Background: Advances in genetic tools applied to livestock breeding has prompted research into the previously neglected breeds adapted to harsh local environments. One such group is the Welsh mountain sheep breeds, which can be farmed at altitudes of 300 m above sea level but are considered to have a low productive value because of their poor wool quality and small carcass size. This is contrary to the lowland breeds which are more suited to wool and meat production qualities, but do not fare well on upland pasture. Herein, medium-density genotyping data from 317 individuals representing 15 Welsh sheep breeds were used alongside the whole-genome resequencing data of 14 breeds from the same set to scan for the signatures of selection and candidate genetic variants using haplotype- and SNP-based approaches.
Results: Haplotype-based selection scan performed on the genotyping data pointed to a strong selection in the regions of GBA3, PPARGC1A, APOB, and PPP1R16B genes in the upland breeds, and RNF24, PANK2, and MUC15 in the lowland breeds. SNP-based selection scan performed on the resequencing data pointed to the missense mutations under putative selection relating to a local adaptation in the upland breeds with functions such as angiogenesis (VASH1), anti-oxidation (RWDD1), cell stress (HSPA5), membrane transport (ABCA13 and SLC22A7), and insulin signaling (PTPN1 and GIGFY1). By contrast, genes containing candidate missense mutations in the lowland breeds are related to cell cycle (CDK5RAP2), cell adhesion (CDHR3), and coat color (MC1R).
Conclusion: We found new variants in genes with potentially functional consequences to the adaptation of local sheep to their environments in Wales. Knowledge of these variations is important for improving the adaptative qualities of UK and world sheep breeds through a marker-assisted selection.
Bibliographical noteFunding Information:
Funding. The collection and sequencing of Russian sheep samples used in this study were funded by the Russian Scientific Foundation grant 19-76-20026 to DL. Resources from HPC Wales and Supercomputing Wales supported the contributions of VL and MS.
© Copyright © 2021 Sweet-Jones, Lenis, Yurchenko, Yudin, Swain and Larkin.