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VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity
Genetics Selection Evolution  (IF5.1),  Pub Date : 2021-11-08, DOI: 10.1186/s12711-021-00659-6
Denoyelle, Laure, Talouarn, Estelle, Bardou, Philippe, Colli, Licia, Alberti, Adriana, Danchin, Coralie, Del Corvo, Marcello, Engelen, Stéfan, Orvain, Céline, Palhière, Isabelle, Rupp, Rachel, Sarry, Julien, Salavati, Mazdak, Amills, Marcel, Clark, Emily, Crepaldi, Paola, Faraut, Thomas, Masiga, Clet Wandui, Pompanon, François, Rosen, Benjamin D., Stella, Alessandra, Van Tassell, Curtis P., Tosser-Klopp, Gwenola

Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra. A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin. We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies.