish (Amaral
and Johnston, 2011). The aims of this chapter were to produce zebrafish lineages
artificially selected for divergent body size and to investigate the effect of the
experimental selection on some early life-history traits of embryo and larval stages. In
addition, the hypothesis that the transcriptional regulation in skeletal muscle in
response to a growth stimulus differs between zebrafish lineages selected for divergent
body size was tested. To this end expression levels of transcripts from the IGF axis,
Chapter 4
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nutritionally-responsive genes and myogenic regulatory factors was investigated in
adult fish from the artificially selected lineages in response to fasting and refeeding.
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113
4.3. Materials and methods
4.3.1. Fish husbandry and artificial selection for body size
The study was conducted on the F3 generation of wild-caught zebrafish (Danio rerio,
Hamilton) from Mymensingh, Bangladesh (27 males and 28 females). Fish were reared
in 10L tanks at 27oC ± 0.3oC (range) under a 12h light: 12h dark photoperiodic regime
in a filtered freshwater recirculation system and fed to satiation twice daily with
bloodworms. Replicated unselected (U), small (S) and large (L) lineages were bred from
a random selection of 18-19 fish per lineage (sex ratio ~1 female: 1 male) derived from
the founder population (Table 4.1). All breeding was conducted at ~120 days post-
fertilization (dpf) when fish were sexually mature. Briefly, for each lineage previously
separated, male and female fish were introduced into a breeding tank and eggs were
collected each morning for 3 days. Eggs were immediately cleaned and maintained in
glass tanks (1L) under the same environmental conditions as the main recirculation
system. After 7dpf the larva were fed ZM-100 (Fish Food Ltd., Hampshire, UK) and
microworms. 50% of the water was changed twice daily until 30dpf, when fish were
transferred to the main recirculation system and fed to satiation with ZM-200 (Fish
Food, Hampshire, UK) and bloodworms (Ocean Nutrition™, Belgium) twice daily. Three
rounds of artificial selection were conducted based on body size at ~90dpf (see Table
4.1). For the S-lineage, fish with standard lengths (SL) (tip of snout to last vertebrae)
greater than 75% of the mean SL for the population were removed from the breeding
population at each generation. The L-lineages were generated by removing fish with SLs
less than 125% of the mean SL for the population. A third line was produced in which
fish were not selected (U-lineage) (Figure 4.1A). The percentage of each lineage selected
for breeding in the next generation was 46-52% (L-lineage), 63-75% (S-lineage) and
100% (U-lineage) and this had little impact on the sex ratio of the populations. The
number of fish used to produce the 2nd, 3rd and 4th generations ranged from 24 to 78 per
replicated lineage (Table 4.1). As part of routine husbandry procedures SL, fork length
(FL), total length (TL), maximum body depth (H) and body mass (BM) were measured
periodically to access the growth and health of all populations in the colony.
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Table 4.1 – Number of individuals in the zebrafish populations from each generation
produced during this study. (dpf: days post-fertilization)
Lineages
Parents S-Lineage U-Lineage L-Lineage
Number of Fish 18 19 18
First Generation (G1) S1.G1 S2.G1 U1.G1 U2.G1 L1.G1 L2.G1
Age at Selection (dpf) 96 87 96 89
Number of Fish Before Selection 24 32 57 35 46 78
Fish Selected 15 22 57 35 23 36
Second Generation (G2) S1.G2 S2.G2 U1.G2 U2.G2 L1.G2 L2.G2
Age at Selection (dpf) 90 108 86 109
Number of Fish Before Selection 35 34 35 42 46 117
Fish Selected 26 24 35 42 26 55
Third Generation (G3) S1.G3 S2.G3 U1.G3 U2.G3 L1.G3 L2.G3
Age at Selection (dpf) 96 101 107 117
Number of Fish Before Selection 36 39 48 38 78 60
Fish Selected 27 26 48 38 43 31
Fourth Generation (G4) S1.G4 S2.G4 U1.G4 U2.G4 L1.G4 L2.G4
Age at Selection (dpf) 95 90 96 91
Number of Fish Before Selection 38 35 36 39 38 37
Fish Selected 38 35 36 39 38 37
Fifth Generation (G5) S1.G5 S2.G5 U1.G5 U2.G5 L1.G5 L2.G5
Age at Selection (dpf) 166 163 165 165 164 164
Number of Fish Before Selection 56 52 43 47 64 68
Fish Selected 30 30 43 47 30 30
4.3.2. Early life-history traits of zebrafish egg and larva
Embryos from the 4th generation of artificial selection were collected in the first hour
after fertilization and photographed using an AxioCam CCD camera (Zeiss, Göttingen,
Germany) and a Leica Wild M3Z stereo microscope (Leica, Heerbrugg, Switzerland) at
10x magnification. Egg and yolk size were calculated by measuring the ferret diameter
of 100 eggs and their yolk, respectively, from three different spawns from each lineage,
using ImageJ V. 1.42i software (National Institutes of Health, Bethesda, MD, USA).
Deformities in the animal pole representing developmental abnormalities were also
recorded. The embryos were then reared in glass bowls as described above until 30dpf,
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and the mortality was checked twice per day. The TL of 50 larva from each lineage was
measured at 6dpf, corresponding to the time when the yolk was almost completely
assimilated and the larvae were free swimming.
4.3.3. Quantitative PCR (qPCR) of maternal transcripts
Maternal transcript levels were measured by qPCR in the 4th generation of selection
using 12 replicates of 60 embryos per lineage using SYBR II chemistry (Stratagene, La
Jolla, CA, USA). Embryos at the 2-4 cell stage were collected at 1 h after fertilization and
snap frozen in liquid nitrogen for total RNA extraction using Tri-reagent (Sigma, St
Louis, MO, USA) and subsequent first strand cDNA synthesis using a Quantitect Reverse
Transcription Kit (Qiagen, Hilden, Germany). cDNA at 40-fold dilution were used as
working solutions. Primer pairs for the 16 known genes of the IGF system in the
zebrafish (Table 2.1) and myogenic regulatory factors (MRFs) (Table 3.1) were as
described previously. New primers were designed to amplify “fecundity genes” (bmp15
and gdf9) and their receptors (bmpr1aa, bmpr1ab, bmpr1ba, bmpr1bb, bmpr2a,
bmpr2b), and growth hormone and its receptors (ghra and ghrb) (Table 4.2). qPCR
procedures were compliant with MIQE guidelines (Bustin et al. 2009) and have been
described in detail previously (section 2.3.8). In order to establish the best
normalization strategy, the expression of 13 reference genes (Table 2.1) were analysed
across lineages using Genorm v3.5 (Vandesompele et al., 2002) with M set to <1.5. qPCR
efficiency was calculated using LinRegPCR V. 12.5 software (Heart Failure Research
Center, Amsterdam, Holland) (Table 4.2). Transcripts levels expressed in arbitrary units
were calculated using the mean efficiency of 72 reactions with posterior normalization
to the level of the two most stable reference genes (tomm20b and ef1a, M=0.129). The
specificity of each qPCR assay was validated by direct sequencing of the PCR product.
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Table 4.2 – Sequence and properties of primers used in chapter 4. Ensembl gene
symbols, forward (f) and reverse (r) primer sequences, product size, efficiency (E)
product melting temperature (Tm) and Ensembl gene ID are shown.
