RT Journal Article SR Electronic T1 High density genome scan for selection signatures in French sheep reveals allelic heterogeneity and introgression at adaptive loci JF bioRxiv FD Cold Spring Harbor Laboratory SP 103010 DO 10.1101/103010 A1 Rochus, Christina Marie A1 Tortereau, Flavie A1 Plisson-Petit, Florence A1 Restoux, Gwendal A1 Moreno, Carole A1 Tosser-Klopp, Gwenola A1 Servin, Bertrand YR 2017 UL http://biorxiv.org/content/early/2017/01/25/103010.abstract AB Sheep was one of the first domesticated livestock species in the Anatolia region of contemporary Iran and eventually spread world-wide. Previous studies have shown that French sheep populations likely harbour a large part of European domesticated sheep diversity in a relatively small geographical region, offering a powerful model for the study of adaptation. We studied the diversity of 27 French sheep populations by genotyping 542 individuals for more than 500 000 SNPs. We found that French sheep breeds were divided into two main groups, corresponding to northern and southern origins and additionally we identified admixture events between northern and southern populations. The genetic diversity of domesticated animals results from adaptation of populations to constraints imposed by farmers and environmental conditions. We identified 126 genomic regions likely affected by selection. In many cases, we found evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. Some of these regions harbour genes potentially involved in morphological traits (SOCS2, NCAPG/LCORL, MSRB3), coat colour (MC1R) and adaptation to environmental conditions (ADAMTS9). Closer inspection of two of these regions clarified their evolutionary history: at the LCORL/NCAPG locus we found evidence for introgression of an adaptive allele from a southern population into northern populations and by resequencing MC1R in some breeds we confirmed different mutations in this gene are responsible for the same phenotypic trait. Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations.