Genome-wide SNP discovery and evaluation of genetic diversity among six Chinese indigenous cattle breeds in Sichuan

PLoS One. 2018 Aug 8;13(8):e0201534. doi: 10.1371/journal.pone.0201534. eCollection 2018.

Abstract

Indigenous cattle in Sichuan Province, southwestern China, provide abundant genetic resources. However, their genetic diversity and population structure remain largely unknown, especially on the genome-wide scale. In the present study, we successfully employed the restriction site-associated DNA sequencing approach (RADseq) to explore genome-wide SNPs among six breeds of Sichuan cattle. A total of 238,725 high-confidence SNPs were finally obtained with a mean distance of 11,140 bp between two adjacent sites, and 43.4% were revealed to be novel in comparison with a public reference database of genetic variants. The mean nucleotide diversity and polymorphism information content (PIC) among all six breeds were 0.1878 and 0.1555, respectively. Pingwu and Ganzi cattle showed the highest and lowest genetic diversity, respectively. The inter-breed comparisons revealed that Ganzi and Ebian cattle were obviously separate from the others. Our reference set of genome-wide SNPs specific to indigenous cattle in Sichuan is the first of its kind. Moreover, our set can be used to investigate the genetic diversity and population structure and for genome-wide association studies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Breeding*
  • Cattle / genetics*
  • China
  • Genome-Wide Association Study / veterinary*
  • Polymorphism, Single Nucleotide / genetics*
  • Sequence Analysis, DNA

Associated data

  • figshare/10.6084/m9.figshare.6726791

Grants and funding

This study was financially supported by The Planning Subject of The Twelfth Five-Year-plan in National Science and Technology for The Rural Development in China (2015BAD03B04-3 to WW) and The Key Technology Research and Development Program of Sichuan Province (2015NZ0020 to WW). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.