Ensembl
Gene
symbol
f/r Primer 5'-3' sequence Product
Size
(bp)
E Tm
(ºC)
Ensembl Gene ID
“Fecundity genes” and their receptors
bmp15 f: GCCCGGTCTGAGACTCTGC 334 103.4 84.6 ENSDARG00000037491
r: CTGAAGATCACTTGATGTTGGGAG
gdf9 f: TCAAGCAAAACAGAGAATTCTTCATG 239 104.5 83.5 ENSDARG00000003229
r: GTGATGGACGCGGAAGCTG
bmpr1aa f: TGGACTCCCTCTGCTGGTGC 224 104.0 83.5 ENSDARG00000019728
r: CAGCAGCGATAAAGCCGAGTA
bmpr1ab f: GCTCCCCCTGCTGGTTCA 222 108.1 83.5 ENSDARG00000045097
r: TCTGCAGCTATGAAGCCGAGT
bmpr1ba f: GCCGTCAAGTTCATCAGCGA 198 116.4 83.5 ENSDARG00000005600
r: TATACCTCCGGTGACGCAGC
bmpr1bb f: GAACATACTGGGCTTCATCGCA 309 100.4 87.6 ENSDARG00000031219
r: CTGATGAACTTGACAGCGAGGC
bmpr2a f: GCAAACAACAACAACAGCAATAACA 313 96.5 86.6 ENSDARG00000011941
r: CGACAGACCTGCCTCCTAGTAATG
bmpr2b f: CAGTGAGGTGGGCACGATCC 306 96.4 86.0 ENSDARG00000020057
r: AGAGAGCGCACAGCCAGGC
Growth Hormone and its receptors
gh1 f: AAAAATGATTAACGACTTTGAGGAA 116 88.7 84.1 ENSDARG00000038185
r: CTTTTCCCGTCGGCGTCT
ghra f: CTCCCAGCAGCAGAGGTTGATG 216 95.7 81.9 ENSDARG00000054771
r: GAATTCTTCTTATCTGCAGGATCGTC
ghrb f: GAAAAGGATCCAAAGAAAACTTACGG 196 96.0 78.2 ENSDARG00000007671
r: CTACAGGTGGGTCTGGAAACACAATA
Chapter 4
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4.3.4. Fasting-refeeding experiment
Fish from G5 were used to investigate the effect of the artificial selection on the
transcriptional response to nutrient levels in the skeletal muscle. Two replicates from
the S- and L-lineages were reared to adult stage in the conditions described in section
4.3.1, population densities during development were the same for all replicates (N~160
fish per tank). At 9 months of age, 50 male fish were randomly collected from each
lineage and transferred to a separate tank, where they were fed bloodworms to satiety
twice daily for two weeks (acclimation period). Food was withdrawn and, after one
week of fasting, feeding was resumed. 6 fish from each lineage were collected at -170h
(just before the fasting period), 0h (just before refeeding the fish), 1, 3, 6, 24 and 48h
after resuming the feeding (Figure 4.1B). The feeding schedule after the 0h time-point
was the same as during the acclimation period. Fish were killed by an overdose of ethyl
3-aminobenzoate methanesulphonate salt (MS-222) (Fluka, St Louis, MO, USA) and had
their TL and BM measured. Fast skeletal muscle was dissected from the dorsal epaxial
myotomes, flash frozen in liquid nitrogen and stored at -80ºC prior to total RNA
extraction. The digestive tract was dissected and fixed in 4% (m/v) paraformaldehyde
for later quantification of intestine content to the nearest milligram. The transcription
levels of the 15 genes of the IGF system, 2 ubiquitin ligases, 12 known nutritionally
responsive genes (Table 2.1), and the 4 myogenic regulatory factors (Table 3.1) in
skeletal muscle were measured by qPCR. Total RNA extraction, first strand cDNA
synthesis and dilution, and qPCR procedures were as described in the sections 2.3.5 and
2.3.8.
4.3.5. Statistical analysis and data transformation
Growth patterns were modelled using Growth II software (Pisces Conservation Ltd.,
New Milton, UK). The data on size at age of the different lineages were fitted to six
growth models (von Bertalanffy, exponential, 3 parameters Gompertz, 3 parameters
logistic, 4 parameters Gompertz and 4 parameters logistic) and the one with the lowest
Akaike Information Criterion and Schwarz Criterion was chosen. To facilitate the
interpretation of the relation between SL and BL in the different populations, these
measurements were transformed by raising to the power 0.33 and log transformation
respectively. A general linear model (GLM) was used to test the effect of selection on the
Chapter 4
118
proportionality among body size measurements (SL, FL, TL, H, and BM) using PAWS
Statistics 18 software (SPSS Inc., Chicago, Illinois, USA). T-test in Paws Statistics (SPSS
Inc.,) was used to compare the body size at age between sexes. The chi-square test in R
V. 2.10.0 software was used to analyse the sex-ratio among the zebrafish populations at
sexual maturity. All data were tested for equality of variance and normal distribution,
and ANOVA followed by Tukey post-hoc test using PAWS Statistics 18 software (SPSS
Inc.,) or Kruskal-Wallis followed by Conover post-hoc test using Brightstat (Stricker,
2008) was employed to analyse normally distributed and non-normally distributed
data, respectively. Bonferoni-corrected p-values lower than 0.05 were considered
statistically significant for gene expression data from the maternal transcripts and
fasting-refeeding experiments. Data from genes with similar expression between the S-
and L- lineage for all time-points of the fasting and refeeding experiment were
combined to produce a heatmap of gene expression independent of fish lineage. The
heatmap was produced using the PermutMatrix software
(http://www.lirmm.fr/~caraux/PermutMatrix/EN/index.html), with gene expression
normalized for rows and McQuitty’s method used for hierarchical clustering.
Chapter 4
119
Figure 4.1 – Experimental design for artificial selection (A) and fasting and refeeding
protocols (B). Fish from a wild-derived population of zebrafish were separated
according to size and used to produce four generations of fish divergently selected for
small (S-lineage), unselected (U-lineage) and large body size (L-lineage). Eggs and
embryos from G5 were used to investigate the effects of selection for body size on early
life-history traits and maternal transcripts levels. Adult fish from G5 were used to
investigate the effects of selection for body size on the transcription level of genes of
interest in skeletal muscle in response to fasting and refeeding. The growth pattern
from embryo to adult stage was determined for fish from G4 and G5.
