Assessing genetic architecture and signatures of selection of dual purpose Gir cattle populations using genomic information

PLoS One. 2018 Aug 2;13(8):e0200694. doi: 10.1371/journal.pone.0200694. eCollection 2018.

Abstract

Gir is one of the main cattle breeds raised in tropical South American countries. Strong artificial selection through its domestication resulted in increased genetic differentiation among the countries in recent years. Over the years, genomic studies in Gir have become more common. However, studies of population structure and signatures of selection in divergent Gir populations are scarce and need more attention to better understand genetic differentiation, gene flow, and genetic distance. Genotypes of 173 animals selected for growth traits and 273 animals selected for milk production were used in this study. Clear genetic differentiation between beef and dairy populations was observed. Different criteria led to genetic divergence and genetic differences in allele frequencies between the two populations. Gene segregation in each population was forced by artificial selection, promoting isolation, and increasing genetic variation between them. Results showed evidence of selective forces in different regions of the genome. A total of 282 genes were detected under selection in the test population based on the fixation index (Fst), integrated haplotype score (iHS), and cross-population extend haplotype homozygosity (XP-EHH) approaches. The QTL mapping identified 35 genes associated with reproduction, milk composition, growth, meat and carcass, health, or body conformation traits. The investigation of genes and pathways showed that quantitative traits associated to fertility, milk production, beef quality, and growth were involved in the process of differentiation of these populations. These results would support further investigations of population structure and differentiation in the Gir breed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cattle
  • Chromosome Mapping
  • Genetic Variation
  • Genome*
  • Genomics / methods
  • Genotype
  • Haplotypes
  • Polymorphism, Single Nucleotide
  • Population Density
  • Principal Component Analysis
  • Selection, Genetic / genetics*
  • South America

Grants and funding

The authors would like to acknowledge the Foundation for Research Support of the State of São Paulo – FAPESP (grant number 2015/06686-7), the National Council for Scientific and Technological Development - CNPq (scholarship number 142373/2015-0) and the Brazilian Federal Agency for Support and Evaluation of Graduate Education - CAPES (scholarship number 88881.131671/2016-01) for support and the Institute of Animal Science (IZ), Sertãozinho, SP, for providing the data used in this study.