A linkage disequilibrium-based statistical test for Genome-Wide Epistatic Selection Scans in structured populations |
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Authors: | Lé a Boyrie,Corentin Moreau,Florian Frugier,Christophe Jacquet,Maxime Bonhomme |
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Affiliation: | 1.Laboratoire de Recherche en Sciences Végétales (LRSV), Université de Toulouse, Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Castanet-Tolosan, France ;2.Institute of Plant Sciences-Paris Saclay (IPS2), Centre National de la Recherche Scientifique, Univ Paris-Sud, Univ Paris-Diderot, Univ d’Evry, Institut National de la Recherche Agronomique, Université Paris-Saclay, 91192 Gif-sur-Yvette, France |
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Abstract: | The quest for signatures of selection using single nucleotide polymorphism (SNP) data has proven efficient to uncover genes involved in conserved and/or adaptive molecular functions, but none of the statistical methods were designed to identify interacting alleles as targets of selective processes. Here, we propose a statistical test aimed at detecting epistatic selection, based on a linkage disequilibrium (LD) measure accounting for population structure and heterogeneous relatedness between individuals. SNP-based () and window-based () statistics fit a Student distribution, allowing to test the significance of correlation coefficients. As a proof of concept, we use SNP data from the Medicago truncatula symbiotic legume plant and uncover a previously unknown gene coadaptation between the MtSUNN (Super Numeric Nodule) receptor and the MtCLE02 (CLAVATA3-Like) signaling peptide. We also provide experimental evidence supporting a MtSUNN-dependent negative role of MtCLE02 in symbiotic root nodulation. Using human HGDP-CEPH SNP data, our new statistical test uncovers strong LD between SLC24A5 (skin pigmentation) and EDAR (hairs, teeth, sweat glands development) world-wide, which persists after correction for population structure and relatedness in Central South Asian populations. This result suggests that epistatic selection or coselection could have contributed to the phenotypic make-up in some human populations. Applying this approach to genome-wide SNP data will facilitate the identification of coadapted gene networks in model or non-model organisms.Subject terms: Population genetics, Epistasis, Rhizobial symbiosis |
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