Chapter 4
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4.4. Results
4.4.1. Effects of selection for body size on growth pattern
Average SL for fish from the fourth generation of the S-lineage was 2% lower when
compared to the founding population (an average of 0.6% loss in SL per generation),
while an average increase of 10% in SL was recorded for fish from the L-lineage in the
fourth generation (gain in SL of 3.3% per generation). The relationship between various
measures of body length (SL, FL, TL and H) and BM were independent of sex and lineage
(GLM, p>0.05). However, a significant difference in body size at age between sexes was
observed, with females having a larger body size than males in all lineages. The sex-
ratio of adult fish among the replicate populations from each lineage was close to 1:1
(chi-square test, p-value=0.6). This allowed for the comparison of the body size and
growth rate of the lineages without considering sex as a confounding variable. Based on
the Akaike Information Criterion (AIC), which measures the closeness of the
experimental points to the model, the best model for growth was a 4 parameter
Gompertz equation (Figure 4.2). In this model SL follows a sigmoid curve with an
inflection point (when growth rate starts to decrease) at 1/3 of age of when the fish
reach the predicted maximum body size. There was a statistically significant difference
in body size at age among the three different populations observable from 120dpf
(Figure 4.3A). Body size measurements between the replicates of a given lineage were
not statistically different when adult stage was reached and therefore were pooled to
facilitate the interpretation of results (Figure 4.3A, insert). Fish from the L-lineages
reached a maximum standard length of 32.9mm at 390dpf, which corresponded to 6.8
and 12.3% larger SLs than fish from U- and S-lineages (Figure 4.3A). These differences
of body size at age between the two selected lines from G4 are in accordance with the
change in SL per generation (~12%, described in the first sentence of this section). The
average BM of the L-lineages (0.521g) was 22.8 and 41.9% greater than the U- and S-
lineages at 390dpf (Figure 4.3C). The data on body size at age allowed only for the
calculation of the average growth rates from each lineage which were 0.194, 0.181, and
0.173 mm/d for the L-, U-, and S-lineage, respectively, during the exponential phase of
growth between 6 and 120 dpf.
Chapter 4
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Figure 4.2 – 4 parameters – Gompertz growth equation.
4.4.2. Effects of selection for body size on early life-history traits of zebrafish
The production of eggs per breeding batch in the 4th generation was 5-times greater in
the L- than the S-lineages (Table 4.3). Eggs from the S-lineages had a small (5.7%) but
significantly reduced diameter than eggs from the L-lineages, corresponding to 18%
less yolk (Table 4.3). Three waves of mortality were observed in all lineages peaking at
<24h (embryos), 2-4d (yolk-sac larvae) and 8-15d (free swimming larvae). The embryos
from L-lineage had the highest rates of deformity and mortality in both first (~12%)
and second waves (40%), followed by the U- and S-lineages (Table 4.3). In the third
wave, however, this scenario was reversed, with the S-lineage having the highest
mortality (~64%) when compared to the other lineages. At the end of the juvenile stage
these differences in mortality seem to have been equalized since the survival rate at
30dpf was around 30% for all three lineages (Table 4.3). The average TL of larvae at
6dpf just prior to complete yolk absorption was ~3.7, 3.6, and 3.4mm for the L-, U-, and
S-lineages (Table 4.3).
Chapter 4
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Figure 4.3 – legend on next page.
S-Lineage U-Lineage L-Lineage
0.0
0.1
0.2
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0 60 120 180 240 300 360 420
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**
**
S
ta
n
d
a
rd
L
e
n
g
th
(m
m
)
Age (dpf)
**
B
S1 S2 S3 U1 U2 U3 L1 L2 L3
0.0
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cd ef
de
debcdd
a
abc
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o
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(g
)
ab
Body mass of replicates at 260dpf
Males
1cm
Females
A
Chapter 4
123
Figure 4.3 – Growth curve from 6 to 390dpf and body mass at 390dpf of the selected
zebrafish lineages. (A)Standard length of zebrafish from S- (○), U- (►) and L-lineages
(■) after three rounds of selection for body size (A), symbols and error bars represent
mean and s.e.m., respectively. One asterisk above data-points means significant
statistical difference in at least one population in comparison to the others at the same
age; two asterisks means that the body size of the three lineages are different at the
same age (ANOVA followed by post-hoc Tukey test with p-value set to 0.05). (A, insert)
body mass at 260dpf of the three replicates lineages of zebrafish. (B) Body mass of
zebrafish lineages at 390dpf, ● represents the average body mass and different letters
above the box-plot means significant statistical difference (ANOVA followed by post-hoc
Tukey test with p-value set to 0.05). Males and females representatives of the average
body size at 390dpf of each lineage are shown in the bottom panel (C).
Table 4.3 – Effects of four rounds of artificial selection for body size at age on early life-
history traits of eggs and larvae. Values given are average ± s.d.m., different superscript
letters across the lineages means statistically significant difference in early-life traits
among the zebrafish lineages.
Early-life trait in chronological order Zebrafish Lineage
S-lineage U-lineage L-lineage
Eggs per spawning 389 ± 49 a 1,045 ± 153 a 1,956 ± 591 b
Yolk diameter (mm) 0.63 ± 0.02 a 0.65 ± 0.02 b 0.66 ± 0.02 c
Egg diameter (mm) 1.10 ± 0.05 a 1.18 ± 0.04 b 1.17 ± 0.03 b
Embryos with developmental deformities (%) 0.9 ± 0.3 a 3.6 ± 0.1 b 12.8 ± 1.1 c
Mortality from 2 to 6dpf (%) 5.0 ± 0.4 a 18.0 ± 1.8 b 40.0 ± 0.9 c
Total length of larvae at 6dpf (mm) 3.42 ± 0.13 a 3.56 ± 0.14 b 3.67 ± 0.14 c
Mortality from 7 to 30dpf (%) 64.0 ± 2.9 a 47.0 ± 0.2 b 32.0 ± 4.8 c
Survival rate at 30dpf (%) 29.0 ± 4.3 a 33.0 ± 0.7 a 28.0 ± 3.3 a
Chapter 4
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4.4.3. Effects of selection for body size on maternal transcripts
Growth hormone (GH) mRNA was 1.4 and 1.9-fold higher in eggs from the U- than the S
and L-lineages respectively (Figure 4.4). In contrast, igf1a transcripts were 1.4-fold
more abundant in eggs from the L-lineage than both the S- or U-lineages and igf1a
transcripts were not detected (Figure 4.4). Igf2a and Igf2b transcripts were also
significantly higher in the L- than either the U- or S- lineages (Figure 4.4). Strikingly,
igf2a mRNA was 5.6-times more abundant in the L-lineage than the other lineages
(P<0.01). Four of the five IGF and GH receptors (ghra, ghrb, igf1ar and igf2r) were
similarly higher in the L- than S-lineages by an average of 1.4-fold whereas there was no
difference in igf1br transcripts between lineages (Figure 4.5). Transcripts of igfbp2a,
igfbp5b, and igfbp6b were not detected at the developmental stage studied. Igfbp1a and
igfbp3 were 46 and 29% higher whereas igfbp1b was 5-fold lower in the L- than the U-
or S-lineages respectively. Igfbp6a mRNA increased in the series, U- > L- > S-lineage
(Figure 4.6).
Transcription factors from the Myogenic Regulatory Family (MRF) function in directing
the fate of embryonic cells to myogenic cells and in differentiation in a later stage.
Transcripts from three MRFs were detected in fertilized eggs of the zebrafish, while
myog was not detected. mRNA levels were higher in the L-lineage than in either the U-
or S-lineages for myoD (2.5-fold), myf5 (1.4-fold) and myf6 (1.4-fold) (Figure 4.7).
In mammals the transcription level of bmp15, gdf9 and their receptors were found to
correlate well with fecundity, and are also known as “fecundity genes”. The increase in
egg production by the L-lineage of zebrafish could not be explained by the expression of
the ligands bmp15 and gdf9 since there was no statistically significant difference in the
levels of the transcripts for bmp15, gdf9, in the eggs of the selected lineages (Figure 4.8).
