Identification of selective sweeps reveals divergent selection between Chinese Holstein and Simmental cattle populations.

Minhui Chen,Qin Zhang,Jian-Feng Liu,Hongyan Ren,Li Jiang,Jinluan Fu,Dunfei Pan,Aiguo Wang,Junya Li,Guosheng Su

doi:10.1186/s12711-016-0254-5

Abstract

BackgroundThe identification of signals left by recent positive selection provides a feasible approach for targeting genomic variants that underlie complex traits and fitness. A better understanding of the selection mechanisms that occurred during the evolution of species can also be gained. In this study, we simultaneously detected the genome-wide footprints of recent positive selection that occurred within and between Chinese Holstein and Simmental populations, which have been subjected to artificial selection for distinct purposes. We conducted analyses using various complementary approaches, including LRH, XP-EHH and FST, based on the Illumina 770K high-density single nucleotide polymorphism (SNP) array, to enable more comprehensive detection.ResultsWe successfully constructed profiles of selective signals in both cattle populations. To further annotate these regions, we identified a set of novel functional genes related to growth, reproduction, immune response and milk production. There were no overlapping candidate windows between the two breeds. Finally, we investigated the distribution of SNPs that had low FST values across five distinct functional regions in the genome. In the low-minor allele frequency bin, we found a higher proportion of low-FST SNPs in the exons of the bovine genome, which indicates strong purifying selection of the exons.ConclusionsThe selection signatures identified in these two populations demonstrated positive selection pressure on a set of important genes with potential functions that are involved in many biological processes. We also demonstrated that in the bovine genome, exons were under strong purifying selection. Our findings provide insight into the mechanisms of artificial selection and will facilitate follow-up functional studies of potential candidate genes that are related to various economically important traits in cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0254-5) contains supplementary material, which is available to authorized users.

Highlights

The identification of signals left by recent positive selection provides a feasible approach for targeting genomic variants that underlie complex traits and fitness
A selective sweep rapidly increases the frequency of the favorable causal variant, and strong linkage disequilibrium (LD) persists between the causal variant and neighboring polymorphisms relative to neutral regions, which results in an unusually long-range haplotype with a high level of homozygosity [4, 5]
Population structure In the principal component analysis (PCA) analyses, after merging the Chinese Holstein population and the dataset downloaded from WIDDE, 2252 individuals with 34,533 single nucleotide polymorphism (SNP) remained; after merging the Chinese Simmental population and the dataset downloaded from WIDDE, 2252 individuals with 35,508 SNPs remained

Summary

Introduction

The identification of signals left by recent positive selection provides a feasible approach for targeting genomic variants that underlie complex traits and fitness. Chen et al Genet Sel Evol (2016) 48:76 selection with some economic purpose favor different variants in different regions, allele frequencies in such regions will differ greatly among populations [9]. To detect these genomic features that result from recent positive selection, various analytical methods have been proposed and successfully applied to many species. These approaches are largely considered as belonging to two different types. A composite method combining different detection approaches to provide complementary information was considered as an optimal strategy in searching for selection signatures with different features [6]

Methods

Results

Discussion

Conclusion