Journal
METHODS IN ECOLOGY AND EVOLUTION
Volume 6, Issue 11, Pages 1248-1258Publisher
WILEY
DOI: 10.1111/2041-210X.12418
Keywords
Bayesian methods; environment; F model; false discovery rate; genome scan; local adaptation
Categories
Funding
- French Ministere de la Recherche et de l'Enseignement Superieur
- Marine Alliance for Science and Technology for Scotland (MASTS)
Ask authors/readers for more resources
1. Genome-scan methods are used for screening genomewide patterns of DNA polymorphism to detect signatures of positive selection. There are two main types ofmethods: (i) 'outlier' detection methods based on F-ST 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 F-ST-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 the other 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 available 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 data set and show that it can be used successfully to study local adaptation. We discuss its scope and compare it to other existing methods.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available