St Andrews Research Repository

St Andrews University Home
View Item 
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

A new FST method to uncover local adaptation using environmental variables

Thumbnail
View/Open
article.pdf (977.0Kb)
Date
09/11/2015
Author
de Villemereuil, Pierre
Gaggiotti, Oscar Eduardo
Keywords
Local adaptation
Environment
Bayesian methods
F model
False discovery rate
Genome scan
QH301 Biology
BDC
R2C
Metadata
Show full item record
Altmetrics Handle Statistics
Altmetrics DOI Statistics
Abstract
1.  Genome-scan methods are used for screening genome-wide patterns of DNA polymorphism to detect signatures of positive selection. There are two main types of methods: (i) "outlier'' detection methods based on FST that detect loci with high differentiation compared to the rest of the genome, and (ii) environmental association methods that test the association between allele frequencies and environmental variables. 2.  We present a new FST-based genome-scan method, BayeScEnv, which incorporates environmental information in the form of "environmental differentiation''. It is based on the F-model, but, as opposed to existing approaches, it considers two locus-specific effects; one due to divergent selection, and another due to various other processes different from local adaptation (e.g. range expansions, differences in mutation rates across loci or background selection). The method was developped in C++ and is avaible at http://github.com/devillemereuil/bayescenv. 3.  A simulation study shows that our method has a much lower false positive rate than an existing FST-based method, BayeScan, under a wide range of demographic scenarios. Although it has lower power, it leads to a better compromise between power and false positive rate. 4.  We apply our method to a human dataset and show that it can be used successfully to study local adaptation. We discuss its scope and compare it to other existing methods.
Citation
de Villemereuil , P & Gaggiotti , O E 2015 , ' A new F ST  method to uncover local adaptation using environmental variables ' , Methods in Ecology and Evolution , vol. 6 , no. 11 , pp. 1248-1258 . https://doi.org/10.1111/2041-210X.12418
Publication
Methods in Ecology and Evolution
Status
Peer reviewed
DOI
https://doi.org/10.1111/2041-210X.12418
ISSN
2041-210X
Type
Journal article
Rights
© 2015 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1111/2041-210X.12418
Description
PdV was supported by a doctoral studentship from the French Ministère de la Recherche et de l'Enseignement Supérieur. OEG was supported by the Marine Alliance for Science and Technology for Scotland (MASTS).
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/9159

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

Advanced Search

Browse

All of RepositoryCommunities & CollectionsBy Issue DateNamesTitlesSubjectsClassificationTypeFunderThis CollectionBy Issue DateNamesTitlesSubjectsClassificationTypeFunder

My Account

Login

Open Access

To find out how you can benefit from open access to research, see our library web pages and Open Access blog. For open access help contact: openaccess@st-andrews.ac.uk.

Accessibility

Read our Accessibility statement.

How to submit research papers

The full text of research papers can be submitted to the repository via Pure, the University's research information system. For help see our guide: How to deposit in Pure.

Electronic thesis deposit

Help with deposit.

Repository help

For repository help contact: Digital-Repository@st-andrews.ac.uk.

Give Feedback

Cookie policy

This site may use cookies. Please see Terms and Conditions.

Usage statistics

COUNTER-compliant statistics on downloads from the repository are available from the IRUS-UK Service. Contact us for information.

© University of St Andrews Library

University of St Andrews is a charity registered in Scotland, No SC013532.

  • Facebook
  • Twitter