In contrast, bmpr1aa and bmpr1bb transcripts were 1.4-fold higher in the L- than the S-
lineages. A very small but significant difference was observed for transcripts of bmpr1ab
in the U-lineage when compared to both S- and L-lineages (around 6% higher). In the
case of bmpr2b, transcript levels increased in the series S- > L- > U-lineages across a 6-
fold range of abundance, while no difference was recorded for bmpr1ba and bmpr2a
transcripts (Figure 4.8).
Chapter 4
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Figure 4.4 – Maternal transcripts of growth hormone and insulin-like growth factors in
zebrafish embryos from S-(black bars), U-(light-gray bars) and L-lineages (dark-gray
bars). Data-points and error bars represent mean and s.e.m. (n=12), respectively.
Different letters above columns of the same gene means statistically significant
difference (Kruskal-Wallis followed by post-hoc Conover test with Bonferoni correction
for multiple comparisons, P<0.05).
Gene
m
R
N
A
le
v
e
l
(A
.U
.)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
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1.0
1.1
b
a
c
a a
b
b
a
c
gh
S
-l
in
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-l
in
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igf1b
S
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igf2a
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igf2b
S
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in
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U
-l
in
e
L
-l
in
e
a
ab
b
Chapter 4
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Figure 4.5 – Maternal transcripts of receptors of growth hormone and insulin-like
growth factors in zebrafish embryos from S-(black bars), U-(light-gray bars) and L-
lineages (dark-gray bars). Data-points and error bars represent mean and s.e.m. (n=12),
respectively. Different letters above columns of the same gene means statistically
significant difference (Kruskal-Wallis followed by post-hoc Conover test with Bonferoni
correction for multiple comparisons, P<0.05).
Gene
m
R
N
A
le
v
e
l
(A
.U
.)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
igf1br
S
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in
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igf1ar
S
-l
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in
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igf2r
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a b
b
Chapter 4
127
Figure 4.6 – Maternal transcripts of insulin-like binding proteins in zebrafish embryos
from S-(black bars), U-(light-gray bars) and L-lineages (dark-gray bars). Data-points
and error bars represent mean and s.e.m. (n=12), respectively. Different letters above
columns of the same gene means statistically significant difference (Kruskal-Wallis
followed by post-hoc Conover test with Bonferoni correction for multiple comparisons,
P<0.05).
Gene
m
R
N
A
le
v
e
l
(A
.U
.)
0.0
0.1
0.2
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igfbp1b
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igfbp2b
S
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igfbp3
S
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in
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igfbp5a
S
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U
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e
L
-l
in
e
igfbp6a
S
-l
in
e
U
-l
in
e
L
-l
in
e
Chapter 4
128
Figure 4.7 – Maternal transcripts of myogenic regulatory factors in zebrafish embryos
from S-(black bars), U-(light-gray bars) and L-lineages (dark-gray bars). Myogenin
transcripts were not detected in the zebrafish embryo at this stage. Data-points and
error bars represent mean and s.e.m. (n=12), respectively. Different letters above
columns of the same gene means statistically significant difference (Kruskal-Wallis
followed by post-hoc Conover test with Bonferoni correction for multiple comparisons,
P<0.05).
Gene
m
R
N
A
le
v
e
l
(A
.U
.)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
a
myod
S
-l
in
e
U
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in
e
L
-l
in
e
myf5
S
-l
in
e
U
-l
in
e
L
-l
in
e
myf6
S
-l
in
e
U
-l
in
e
L
-l
in
e
a
b
a
b b
a
b b
Chapter 4
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Figure 4.8 – Maternal transcripts of “fecundity genes” and their receptors in zebrafish
embryos from S-(black bars), U-(light-gray bars) and L-lineages (dark-gray bars). Data-
points and error bars represent mean and s.e.m. (n=12), respectively. Different letters
above columns of the same gene means statistically significant difference (Kruskal-
Wallis followed by post-hoc Conover test with Bonferoni correction for multiple
comparisons, P<0.05).
Gene
m
R
N
A
le
v
e
l
(A
.U
.)
0.0
0.1
0.2
0.3
0.4
0.5
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a aa a
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4.4.4. Effects of selection for body size on muscle gene expression in adults
The S- and L-lineages had a similar feeding response across the fasting and refeeding
experiment, with no noticeable difference between the two lineages. The gut food
content decreased from 1.4 (% of body mass) at -170h to 0% after 7d of fasting. After
feeding was resumed the gut food content increased to 4.0, 3.3, and 4.0% at 1, 3 and 6h
respectively. At 24 and 48h the gut food content was similar to that found before the
fasting period (~1% of body mass), indicating fasting resulted in a transient increase in
food intake following refeeding (Figure 4.9).
Figure 4.9 – Gut food content of S- (○) and L-lineages (▀) in response to fasting and
refeeding. Symbols and error bars represent mean and s.e.m., respectively, N=6 fish per
lineage per time-point. Different letters above symbols represent statistically different
means among time-points for the S- (lowercase letters) and L-lineages (uppercase
letters), at P<0.05. The gut food content was similar between the two lineages at every
time-point at P<0.05.
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Chapter 4
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The expression of 8 out of 15 genes from the IGF system was very similar in the
S- and L-lineages in response to the fasting and refeeding experiment. Similarly, no
significant difference was observed for 11 out of 12 other nutritionally-responsive
genes and the 2 ubiquitin ligases [mafbx and trim63 (murf1)] in the two lineages. The
transcript levels of these genes in relation to the gut food content (Figure 4.10A) were
comparable to that reported previously (Amaral and Johnston, 2011).
The expression levels of three MRFs (myogenin, myf6 and myf5) were similar in
both S- and L-lineages, with no discernible pattern of expression for myf6 and myogenin
in response to fasting and refeeding (Figure 4.10C,D). In contrast, a small
downregulation of myf5 was observed from 0 to 1h (fasting period), with a subsequent
upregulation from 6 to 48h after feeding was resumed (Figure 4.10B). From the 33
genes assayed only 9 (igf1a, igf2a, igf1ar, igf1rb, igf2r, igfbp1a, igfbp1b, myoD and
kruppel like factor 11b – klf11b) showed a significant degree of variation in expression
between the S- and L-lineages. In all cases the artificial selection regime modified the
responsiveness of the transcriptional regulation in relation to the nutrient level but not
the pattern of expression. The constitutive expression of the ligand igf1a was around
1.5-fold higher in the L-lineage across the experiment, with a 2-fold higher expression
during 6 and 48h after resuming the feeding (Figure 4.11A). Conversely, only a transient
but significant difference in expression of igf2b was observed during the fasting period,
with 22% fewer transcripts detected in the L- compared to the S-lineage during the
fasting period (Figure 4.11B).
The artificial selection regime also affected the expression of all three receptors
of the IGF system. However, the expression of igf1ar was only slighty affected by
artificial selection, with a 1.5-fold higher expression in the L-lineage as the only
difference in expression of this gene across the experiment between the two lineages
(Figure 4.11C). The expression of igf1br was 2-fold higher in the L-lineage during the
fasting period (0 and 1h). Interestingly, this scenario was reversed during the refeeding
period when the transcript levels were around 40% less in the L-lineage from 24 to 48h
(Figure 4.11D). On the other hand, the constitutive expression of igf2r was 1.5-fold
higher on average in the L-lineage at all time-points (Figure 4.11E). Transcript levels of
this gene gradually increased as the gut emptied and a very gradual downregulation
was observed during the refeeding period for both lineages (Figure 4.11E).
