Identification of copy number variation in French dairy and beef breeds using next-generation sequencing

• Main Authors: Rabia Letaief, Emmanuelle Rebours, Cécile Grohs, Cédric Meersseman, Sébastien Fritz, Lidwine Trouilh, Diane Esquerré, Johanna Barbieri, Christophe Klopp, Romain Philippe, Véronique Blanquet, Didier Boichard, Dominique Rocha, Mekki Boussaha
• Format: Article
• Language: deu
• Published: BMC 2017-10-01
• Series: Genetics Selection Evolution
• Online Access: http://link.springer.com/article/10.1186/s12711-017-0352-z

Abstract Background Copy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches. Results We report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions. Conclusions Our study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle.