Genetic diversity and population structure of four Chinese rabbit breeds

PLoS One. 2019 Sep 16;14(9):e0222503. doi: 10.1371/journal.pone.0222503. eCollection 2019.

Abstract

There are a few well-known indigenous breeds of Chinese rabbits in Sichuan and Fujian provinces, for which the genetic diversity and population structure have been poorly investigated. In the present study, we successfully employed the restriction-site-associated DNA sequencing (RAD-seq) approach to comprehensively discover genome-wide SNPs of 104 rabbits from four Chinese indigenous breeds: 30 Sichuan White, 34 Tianfu Black, 32 Fujian Yellow and eight Fujian Black. A total of 7,055,440 SNPs were initially obtained, from which 113,973 high-confidence SNPs (read depth ≥ 3, calling rate = 100% and biallelic SNPs) were selected to study the genetic diversity and population structure. The mean polymorphism information content (PIC) and nucleotide diversity (π) of each breed slightly varied with ranging from 0.2000 to 0.2281 and from 0.2678 to 0.2902, respectively. On the whole, Fujian Yellow rabbits showed the highest genetic diversity, which was followed by Tianfu Black and Sichuan White rabbits. The principal component analysis (PCA) revealed that the four breeds were clearly distinguishable. Our results first reveal the genetic differences among these four rabbit breeds in the Sichuan and Fujian provinces and also provide a high-confidence set of genome-wide SNPs for Chinese indigenous rabbits that could be employed for gene linkage and association analyses in the future.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biodiversity
  • Breeding
  • China
  • Genetics, Population / methods
  • Genome / genetics
  • Linkage Disequilibrium / genetics
  • Polymorphism, Single Nucleotide / genetics*
  • Principal Component Analysis / methods
  • Rabbits
  • Sequence Analysis, DNA / methods

Grants and funding

This study was financially supported by the Earmarked Fund for China Agriculture Research System (CARS-44-A-2) and Science & Technology Department of Sichuan Province (2016NYZ0046). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.