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dc.contributor.authorHoedjes, KM
dc.contributor.authorGrath, S
dc.contributor.authorPosnien, N
dc.contributor.authorRitchie, MG
dc.contributor.authorSchlötterer, C
dc.contributor.authorAbbott, JK
dc.contributor.authorAlmudi, I
dc.contributor.authorCoronado-Zamora, M
dc.contributor.authorMitchell, ED
dc.contributor.authorFlatt, T
dc.contributor.authorFricke, C
dc.contributor.authorGlaser-Schmitt, A
dc.contributor.authorGonzález, J
dc.contributor.authorHolman, L
dc.contributor.authorKankare, M
dc.contributor.authorLenhart, B
dc.contributor.authorOrengo, DJ
dc.contributor.authorSnook, RR
dc.contributor.authorYilmaz, VM
dc.contributor.authorYusuf, L
dc.date.accessioned2024-07-17T15:30:10Z
dc.date.available2024-07-17T15:30:10Z
dc.date.issued2024-06-10
dc.identifier303808626
dc.identifier531542b6-5a24-491a-9bf4-7c1dcce8b227
dc.identifier001241862400001
dc.identifier38856653
dc.identifier85195635847
dc.identifier.citationHoedjes , KM , Grath , S , Posnien , N , Ritchie , MG , Schlötterer , C , Abbott , JK , Almudi , I , Coronado-Zamora , M , Mitchell , ED , Flatt , T , Fricke , C , Glaser-Schmitt , A , González , J , Holman , L , Kankare , M , Lenhart , B , Orengo , DJ , Snook , RR , Yilmaz , VM & Yusuf , L 2024 , ' From whole bodies to single cells : a guide to transcriptomic approaches for ecology and evolutionary biology ' , Molecular Ecology , vol. Early View . https://doi.org/10.1111/mec.17382en
dc.identifier.issn0962-1083
dc.identifier.otherORCID: /0000-0001-7913-8675/work/162168593
dc.identifier.urihttps://hdl.handle.net/10023/30206
dc.descriptionFunding: The authors were assisted by a Special Topics Network (STN) grant from the European Society for Evolutionary Biology (ESEB) to facilitate networking of the European Drosophila Population Genomics consortium (DrosEU; https://droseu.net/). SG and NP are supported by a Deutsche Forschungsgemeinschaft grant (GR 4495/4-1, PO 1648/7-1, PO 1648/4-1). MGR is supported by Natural Environment Research Council, UK (NE/V001566/1). CS is supported by the Austrian Science Funds (P32935, P33734, W1225). TF is supported by the Swiss National Science Foundation (310030_219283, FZEB-0-214654, 31003A-182262). JG is supported by grant PID2020-115874GB-I00 funded by MCIN/AEI/10.13039/501100011033 and from grant 2021 SGR 00417 funded by Departament de Recerca i Universitats, Generalitat de Catalunya. MK was supported by the grant 322980 from The Research Council of Finland.en
dc.description.abstractRNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.
dc.format.extent11
dc.format.extent1018502
dc.language.isoeng
dc.relation.ispartofMolecular Ecologyen
dc.subjectBulk RNAseqen
dc.subjectCellular heterogeneityen
dc.subjectDeconvolutionen
dc.subjectGene expressionen
dc.subjectSingle-cell RNAseqen
dc.subjectTranscriptomicsen
dc.subjectQH301 Biologyen
dc.subjectT-DASen
dc.subject.lccQH301en
dc.titleFrom whole bodies to single cells : a guide to transcriptomic approaches for ecology and evolutionary biologyen
dc.typeJournal articleen
dc.contributor.sponsorNERCen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews. St Andrews Bioinformatics Uniten
dc.identifier.doi10.1111/mec.17382
dc.description.statusPeer revieweden
dc.identifier.grantnumberNE/V001566/1en


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