Chapter 4
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The constitutive level of expression of both igfbp1a and igfbp1b was around 30%
less in the L-lineage across the experiment (Figure 4.12A,B). The biggest difference was
observed at 0h for the igfbp1b transcript (50% fewer transcripts in the L-lineage).
Transcription of myoD was regulated by nutrient levels and differed between
selected lines, with a single peak of expression at 1h after refeeding was resumed, when
~1.7-fold more transcripts were detected in skeletal muscle of the S-lineage (Figure
4.12C).
Kruppel-like factor 11b (klf11b) was the only nutritionally-responsive gene with
differential expression between the S- and L-lineages, with twice as much transcripts
detected in the L-lineage during prolonged fasting (Figure 4.12D).
Chapter 4
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Figure 4.10 – Transcription levels that were similar for the S- and L-lineages were
averaged to produce a heatmap of gene expression in response to fasting and refeeding
independent of fish lineage (A). The heatmap shows the hierarchical clustering
(McQuitty’s method) of normalized mRNA levels across the fasting and refeeding
periods – mean equals to zero and standard deviation equals to 1. Shades of yellow
represent upregulation and shades of cyan represent downregulation. Each block
represents the mean of mRNA level of 12 fish quantified by qPCR. The expression of
myf5 (B), myf6 (C) and myogenin (D) in response to nutrient levels were similar for both
lineages, with only myf5 displaying a discernible pattern of expression in response to
nutrient levels. Dashed lines in the graphs represent the gut food content and different
means are represented by different letters above symbol (P<0.05).
Chapter 4
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Figure 4.11 – Differential level of expression of the ligands igf1a (A) and igf2a (B), and
IGF receptors igf1ar (C), igf1br (D) and igf2r (E) between the S- (○) and L-lineages (▀) in
response to fasting and refeeding. Symbols and error bars represent mean and s.e.m,
respectively, N=6 fish per time-point per lineage. Different uppercase (L-lineage) and
lowercase (S-lineage) letters represent statistically significant means among the time-
points of the same lineage (P<0.05). Asterisks represent statistically different means
between the S- and L-lineages at the same time-point (P<0.05). The solid line on the top
denotes the acclimation and refeeding periods whereas the fasting period is
represented by a dashed line.
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Chapter 4
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Figure 4.12 – Differential level of expression of the IGF binding proteins igfbp1a (A)
and igfbp1b (B), the myogenic regulatory factor myoD (C), and the kruppel-like factor
11b (klf11b, D) between the S- (○) and L-lineages (▀) in response to fasting and
refeeding. Symbols and error bars represent mean and s.e.m, respectively, N=6 fish per
time-point per lineage. Different uppercase (L-lineage) and lowercase (S-lineage) letters
represent statistically significant means among the time-points of the same lineage
(P<0.05). Asterisks represent statistically different means between the S- and L-lineages
at the same time-point (P<0.05). The solid line on the top denotes the acclimation and
refeeding periods whereas the fasting period is represented by a dashed line.
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4.5. Discussion
After three rounds of experimental selection, the L-lineage of zebrafish showed
increased growth rate and final body size when compared to U- and S-lineages. This
change in body size seems to have affected the physiology of this fish at many levels. For
example, larger fish produced more and larger eggs containing more yolk, which
probably explains the larger body size of larvae at yolk absorption stage. Deposition of
maternal transcripts was also affected by the selective breeding as evidenced by higher
levels of IGFs, and GH and IGF receptors in fertilized eggs from the L-lineage compared
to the S-lineage. The experimental selection also affected the transcription of a limited
number of genes from the IGF-pathway in skeletal muscle of adult fish in response to a
growth-stimulus, including the IGFs, IGF receptors and the nutritionally-responsive
igfbp1, without significantly affecting the feeding intake. These findings point to a
directional and differential regulation of transcript deposition in eggs and transcription
in adult muscle that could contribute to the observed differences in growth with
selection. The changes in the IGF pathway observed in zebrafish selected for larger body
size are similar to those observed in domesticated and GH-transgenic rainbow trout
(Devlin et al., 2009).
A considerably higher number of embryos were produced by the L- as compared
to the S-lineage (Table 4.3), using the same numbers of fish and sex ratio per spawning.
This difference in embryo production could be simply due to the differences in body
mass since a strong positive relationship was previously described between body mass
and egg production in the zebrafish (Forbes et al., 2010). This difference in egg
production could also be due to a higher number of females ready to lay eggs which
could be investigated in the future by single-pair breeding experiments. In a previous
work the yolk volume of zebrafish embryos was experimentally manipulated and a clear
effect of yolk volume on larvae body size was found (Jardine and Litvak, 2003). The
larger body size of larvae from the L-lineage (Table 4.3) could be partially explained by
the higher amount of energy available for development and growth (yolk content).
During oocyte maturation, maternal transcripts are deposited in the oocyte and
are detectable until ~6hpf with varying degrees of degradation (Pelegri, 2003;
Mathavan et al., 2005; Tadros and Lipshitz, 2009). The maternally-deposited mRNA are
necessary for normal embryo development prior to zygotic activation (Pelegri, 2003;
Dosch et al., 2004; Lubzens et al., 2010), but are also thought to partially serve as
Chapter 4
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nutritional reserves (Hunter et al., 2010). Research in this area tends to focus on
observation of developmental abnormalities in zebrafish embryos triggered by chemical
mutations by exposing the parents to N-ethyl-N-nitrosurea, which causes random point
mutations. Although important, this approach lacks the power to investigate the
changes in deposition of non-lethal transcripts, which could have milder but important
and persistent effects on fitness. For example, the morpholino knockdown technology
has been used to specifically and transiently block the maternal transcripts of the
estrogen receptor 2a, which affected the development of the zebrafish embryo and
larvae (Celeghin et al., 2011). An earlier research also showed that maternally deposited
transcripts of radar, a TGF-β signalling molecule, is essential for the ventral fate of cells 
during development with loss-of-function causing lethal dorsalized phenotypes (Sidi et
al., 2003). Thus, it is possible that variation in maternal mRNA deposition between
families of fish is a trade-off in egg quality, with permanent effects on early life-history
traits. The levels of most of the transcripts investigated in the present work have been
recently reported to belong to gene clusters with very little changes between the 1- and
512-cell developmental stages in the zebrafish embryo as assayed by RNA-seq
(Vesterlund et al., 2011).
The level of transcription of genes involved in fertilization (gdf9, bmp15 and
bmp-receptors), growth (GH-IGF axis) and myogenesis (MRFs) was investigated. No
difference was observed in maternal deposition of gdf9 and bmp15 transcripts among
the three selected lineages. These two genes are closely related members of the TGF-β 
superfamily with important roles in oocyte maturation in the zebrafish (Liu and Ge,
2007; Peng et al., 2009), and are thought to be involved in ovulation and fecundity. A
previous work found no correlation between gdf9 and bmp15 levels in mature oocytes
and fecundity in zebrafish populations fed four different diets (Forbes et al., 2010). It is
possible, however, that ovulation and fecundity are not solely regulated at the ligands
but also at the receptor level. For example, polymorphisms in bmpr1b correlated well
with distinct prolificacy phenotypes in sheep (Chu et al., 2011). However, gdf9 and
bmp15 are not the only ligands that bind to BMP receptors, in fact these receptors are
capable of recognizing and binding a number of ligands from the TGF-β family (Koenig 
et al., 1994; Penton et al., 1994).
