Identification of Genomic Variants and Candidate Genes for Reproductive Traits and Growth Traits in Pishan Red Sheep Using Whole-Genome Resequencing

Sheep have evolved remarkable phenotypic diversity through artificial and natural selection, with reproductive traits being pivotal for breeding economics. As a unique genetic resource, Pishan red sheep exhibit exceptional advantages, including perennial estrus, high fecundity, and stable hereditary characteristics, establishing them as an optimal model for investigating reproductive genetics. In this study, we performed whole-genome resequencing of Pishan red sheep, generating 9084.81 Gb of raw data and identifying 53,968,686 high-quality single-nucleotide polymorphisms (SNPs). Through selective sweep analysis, 92 genomic regions under selection were detected, containing 90 positional candidate genes significantly associated with growth, reproduction, and immune functions. Notably, we revealed BMPRIB, UNC5C, PDLIM5, GRID2, and HPGDS as core positional candidate genes influencing litter size, operating through the TGF-beta and Thyroid hormone signaling pathways. A genome-wide association study (GWAS) further identified 59 trait-related SNPs, including 39 loci linked to growth traits (affecting positional candidate genes such as PROM1, TAPT1, LDB2, and KIF16B) and 20 loci of positional candidate genes associated with reproductive traits (involving ASPA, RAP1GAP2, PHIP, and WDR82).These findings not only elucidate the molecular basis of superior reproductive performance in Pishan red sheep, but also provide functional markers for precision breeding.

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Journal
Biology
Published
2025-05-30
DOI
https://doi.org/10.3390/biology14060636
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
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article

Identification of Genomic Variants and Candidate Genes for Reproductive Traits and Growth Traits in Pishan Red Sheep Using Whole-Genome Resequencing

Yiming Sulaiman, Aladaer Qi, Mengting Zhu, Maimaitijiang Muhetapa
Biology
Genetic and phenotypic traits in livestock
article

Identification of Genomic Variants and Candidate Genes for Reproductive Traits and Growth Traits in Pishan Red Sheep Using Whole-Genome Resequencing

Yiming Sulaiman, Aladaer Qi, Mengting Zhu, Maimaitijiang Muhetapa
article en

Abstract

Sheep have evolved remarkable phenotypic diversity through artificial and natural selection, with reproductive traits being pivotal for breeding economics. As a unique genetic resource, Pishan red sheep exhibit exceptional advantages, including perennial estrus, high fecundity, and stable hereditary characteristics, establishing them as an optimal model for investigating reproductive genetics. In this study, we performed whole-genome resequencing of Pishan red sheep, generating 9084.81 Gb of raw data and identifying 53,968,686 high-quality single-nucleotide polymorphisms (SNPs). Through selective sweep analysis, 92 genomic regions under selection were detected, containing 90 positional candidate genes significantly associated with growth, reproduction, and immune functions. Notably, we revealed BMPRIB, UNC5C, PDLIM5, GRID2, and HPGDS as core positional candidate genes influencing litter size, operating through the TGF-beta and Thyroid hormone signaling pathways. A genome-wide association study (GWAS) further identified 59 trait-related SNPs, including 39 loci linked to growth traits (affecting positional candidate genes such as PROM1, TAPT1, LDB2, and KIF16B) and 20 loci of positional candidate genes associated with reproductive traits (involving ASPA, RAP1GAP2, PHIP, and WDR82).These findings not only elucidate the molecular basis of superior reproductive performance in Pishan red sheep, but also provide functional markers for precision breeding.

BiologyVol. 14(6)
Xinjiang Agricultural University (CN)
Openalex Percentile: Top 86%
Genetic and phenotypic traits in livestock
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Identification of Genomic Variants and Candidate Genes for Reproductive Traits and Growth Traits in Pishan Red Sheep Using Whole-Genome Resequencing — Yiming Sulaiman, Aladaer Qi, et al. · Biology (2025) | TGRS Research Map | TGRS