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Whole-genome analyses identify loci and selective signals associated with body size in cattle
Whole-genome analyses identify loci and selective signals associated with body size in cattle
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Whole-genome analyses identify loci and selective signals associated with body size in cattle
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Whole-genome analyses identify loci and selective signals associated with body size in cattle
Whole-genome analyses identify loci and selective signals associated with body size in cattle

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Whole-genome analyses identify loci and selective signals associated with body size in cattle
Whole-genome analyses identify loci and selective signals associated with body size in cattle
Journal Article

Whole-genome analyses identify loci and selective signals associated with body size in cattle

2020
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Overview
Abstract Body size plays a key role in production, health, selection, and environmental adaptation of animals, but the genetic basis of body size variation is not clearly understood. Here, we conducted genome-wide association studies (GWAS) of 15 body size traits using autosomal single nucleotide polymorphisms (SNPs) derived from whole-genome sequences of 31 Brahman cattle and 131 Yunling cattle and identified 20 significant loci, which implicated 18 candidate genes. For ischium width, the most significant SNP was assigned to LCORL, a famous gene controlling body size. For chest width, the most significant SNP was located upstream of BMP5, a secreted ligand of transformation growth factor-beta superfamily of proteins involved in bone and cartilage development. Subsequently, we detected selective sweeps in Brahman cattle using integrated Haplotype Score, composite likelihood ratio, and nucleotide diversity. The results showed CNTNAP5 locus associated with hip cross height and LIMCH1 locus associated with forehead size were in selective signals, which were consistent with higher hip cross height and higher forehead size in Brahman cattle compared with Yunling cattle. Our findings provide genetic insights into variation and selection of body size using GWAS and selective signals and will accelerate future efforts aimed at cattle improvement.