The present work shows that deposition of some paralogues of the receptors for
BMPs was differentially regulated among the three selected lineages, with the L-lineage
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having significantly more transcripts of bmpr1aa, bmpr1ba and bmpr2b (Figure 4.8).
Embryos from the L-lineage had more transcripts of three IGF ligands (igf1b, igf2a, igf2b
– Figure 4.4), growth hormone receptors (ghra and ghrb – Figure 4.5) and two IGF
receptors (igf1ar and igf2r – Figure 4.5) than the S-lineage. There is no information
available on the effect that change in levels of these maternal transcripts might cause on
zebrafish development, but experiments with morpholinos in zebrafish embryos
revealed the importance of igf1 receptors for the normal development of the embryo
(Schlueter et al., 2007). Information on the effect of knockdown of igf2r is currently
lacking. A differential deposition of igbp1a and igfbp1b in the selected lineages was
observed, with igfbp1 lower in S- than L-lineages, while the opposite was observed for
igfbp1b (Figure 4.6). Subfunction partitioning between these two igfbp1 transcripts in
the zebrafish has been reported before, with overexpression of either binding protein
causing developmental retardation (Kamei et al., 2008). However, care must be taken
when interpreting these results since there is no experimental evidence that the
different growth phenotypes obtained here are caused by changes in maternal
deposition of these transcripts.
Variations in the regulatory sequence of genes is an important mechanism that
can result in phenotypic variation and evolution (Nei, 2007). In this case, variations in
the regulatory sequence would cause changes in expression of the affected gene, with a
quantitative effect on biological processes upstream of gene expression. In the present
work, the S- and L-lineages did not display a different feeding response (Figure 4.9),
which shows that differences in growth could not be explained by changes in energy
acquisition. Then, it is possible that fish from the selected lines are allocating the
acquired energy in different ways, with the L-lineage allocating more energy for growth.
The hypothesis that gene expression of genes from the IGF pathway is differentially
regulated between the two selected lines in response to a growth stimulus was then
tested.
In a previous work, the transcriptional response of the IGF pathway in skeletal
muscle of the zebrafish after seven days of fasting with a single-meal as the growth
stimulus has been characterized (Amaral and Johnston, 2011). Here a slight
modification of the previous experiment, with ad libitum feeding after seven days of
fasting to observe the recovery response after fasting was used. The results of
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transcriptional regulation in response to fasting obtained here are very similar to those
described in the previous work (Amaral and Johnston, 2011) and 23 genes showed no
difference in level or pattern expression between the S- and L-lineages. In addition to
the transcripts studied in the previous work, the transcriptional response of the MRFs
to fasting and refeeding was investigated, with the expression of three MRFs not being
affected by experimental selection. Myf5, a member of the MRF family involved in
muscle differentiation and proliferation (Chen and Tsai, 2008), showed a clear response
to fasting-refeeding with downregulation during fasting and gradual upregulation with
feeding (Figure 4.10). This pattern of myf5 expression was independent of the zebrafish
lineage and has been previously described in Atlantic salmon (Bower and Johnston,
2010a). Expression of two other MRFs, myogenin and myf6, was not affect by the
experimental selection with no discernible pattern in response to fasting-refeeding
(Figure 4.10). Expression of myoD had a clear response to fasting and refeeding, with a
peak of expression at 1h after fish were re-fed and expression returned to basal levels
from 3h after refeeding (Figure 4.12C). MyoD was the only MRF whose expression was
affected by selection. Peak expression of myoD in response to refeeding was
considerably higher in fish from the S-lineage (Figure 4.12C). The pattern described
here is similar to the MyoD1b paralogue in Atlantic salmon (Bower and Johnston,
2010a).
Only 9 genes showed different levels of expression between the S- and L-
lineages, with very similar patterns of expression in response to the fasting-refeeding in
the two lineages. Genes with differential expression between the two lineages included
two ligands (igf1a and igf2a), the three receptors (igf1ar, igf1br and igf2r), two binding
proteins of the IGF-axis (igfbp1a and igfbp1b), one MRF (myoD) and one nutritionally-
responsive gene (klf11b).
In the zebrafish, igf1a is downregulated during fasting with a peak of expression
in response to a single-meal, while its receptors (igf1ar and igf1br) show an opposite
pattern of expression with upregulation during fasting with subsequent downregulation
during refeeding (Amaral and Johnston, 2011). The selection regime affected the level of
expression of these three transcripts, with the L-lineage having a higher basal
expression of igf1a across the fasting-refeeding experiment and higher expression of
the IGF receptors during the prolonged fasting period only (Figure 4.11A,C,D). IGF
promotes cell growth after binding to its respective receptors, activating the
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AKT/PI3K/mTOR pathway (Laplante and Sabatini, 2009). The present work shows that
the L-lineage might be more responsive to the same level of energy due to a higher
expression of igf1a and more sensitive to the ligand during fasting due to a higher
availability of the respective receptors.
The present approach allowed for a better observation of the transcriptional
response of igf2r and igf2a to refeeding which was not observed in the previous work
due to differences in experimental conditions (Figure 4.11B,E). Transcripts of igf2r and
igf2a were upregulated with prolonged fasting and a downregulation was observed
during refeeding, with the igf2r transcripts showing a very gradual change in transcript
level in relation to igf2a (Figure 4.11B,E). This pattern of expression and correlation
between igf2r and igf2 were as observed previously in Atlantic salmon (Bower et al.,
2008; Bower and Johnston, 2010a). The results show that the basal expression of igf2r
was affected by the selection experiment, while only a transient change during fasting
was observed for igf2a. Absence of a functional allelic copy of the maternal igf2r leads to
perinatal overgrowth and lethality, with elevated levels of igf2 in mice embryos due to
the absence of the degrading igf2 function of the igf2r (Lau et al., 1994; Wang et al.,
1994). In the zebrafish two copies of the igf2 gene exist, with distinct transcriptional
regulation during embryonic and adult phases (Zou et al., 2009; Nelson and Van Der
Kraak, 2010) with differential regulation in response a single-meal (Amaral and
Johnston, 2011) and fasting-refeeding (present work).
It is known that overexpression of igfbp1a/b in zebrafish embryos under
normoxia causes growth and developmental retardations (Kajimura et al., 2005; Kamei
et al., 2008). Igfbp1 causes its growth inhibiting action by rendering igf1 less available
to tissues. This negative regulation of growth by igfbp1 genes might explain the
downregulation of these genes during the growth stimuli of satiation (Amaral and
Johnston, 2011) and hints at a putative role of igfbp1 in the differential response to
growth stimuli in zebrafish lineages selected for divergent body size at age (Figure
4.12A,B).
