|Xu, Lingyang - UNIVERSITY OF MARYLAND|
|Hutchison, Jana - Edwards|
|Schroeder, Steven - Steve|
|Song, Juizhou - UNIVERSITY OF MARYLAND|
|Garcia, Jose Fernando - FACULDADE DE CIÊNCIAS AGRÁRIAS E VETERINÁRIAS DE JABOTICABAL-UNESP|
|Van Tassell, Curtis - Curt|
|Schnabel, Robert - UNIVERSITY OF MISSOURI|
|Taylor, Jeremy - UNIVERSITY OF MISSOURI|
|Lewin, Harris - UNIVERSITY OF CALIFORNIA|
|Liu, Ge - George|
Submitted to: DNA Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/29/2016
Publication Date: 4/15/2016
Citation: Bickhart, D.M., Xu, L., Hutchison, J.L., Cole, J.B., Schroeder, S.G., Song, J., Garcia, J., Van Tassell, C.P., Sonstegard, T.S., Schnabel, R.D., Taylor, J.F., Lewin, H.A., Liu, G. 2016. Whole-genome sequencing reveals the diversity of cattle copy number variations and multicopy genes. DNA Research. 23(3):253-62.
Interpretive Summary: Structural and functional impacts of copy number variations (CNVs) on livestock genomes are not yet well understood. We identified 1853 CNV regions (CNVRs) using population-scale sequencing data generated from 75 cattle of 8 breeds. We porformed the first detailed population-genetic analyses of cattle CNVs and multicopy genes in modern domesticated cattle. These CNV results provide a new glimpse of diverse selections during cattle speciation, domestication, breed formation, and recent genetic improvement. Farmers, scientist, and policy planners who need to improve animal health and production based on genome-enable animal selection will benefit from this manuscript.
Technical Abstract: Structural and functional impacts of copy number variations (CNVs) on livestock genomes are not yet well understood. We identified 1853 CNV regions using population-scale sequencing data generated from 75 cattle representing 8 breeds (Angus, Brahman, Gir, Holstein, Jersey, Limousin, Nelore, Romagnola). Individual genome sequence coverage ranged from 4 to 30 fold, with a mean of 11.8 fold. A total of 3.1% (87.5 Mb) of the cattle genome is predicted to be copy number variable, representing a substantial increase over previous estimates (~2%). CNV calls made with sequence data showed good correlation with array comparative genomic hybridization (CGH) data (r2 = 0.761) and had an estimated 12% false positive rate and a 19% false negative rate based upon qPCR and array CGH, respectively. Hundreds of CNVs were found to be either breed specific or differentially variable across breeds, including the RICTOR gene in dairy breeds and the PNPLA3 gene in beef breeds. In contrast, clusters of the PRP and PAG genes were found to be duplicated in all sequenced animals, suggesting that subfunctionalization, neofunctionalization or overdominance play roles in diversifying those fertility related genes. Further population-genetic analyses based on CNVs revealed the population structures of these taurine and indicine breeds and uncovered potential positively selected CNV candidates near important functional genes, such as AOX1, ASZ1, GAT, GLYAT, and KRTAP9-1. These CNV results provide a new glimpse into the diverse selection histories of cattle breeds during speciation, domestication, breed formation, and more recently, genetic improvement.