Uncovering Adaptation from Sequence Data: Lessons from Genome Resequencing of Four Cattle Breeds

Author:

Boitard Simon12,Boussaha Mekki1,Capitan Aurélien13,Rocha Dominique1,Servin Bertrand4

Affiliation:

1. Génétique Animale et Biologie Intégrative, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France

2. Institut de Systématique, Évolution, Biodiversité–UMR 7205–Centre National de la Recherche Scientifique and Muséum National d′Histoire Naturelle and Université Pierre et Marie Curie and Ecole Pratique des Hautes Etudes, Ecole Pratique des Hautes Etudes, Sorbonne Universités, 75005 Paris, France

3. Alice, 75595 Paris, France

4. GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, 31326 Castanet-Tolosan, France

Abstract

Abstract Detecting the molecular basis of adaptation is one of the major questions in population genetics. With the advance in sequencing technologies, nearly complete interrogation of genome-wide polymorphisms in multiple populations is becoming feasible in some species, with the expectation that it will extend quickly to new ones. Here, we investigate the advantages of sequencing for the detection of adaptive loci in multiple populations, exploiting a recently published data set in cattle (Bos taurus). We used two different approaches to detect statistically significant signals of positive selection: a within-population approach aimed at identifying hard selective sweeps and a population-differentiation approach that can capture other selection events such as soft or incomplete sweeps. We show that the two methods are complementary in that they indeed capture different kinds of selection signatures. Our study confirmed some of the well-known adaptive loci in cattle (e.g., MC1R, KIT, GHR, PLAG1, NCAPG/LCORL) and detected some new ones (e.g., ARL15, PRLR, CYP19A1, PPM1L). Compared to genome scans based on medium- or high-density SNP data, we found that sequencing offered an increased detection power and a higher resolution in the localization of selection signatures. In several cases, we could even pinpoint the underlying causal adaptive mutation or at least a very small number of possible candidates (e.g., MC1R, PLAG1). Our results on these candidates suggest that a vast majority of adaptive mutations are likely to be regulatory rather than protein-coding variants.

Publisher

Oxford University Press (OUP)

Subject

Genetics

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