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Genome-Wide Association Study of Body Weight Trait in Yaks
SIMPLE SUMMARY: The yak is the largest mammal in the Qinghai–Tibetan Plateau and also supplies necessary sources of food and finance for the Tibetan people. Their body weight is a valuable trait for breeding. In the traditional breeding processes, pedigree data were used to evaluate individual genet...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311934/ https://www.ncbi.nlm.nih.gov/pubmed/35883402 http://dx.doi.org/10.3390/ani12141855 |
Sumario: | SIMPLE SUMMARY: The yak is the largest mammal in the Qinghai–Tibetan Plateau and also supplies necessary sources of food and finance for the Tibetan people. Their body weight is a valuable trait for breeding. In the traditional breeding processes, pedigree data were used to evaluate individual genetic potency ability. However, based on the free range husbandry and random mating in domesticated yaks, the genetic improvement in yaks’ body weight is still very slow. In this study, we performed a genome-wide association study using whole genome sequencing data to detect the potential functional genes for body weight in yaks. In total three functional genes were identified as being associated with body weight. The results of this study are important for developing and improving body weight in yaks. ABSTRACT: The yak is the largest meat-producing mammal around the Tibetan Plateau, and it plays an important role in the economic development and maintenance of the ecological environment throughout much of the Asian highlands. Understanding the genetic components of body weight is key for future improvement in yak breeding; therefore, genome-wide association studies (GWAS) were performed, and the results were used to mine plant and animal genetic resources. We conducted whole genome sequencing on 406 Maiwa yaks at 10 × coverage. Using a multiple loci mixed linear model (MLMM), fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK), we found that a total of 25,000 single-nucleotide polymorphisms (SNPs) were distributed across chromosomes, and seven markers were identified as significantly (p-values < 3.91 × 10(−7)) associated with the body weight trait,. Several candidate genes, including MFSD4, LRRC37B, and NCAM2, were identified. This research will help us achieve a better understanding of the genotype–phenotype relationship for body weight. |
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