Identification of copy number variations in the genome of Dairy Gir cattle

PLoS One. 2023 Apr 10;18(4):e0284085. doi: 10.1371/journal.pone.0284085. eCollection 2023.

Abstract

Studying structural variants that can control complex traits is relevant for dairy cattle production, especially for animals that are tolerant to breeding conditions in the tropics, such as the Dairy Gir cattle. This study identified and characterized high confidence copy number variation regions (CNVR) in the Gir breed genome. A total of 38 animals were whole-genome sequenced, and 566 individuals were genotyped with a high-density SNP panel, among which 36 animals had both sequencing and SNP genotyping data available. Two sets of high confidence CNVR were established: one based on common CNV identified in the studied population (CNVR_POP), and another with CNV identified in sires with both sequence and SNP genotyping data available (CNVR_ANI). We found 10 CNVR_POP and 45 CNVR_ANI, which covered 1.05 Mb and 4.4 Mb of the bovine genome, respectively. Merging these CNV sets for functional analysis resulted in 48 unique high confidence CNVR. The overlapping genes were previously related to embryonic mortality, environmental adaptation, evolutionary process, immune response, longevity, mammary gland, resistance to gastrointestinal parasites, and stimuli recognition, among others. Our results contribute to a better understanding of the Gir breed genome. Moreover, the CNV identified in this study can potentially affect genes related to complex traits, such as production, health, and reproduction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biological Evolution
  • Cattle / genetics
  • DNA Copy Number Variations* / genetics
  • Genome*
  • Genotype
  • Multifactorial Inheritance
  • Polymorphism, Single Nucleotide

Grants and funding

LGB, RNW, and TMS. were supported by Coordination for the Improvement of Higher Education Personnel (CAPES - grant number 001). DPM has received a grant from National Council for Scientific and Technological Development (CNPq 431629/2016-1). MVGBS has received grants from Embrapa (Brazil) SEG 02.13.05.011.00.00 and CNPq 310199/2015–8 “Detecting signatures of selection from Next Generation Sequencing Data”, MCTI/CNPq/INCT-Ciência Animal and FAPEMIG CVZ PPM 00606/16 “Detecting signatures of selection in cattle from Next Generation Sequencing Data” appropriated projects. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.