Use of Qualitative Environmental and Phenotypic Variables in the Context of Allele Distribution Models: Detecting Signatures of Selection in the Genome of Lake Victoria Cichlids
When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named Matsam. Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (Dfdist and BayeScan) and ADM (Matsam) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.
Key wordsGenome scans Signature of selection Genotype × phenotype association Environmental variables Logistic regression Cichlid fishes Seascape genetics
We would like to thank Geoffrey Dheyongera, Salome Mwaiko, and Isabel Magalhaes for their participation to the project. We are also grateful to Martine Maan, Alan Hudson, Kay Lucek, and Mathieu Foll for their contribution to fruitful scientific discussions about the issues presented in this chapter.
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