Klf11b was also found to have different levels of expression between the S- and
L-lineages. Klf11b is a zebrafish paralogue of the KLF family of transcription factors
which has members involved in many biological processes including differentiation,
proliferation and apoptosis (McConnell and Yang, 2010). In mice klf11 functions in
growth inhibition (Fernandez-Zapico et al., 2003) while in fish its functions are not
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known. There is evidence that KLF is not strictly necessary for normal development and
growth in knockout mice, probably due to overlap in function of the different members
of the KLF family (Song et al., 2005). A strong upregulation of klf11b with prolonged
fasting in zebrafish skeletal muscle has been previously reported (Amaral and Johnston,
2011). In the present work a strong effect of selection on the transcriptional regulation
of this gene was observed, with fish from the L-lineage having twice as many transcripts
during prolonged fasting (Figure 4.12D).
The artificial selection experiment reported in this chapter successfully produced
three lineages of zebrafish with divergent body size. Selection for larger body size had
positive effects on offspring during embryonic and adult stage in terms of growth
(during both phases) and absolute number of fish per spawning, with no clear trade-off
for the increased body size at adult stage. A change in expression of a limited number of
genes from the IGF pathway was demonstrated in the present work, which points to a
better growth opportunity for fish from the L-lineage in response to a growth stimulus
(higher basal expression of igf1a, higher transient expression of igf1 receptors and
lower transient expression of igfbp1 genes in response to fasting-refeeding). However,
the L-lineage also had higher expression of the klf11b, which has negative effects on
growth in other organisms. Directional changes in transcript levels as a result of
selective breeding are based on the maintenance of alleles and loci that are beneficial to
the affected trait. Small changes in the regulatory sequence of genes and single
nucleotide polymorphisms in the coding sequence (SNPs) are two important variations
within an allele that could contribute to phenotypical differences within families. The
current work provides a good starting point for future research on the regulatory
sequence and SNPs of candidate genes that were changed after experimental selection.
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5. General Discussion
The overall objective of this thesis was to characterize the transcriptional change in
response to nutrition, photoperiod and selective breeding in the zebrafish, with special
attention to the IGF system. These three factors were chosen for their importance for
growth physiology of fish, with the intention of understanding in more detail the
molecular mechanisms of regulation. Transcription of DNA into mRNA is a fundamental
process for the production of protein, and recent findings point to a good correlation
between mRNA and protein levels in a teleost (Rees et al., 2011). However, care must be
exercised when extrapolating the results of transcript levels to biological outputs due to
the complex regulatory mechanisms that exist within the cells (e.g., mRNA stability and
degradation, translation control). In this section the main findings made during this
study and their impact on the literature will be discussed, together with ideas for future
experiments.
5.1. IGF signalling in zebrafish skeletal muscle
In chapters 2 and 4 the transcriptional response to nutrition was investigated in skeletal
muscle of zebrafish. In both experiments the concurrent expression of the 16 known
zebrafish genes of the IGF signaling was investigated. In zebrafish, the transcription of
the ligands igf1a, igf2a and igf2b, the receptors igf1ar, igf1br and igf2r, and the binding
proteins igfbp1a and igfbp1b changed in response to nutritional status. Some of the
duplicated genes showed a marked difference in expression. For example, igf1a was
detected in skeletal muscle but igf1b was not. The patterns of transcription for igf1a,
igf1ar and igf1br described here for the zebrafish are similar to other fish species
(Chauvigne et al., 2003; Bower et al., 2008). However, the timing of changes in
transcription were dramatically faster in this small tropical species. For example,
previous research has demonstrated a marked increase in igf1 transcripts within days
in skeletal muscle of fasted rainbow trout and Atlantic salmon following refeeding
(Chauvigne et al., 2003; Bower et al., 2008). It is important to notice that those studies
investigated the transcriptional response during recovery for a period of days, and that
fast (<2d) transcriptional responses were not investigated. Thus the present work
provides a detailed description of the fast transcriptional response of IGF components
during the post-prandial period.
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The transcription of IGF binding proteins was another noteworthy difference
between zebrafish and Atlantic salmon. Only the paralogues igfbp1a and igfbp1b
showed a clear response to feeding, with upregulation during fasting in skeletal muscle
of zebrafish. In Atlantic salmon, igfbp2.1 was upregulated during maintenance feeding
with a gradual downregulation with refeeding whereas igfbp4 showed the opposite
pattern to igfbp2.1 (Bower et al., 2008). It is possible that the differences in IGF binding
protein regulation found between zebrafish and salmonids derived from the massive
genome rearrangements after WGD events, with retained gene paralogues sharing the
molecular functions of genes that were lost over evolutionary time. For example, igfbp4
was apparently lost in the zebrafish genome, whereas it is conserved in the salmonid
lineage functioning in the transcriptional response to nutritional status.
Igf2r is known to have a fundamental function in development and embryonic
growth in mice (Lau et al., 1994; Wang et al., 1994). The function of this receptor has not
been investigated in fish. In chapter 4 a clear upregulation with fasting with a very
gradual downregulation with feeding was observed for this receptor. This finding,
together with previous report in Atlantic salmon, point to a function of the igf2r in the
nutritional response in fish (Bower et al., 2008). Transient loss-of-function using
antisense morpholino in zebrafish embryos could shed light on this matter and would
be an important model to study the signaling downstream of the igf2r (to confirm that
the ligands are targeted for lysosomal degradation, for example).
In addition to the expression of the genes of the IGF signaling, the microarray
analysis revealed approximately 147 genes differentially regulated in skeletal muscle in
response to nutritional status (chapter 2). For example, ornithine decarboxylase 1
(ODC1) was strongly upregulated with feeding. This enzyme catalyses the rate limiting
step of polyamine biosynthesis pathway by converting ornithine to putrescine (Figure
5.1). Polyamines interact with a number of macromolecules within the cell, including
the DNA and can cause changes in transcriptional regulation. They have been implicated
in various biological processes and are known to play an important role in control of cell
cycle (Nasizadeh et al., 2005; Larqué et al., 2007; Alm and Oredsson, 2009). Previous
research has demonstrated the changes in activity of hepatic ODC in mice and fish in
response to the nutritional status (Moore and Swendseid, 1983; Benfey, 1992). For
example, hepatic ODC activity decreased exponentially during fasting and was elevated
4h after refeeding in brook trout (Salvelinus fontinalis) (Benfey, 1992). Furthermore,
Chapter 5
144
ODC mRNA and activity levels in muscle of Atlantic salmon and brook trout were
strongly positively correlated with growth rate (Arndt et al., 1994; Benfey et al., 1994).
The description of ODC in this study as a nutritionally-responsive gene is an example of
the importance of a gene discovery approach, revealing the importance of other genes
than the candidate ones. Future investigation on the transcriptional changes triggered
by polyamines in cell culture could shed light on the molecular mechanisms controlling
cell cycle control in fish muscle.
Figure 5.1 – Role of ornithine decarboxylase (ODC) in the biosynthesis of polyamines
(putrescine, spermidine and spermine). ODC has high turnover rates due to fast
degradation by the proteasome. In contrast to other proteins, ODC is targeted to
proteasome degradation by conjugation to ATP by antizyme, whose expression is
positively correlated with polyamine levels. The biological functions of polyamines are
many, and are thought to be based on their poly-cationic nature by binding and
stabilizing DNA and mRNA molecules, for example. This diagram was modified from
(Pegg, 2006; Larqué et al., 2007).
