Genome-wide association study and scan for signatures of selection point to candidate genes for body temperature maintenance under the cold stress in Siberian cattle populations

Abstract

BackgroundDesign of new highly productive livestock breeds, well-adapted to local climatic conditions is one of the aims of modern agriculture and breeding. The genetics underlying economically important traits in cattle are widely studied, whereas our knowledge of the genetic mechanisms of adaptation to local environments is still scarce. To address this issue for cold climates we used an integrated approach for detecting genomic intervals related to body temperature maintenance under acute cold stress. Our approach combined genome-wide association studies (GWAS) and scans for signatures of selection applied to a cattle population (Hereford and Kazakh Whiteheaded beef breeds) bred in Siberia. We utilized the GGP HD150K DNA chip containing 139,376 single nucleotide polymorphism markers.ResultsWe detected a single candidate region on cattle chromosome (BTA)15 overlapping between the GWAS results and the results of scans for selective sweeps. This region contains two genes, MSANTD4 and GRIA4. Both genes are functional candidates to contribute to the cold-stress resistance phenotype, due to their indirect involvement in the cold shock response (MSANTD4) and body thermoregulation (GRIA4).ConclusionsOur results point to a novel region on BTA15 which is a candidate region associated with the body temperature maintenance phenotype in Siberian cattle. The results of our research and the follow up studies might be used for the development of cattle breeds better adapted to cold climates of the Russian Federation and other Northern countries with similar climates.Electronic supplementary materialThe online version of this article (10.1186/s12863-019-0725-0) contains supplementary material, which is available to authorized users.

Genetic Diversity and Signatures of Selection for Thermal Stress in Cattle and Other Two Bos Species Adapted to Divergent Climatic Conditions

“… Yang et al (2017) also identified the gene COL27A1 (found here in F ST 2 and ROH), which has been proposed to be involved in cartilage calcification, which is another important aspect in cold climates. Studying signatures of selection for candidate genes for body temperature maintenance under the cold stress in Siberian cattle populations, Igoshin et al (2019) found that the gene GRIA4 contribute to cold-stress resistance due to indirect involvement in body thermoregulation. In our study a gene from the same family ( GRIA1 ) was found for YAK in the F ST 3 and ROH scenarios.…”

“…For instance, a genomic evaluation for improved heat tolerance has been recently developed for Australian dairy cattle ( Nguyen et al, 2016 ). There is an increased interest in identifying and exploring signatures of selection (also known as selective sweeps) and the genomic diversity resulting from adaptation to environment and artificial selective pressure ( Igoshin et al, 2019 ; Osei-Amponsah et al, 2019 ; Upadhyay et al, 2019 ). Different approaches can be used to scan the genome for regions of homozygosity, as well as to estimate differences in the frequency of alleles or haplotypes between divergent populations or even generations within a population ( Boschiero et al, 2018 ; Ceballos et al, 2018 ).…”

Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle

“…From the multivariate envGWAS in Red Angus, 9 of the 16 positional candidate genes have been identified by previous studies of adaptation or selection in humans or cattle (DIRC1, ABCB1, TBC1D1, AP5M1, GRIA4, LRRC4C, RBMS3, GADL1, PLA2G12B) 89,113,114 . For example, GRIA4 has been identified as a target of selection in coldadapted Yakutian cattle populations 115 . Of the other 7 candidate genes, three have been previously associated with adaptive phenotypes; body size (E2F7, BBS1) and circadian rhythm (ADCYAP1).…”

Genome‐wide association study of shank length and diameter at different developmental stages in chicken F2 resource population

“…After detection of significant and suggestive SNPs, the positions of SNPs on the chicken reference genome (Gallus-Gallus 4.0) were identified by NCBI database. According to Yates et al (2015), the names of the genes in 250 kbp up and down regions of significant SNPs were detected from NCBI and Ensembl (Goor et al 2015;Mengmeng et al 2016;Igoshin et al 2019). In order to investigate molecular and biological functions of the identified candidate genes, the UniProt (Universal Protein Resource) database was searched (Pundir et al 2015) and the animal QTLdb database was used for finding the QTL in the candidate genomic regions (Hu et al 2015).…”