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This study focused on the changes in the composition and immune evolution in milk from birth to 144 h postpartum and the genes associated with the colostrum yield of Hu sheep. Twelve Hu sheep, which were bred carefully under animal health standards and have a litter size of two kids and similar gestation length (149 ± 1 days), were used. Lambs were transferred into their own cots to avoid interference. The compositional content (i.e., fat, protein, and lactose) and some other properties, including daily colostrum yield, DM, and SNF, were determined. In addition, immunity molecules (IgG, IgA, and IgM concentrations) received remarkable attention. The DM, SNF, fat, and protein contents were higher in the first days postpartum and then dropped quickly from the time of birth to 144 h postpartum. However, the lactose content displayed an increasing pattern and reached normal milk percentage at 48 h. The highest IgG (103.17 mg/mL), IgA (352.82 μg/mL), and IgM (2.79 mg/mL) colostrum concentrations were observed at partum, decreased quickly, and finally stabilized. The change law of concentration of IgA and IgM in colostrum are the same with IgG. Furthermore, the whole-genome resequencing was performed, and a missense variant locus in the SRC gene and two missense locus variants in the HIF1A gene were significantly associated with the colostrum yield of sheep by using the whole-genome selection signal detection analysis. In conclusions, colostrum contains abundant nutrients especially immunoglobulin, and the HIF1A gene may be used as candidate genes for colostrum yield, which has important information as a basic knowledge for the Hu sheep breeding program. [ABSTRACT FROM AUTHOR]

Detecting signatures of selection can provide a new insight into the mechanism of contemporary breeding and artificial selection and further reveal the causal genes associated to the phenotypic variation. However, the signatures of selection on genes entailing for profitable traits between Chinese commercial and indigenous goats have been poorly interpreted. We noticed footprints of positive selection at MC1R gene containing SNPs genotyped in five Chinese native goat breeds. An experimental distribution of FST was built based on approximations of FST for each SNP across five breeds. We identified selection using the high FST outlier method and found that MC1R candidate gene show evidence of positive selection. Furthermore, adaptive selection pressure on specific codons was determined using different codon based on maximum-likelihood methods; signature of positive selection in mammalian MC1R was explored in individual codons. Evolutionary analyses were inferred under maximum likelihood models, the HyPhy package implemented in the DATAMONKEY Web Server. The results of codon selection displayed positive diversifying selection at the sites were mainly involved in development of genetic variations in coat color in various mammalian species. Positive diversifying selection inferred with recent evolutionary changes in domesticated goat MC1R provides new insights that the gene evolution may have been modulated by domestication events in goats. [ABSTRACT FROM AUTHOR]

Beef is a major global source of protein, playing an essential role in the human diet. The worldwide production and consumption of beef continue to rise, reflecting a significant trend. However, despite the critical importance of beef cattle resources in agriculture, the diversity of cattle breeds faces severe challenges, with many breeds at risk of extinction. The initiation of the Beef Cattle Genome Project is crucial. By constructing a high-precision functional annotation map of their genome, it becomes possible to analyze the genetic mechanisms underlying important traits in beef cattle, laying a solid foundation for breeding more efficient and productive cattle breeds. This review details advances in genome sequencing and assembly technologies, iterative upgrades of the beef cattle reference genome, and its application in pan-genome research. Additionally, it summarizes relevant studies on the discovery of functional genes associated with key traits in beef cattle, such as growth, meat quality, reproduction, polled traits, disease resistance, and environmental adaptability. Finally, the review explores the potential of telomere-to-telomere (T2T) genome assembly, structural variations (SVs), and multi-omics techniques in future beef cattle genetic breeding. These advancements collectively offer promising avenues for enhancing beef cattle breeding and improving genetic traits.

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