Chapter 5
145
The expression of different nutritionally-responsive IGF muscle genes was also
differentially expressed in two lineages of zebrafish divergently selected for body size at
age (chapter 4). The changes in transcription could not be linked to differences in feed
intake, since fish from both lineages showed similar relative gut food content. It is
possible that experimental selection resulted in fish with different feeding conversion,
affecting the metabolism rather than the appetite control. In line with this hypothesis,
fish from the L-lineage had a transcriptional profile compatible with a higher anabolic
state (higher constitutive levels of igf1a that became more pronounced during feeding
and higher levels of igf1 receptor during satiation feeding). Furthermore, fish from the
L-lineage had lower levels of igfbp1a/1b during feeding, pointing to a higher availability
of igf1a. The promoter region of these genes are interesting candidates for investigating
variations in cis-regulatory sequences responsible for the modifications observed in size
in the zebrafish lineages. Another possibility that was not explored in the present study
is that there could exist small variations in the coding sequence of genes, and that
experimental selection is purifying favourable alleles in a certain direction. Occurrence
of single nucleotide polymorphisms (SNPs) in many species is one example of well
documented sequence variation, with correlations with changes of phenotype. For
example, SNPs have been used in breeding programs to improve qualities of trait in the
production of meat from cattle (Goddard et al., 2010). A web data-base is available for
SNPs markers in cattle, allowing a quick glance at annotation and gene ontology of
affected genes (Wang et al., 2011). It is possible that experimental selection and
domestication in fish cause a directional shift in frequency of alleles bearing SNPs
related to growth and fillet quality traits. Next generation sequencing of genomic DNA
and RNAseq techniques could prove very useful in the investigation of differences in
regulatory and coding sequence of selected fish, respectively. The availability of a well
annotated genome sequence would certainly be a great advantage in analysing the
results of such a large-scale experiment.
Adult fish from the L-lineage were ~12% larger and ~41% heavier than fish
from the S-lineage after three rounds of experimental selection for body size at age.
Although these results are significant, it is important to notice that around 45-75% of
fish were selected from each generation to produce offspring for the following
generation. These percentages were chosen to keep a minimum number of fish per
population in order to avoid an extensive loss of genetic variation. If the circumstances
Chapter 5
146
allowed, it would have been better to have more fish per replicate line allowing for an
increase in the selective pressure, which could result in even more clear-cut effects. In
addition, genetic material from the founding populations and the selected lineages could
have been stored. By doing so it would have been possible to assert parentage, to
calculate the heritability of the traits under investigation, and to analyse the extent of
loss of genetic variation per generation, which are very important factors in selective
breeding of captive fish.
Apart from the effects on body size and gene expression in skeletal muscle,
experimental selection caused several changes on the early-life traits of zebrafish. The
higher number of eggs produced per spawning is maybe the most significant difference
for successful propagation of a fish lineage in a competitive environment. Five times
more fish were produced by the L-lineage compared to the S-lineage. However, it
remains to be established whether the experimental selection affected the timing of
sexual maturation or the fertilization rate. To properly address this question, the
number of eggs produced at age by single pairs of fish could have been calculated over a
period from the juvenile to early adult stages. It is also possible that the selective
breeding did not affect sexual maturation or fertilization rate and that the number of
eggs produced is simply a result of the positive correlation between body size and egg
production, as observed previously (Forbes et al., 2010).
Differential deposition of maternal transcripts was another important early-life
trait change triggered by the experimental selection experiment. The functions of
maternal transcripts are far from completely understood and more experiments to
specifically investigate the importance of these maternally-deposited transcripts in fish
eggs are necessary.
5.2. Molecular clock machinery in zebrafish skeletal muscle
Zebrafish have strong circadian locomotory, breeding and feeding rhythm (Blanco-
Vives and Sanchez-Vazquez, 2009; del Pozo et al., 2011). The experiments in chapter 3
were first designed to provide evidence whether the changes in expression observed in
genes of the IGF pathway and nutritionally-responsive genes were due to metabolic
changes triggered by circadian food-anticipatory activities or to the nutrient levels. The
experiments in that chapter were then expanded to characterize the circadian
Chapter 5
147
expression of the core-clock machinery and putative clock-controlled genes in skeletal
muscle, an underexplored field in fish biology.
The experiments in chapter 3 confirmed that the differences observed in the IGF
muscle genes were due to nutritional status since no circadian pattern was found for igf
ligands, igf receptors or igfbp1a/b. Furthermore, expression of igfbp3 and igfbp5b
followed a circadian pattern and were described as putative clock-controlled genes. The
photoperiod experiment was also important in discovering genes that integrate
metabolism with the molecular clock machinery. For example, two nutritionally-
responsive genes (nr1d1 and hsf2) were found to have a strong circadian pattern of
expression, highlighting the importance of the comparison of the different experiments
performed in this study.
Concurrent expression of 17 known circadian genes in skeletal muscle was
investigated and differences in responsiveness were found between three gene
paralogues. Expression of the main positive (clock1a/b and bmal1a/b) and negative
oscillators (cry1a, per1a/1b, per2, and per3) in skeletal muscle followed a strong
circadian pattern similar to those described in central pacemaker organs of the
circadian mechanism (eye, brain and pineal gland) in zebrafish and Senegalese sole
(Solea senegalensis) (Whitmore et al., 1998; Martín-Robles et al., 2011; Vatine et al.,
2011). From the known circadian genes investigated, cry1b was the only one with no
strong circadian pattern. Thus, this gene might not participate in the pool of
cryptochrome proteins that form heterodimers with period proteins in the cytoplasm to
block dimerization of clock with bmal. The apparent synchronization of peripheral clock
in skeletal muscle and central pacemaker organs remains to be established and has
been a contentious subject in this field (Vatine et al., 2011; Weger et al., 2011).
To investigate the fundamentals of integration and synchronization of the
peripheral organs to central pacemakers in adult fish the first step would be to disrupt
the molecular clock in either tissue. Disruption of the molecular clock in the central
pacemakers would have a systemic effect and would possibly make the interpretation of
specific effects in peripheral tissues impossible. However, there are two advantages in
this scenario: it would be possible (a) to assert the putative direct responsiveness of
peripheral tissues to light and establish the hierarchy of the central pacemakers, and (b)
to establish the importance of the central molecular clock for peripheral homeostasis.
Disruption of the molecular clock in the peripheral tissue of interest would possibly
Chapter 5
148
render the tissue irresponsive to the central pacemakers, allowing for direct
observation of the importance of the clock mechanism in the peripheral tissue. This
approach also has the advantage of investigating the effect of disruption of clock-
controlled genes in tissue-specific manner. To achieve such objectives in adult tissues, a
long-term change in the transcriptional machinery would be necessary which excludes
the possibility of using anti-sense morpholinos. Loss-of-function of the main oscillators
clock and bmal could theoretically be achieved by the RNA interference technique,
affecting the positive arm of the clock pathway. However, there are difficulties in
establishing RNA interference in zebrafish (Lawson and Wolfe, 2011). Maybe a more
feasible way to disrupt the molecular clock would be to use gain-of-function
experiments in which a constitutive expression of the clock and bmal dimerization
inhibitors (cryptochrome and period proteins) would disrupt the control of the negative
oscillators of the clock pathway.
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