Abstract

Russian sheep breeds represent an important economic asset by providing meat and wool, whilst being adapted to extreme climates. By resequencing two Russian breeds from Siberia: Tuva (n=20) and Baikal (n=20); and comparing them with a European (UK) sheep outgroup (n=14), 41million variants were called, and signatures of selection were identified. High-frequency missense mutations on top of selection peaks were found in genes related to immunity (LOC101109746) in the Baikal breed and wool traits (IDUA), cell differentiation (GLIS1) and fat deposition (AADACL3) in the Tuva breed. In addition, genes found under selection owing to haplotype frequency changes were related to wool traits (DSC2), parasite resistance (CLCA1), insulin receptor pathway (SOCS6) and DNA repair (DDB2) in the Baikal breed, and vision (GPR179) in the Tuva breed. Our results present candidate genes and SNPs for future selection programmes, which are necessary to maintain and increase socioeconomic gain from Siberian breeds.

Highlights

  • High-frequency missense mutations on top of selection peaks were found in genes related to immunity (LOC101109746) in the Baikal breed and wool traits (IDUA), cell differentiation (GLIS1) and fat deposition (AADACL3) in the Tuva breed

  • Genes found under selection owing to haplotype frequency changes were related to wool traits (DSC2), parasite resistance (CLCA1), insulin receptor pathway (SOCS6) and DNA repair (DDB2) in the Baikal breed, and vision (GPR179) in the Tuva breed

  • Our results present candidate genes and SNPs for future selection programmes, which are necessary to maintain and increase socioeconomic gain from Siberian breeds

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Summary

Aberystwyth University

Publication date: 2020 Citation for published version (APA): Sweet-Jones, J., Yurchenko, A. Resequencing and signatures of selection scan in two Siberian native sheep breeds point to candidate genetic variants for adaptation and economically important traits.

Document License CC BY
Summary
Calcium ion transport Immunity
Findings
Supporting information
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