Whole-Genome Resequencing Reveals Population Structure and Loci Associated with Growth and Meat-Quality Traits in Meigu Yanying Chickens

Liangshan Meigu Yanying chicken is an indigenous high-altitude breed in Sichuan, China, but its population genetic structure and the genetic basis of key growth and meat-quality traits remain unclear. In this study, 211 Meigu Yanying chickens were whole-genome resequenced, and leg muscle weight, liver weight, leg muscle total protein content and leg muscle total cholesterol content were recorded at slaughter. After quality control, high-confidence single-nucleotide polymorphisms were used to analyze linkage disequilibrium, population structure and genome-wide associations. Linkage disequilibrium decayed rapidly with distance, and multivariate analyses indicated an overall homogeneous genetic background with only mild substructure and few closely related individuals. Genome-wide association studies for the four traits detected several significant or suggestive regions harboring biologically plausible candidate genes, including CPNE4, PLXNB2, SMAP1, SDHAF4, FAM135A, LCP1, MAPK15 and SCRIB. Gene Ontology enrichment showed that candidate genes for leg muscle weight and liver weight were mainly involved in cellular processes and tissue development, whereas those for leg muscle total cholesterol content were enriched in phosphorus metabolism and phosphate-containing compound metabolism. These results provide a genome-wide resource for Meigu Yanying chickens and lay a basis for conservation and genomic breeding aimed at improved growth performance, meat quality and nutritional value.

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Journal
Animals
Published
2026-02-09
DOI
https://doi.org/10.3390/ani16040540
Primary Topic
Livestock and Poultry Management
Type
article
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article

Whole-Genome Resequencing Reveals Population Structure and Loci Associated with Growth and Meat-Quality Traits in Meigu Yanying Chickens

B. Chen, Yaodong Hu, Tianyu Li, Silu Wang et al.
Animals
Livestock and Poultry Management
article

Whole-Genome Resequencing Reveals Population Structure and Loci Associated with Growth and Meat-Quality Traits in Meigu Yanying Chickens

B. Chen, Yaodong Hu, Tianyu Li, Silu Wang, Tang Shi, Caiyun Sun, Bei-yu Cai, Peng Ren
article en

Abstract

Liangshan Meigu Yanying chicken is an indigenous high-altitude breed in Sichuan, China, but its population genetic structure and the genetic basis of key growth and meat-quality traits remain unclear. In this study, 211 Meigu Yanying chickens were whole-genome resequenced, and leg muscle weight, liver weight, leg muscle total protein content and leg muscle total cholesterol content were recorded at slaughter. After quality control, high-confidence single-nucleotide polymorphisms were used to analyze linkage disequilibrium, population structure and genome-wide associations. Linkage disequilibrium decayed rapidly with distance, and multivariate analyses indicated an overall homogeneous genetic background with only mild substructure and few closely related individuals. Genome-wide association studies for the four traits detected several significant or suggestive regions harboring biologically plausible candidate genes, including CPNE4, PLXNB2, SMAP1, SDHAF4, FAM135A, LCP1, MAPK15 and SCRIB. Gene Ontology enrichment showed that candidate genes for leg muscle weight and liver weight were mainly involved in cellular processes and tissue development, whereas those for leg muscle total cholesterol content were enriched in phosphorus metabolism and phosphate-containing compound metabolism. These results provide a genome-wide resource for Meigu Yanying chickens and lay a basis for conservation and genomic breeding aimed at improved growth performance, meat quality and nutritional value.

AnimalsVol. 16(4)
Southwest University of Science and Technology (CN), Xichang University (CN)
Zero hunger
Openalex Percentile: Top 58%
Livestock and Poultry Management
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Whole-Genome Resequencing Reveals Population Structure and Loci Associated with Growth and Meat-Quality Traits in Meigu Yanying Chickens — B. Chen, Yaodong Hu, et al. · Animals (2026) | TGRS Research Map | TGRS