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Genome-Wide Association Study on Body Conformation Traits in Xinjiang Brown Cattle

Menghua Zhang, Yachun Wang, Qiuming Chen, Dan Wang, Xiaoxue Zhang, Xixia Huang, Lei Xu

2024International Journal of Molecular Sciences11 citationsDOIOpen Access PDF

Abstract

Body conformation traits are linked to the health, longevity, reproductivity, and production performance of cattle. These traits are also crucial for herd selection and developing new breeds. This study utilized pedigree information and phenotypic (1185 records) and genomic (The resequencing of 496 Xinjiang Brown cattle generated approximately 74.9 billion reads.) data of Xinjiang Brown cattle to estimate the genetic parameters, perform factor analysis, and conduct a genome-wide association study (GWAS) for these traits. Our results indicated that most traits exhibit moderate to high heritability. The principal factors, which explained 59.12% of the total variance, effectively represented body frame, muscularity, rump, feet and legs, and mammary system traits. Their heritability estimates range from 0.17 to 0.73, with genetic correlations ranging from −0.53 to 0.33. The GWAS identified 102 significant SNPs associated with 12 body conformation traits. A few of the SNPs were located near previously reported genes and quantitative trait loci (QTLs), while others were novel. The key candidate genes such as LCORL, NCAPG, and FAM184B were annotated within 500 Kb upstream and downstream of the significant SNPs. Therefore, factor analysis can be used to simplify multidimensional conformation traits into new variables, thus reducing the computational burden. The identified candidate genes from GWAS can be incorporated into the genomic selection of Xinjiang Brown cattle, enhancing the reliability of breeding programs.

Topics & Concepts

Genome-wide association studyHeritabilityBiologySingle-nucleotide polymorphismGeneticsGenetic associationQuantitative trait locusCandidate geneGenetic architectureGenetic correlationSelection (genetic algorithm)SNPBeef cattleGeneGenetic variationGenotypeArtificial intelligenceComputer scienceGenetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and AnimalsCancer-related molecular mechanisms research