Simple Summary Improving milk yields and milk composition is a central objective of dairy goat breeding. This study compared conventional genomic prediction models, Bayesian regression models, and machine learning algorithms for three economically important traits in dairy goats: milk yield, milk fat percentage, and milk protein percentage. The results showed that the prediction accuracy depended jointly on the trait, genotyping strategy, statistical model, and type of biological prior information. Bayesian and gradient boosting methods were particularly useful for milk composition traits, whereas chip-based genotyping remained cost-effective for milk yield. These findings provide a practical framework for integrating machine learning, low-coverage whole-genome sequencing, SNP chip data, GWAS signals, and selection signature information into genomic selection programs for dairy goats.
Litter size is an economically important reproductive trait in dairy goats, but its genetic improvement remains challenging because of its complex genetic architecture and the influence of multiple environmental factors. This study aimed to identify genomic loci associated with litter size-related traits and to evaluate the potential of an intergenic variant near the candidate gene CTNND2 as a molecular marker in Saanen dairy goats. A total of 341 does with reproductive records were analyzed using a genome-wide association study (GWAS), followed by candidate SNP genotyping and association analysis. A shared association signal for litter size and live-born kid number was identified on chromosome 20, leading to the selection of the intergenic SNP CM048886.1:g.61357858G>A located near CTNND2 for further evaluation. Three genotypes (GG, AG, and AA) were detected, and the locus exhibited moderate genetic diversity (PIC = 0.27) while conforming to Hardy–Weinberg equilibrium. Association analysis revealed nominal associations between the SNP and both litter size (p = 0.0445) and live-born kid number (p = 0.0448), whereas no significant association was observed with average kid birth weight (p = 0.125). Goats carrying the A allele showed numerically higher litter size and live-born kid number than those carrying the G allele. These findings identify CM048886.1:g.61357858G>A, an intergenic variant near CTNND2, as a promising candidate marker for litter size-related traits in Saanen dairy goats and provide a foundation for future validation studies and the development of molecular breeding strategies to improve reproductive performance.
Jian-Qing Zhao, Shu-Hao Guo, Jian-Wu Li et al.· Veterinary Sciences· 0 citations
Leiwuqi yak is an important indigenous yak genetic resource distributed in eastern Tibet, but its genomic characteristics and adaptive evolutionary features remain poorly understood. In this study, whole-genome resequencing was performed on 110 Leiwuqi yaks, and these data were integrated with publicly available genomic data from other domestic and wild yak populations to investigate the genetic diversity, population structure, and candidate genomic regions potentially associated with local adaptation of Leiwuqi yak. After quality control and variant filtering, a total of 19,966,141 high-quality SNPs were identified across all samples. Most SNPs were located in intronic and intergenic regions, with a transition/transversion ratio of 2.47. Although sequencing depth differed between newly sequenced (3.87×) and public (9.04×) data, all samples were processed through a unified pipeline with stringent filtering criteria. Genetic diversity analyses showed that Leiwuqi yak retained relatively abundant nucleotide diversity, whereas runs of homozygosity and genomic inbreeding coefficient analyses suggested possible effects of local isolation or recent inbreeding. Population structure analyses based on principal component analysis and ADMIXTURE revealed that Chinese domestic yak populations shared a broadly similar genetic background with wild yak, whereas Indian yak exhibited clear genetic differentiation. Although Leiwuqi yak did not form a completely independent genetic cluster at the genome-wide level, selective sweep analysis identified localized genomic differentiation in this population. A total of 466 protein-coding genes were detected within candidate selected regions. Functional enrichment analyses showed that these genes were mainly associated with the Wnt signaling pathway, NF-kappa B signaling pathway, pathways in cancer, light absorption, and receptor-mediated endocytosis. These findings suggest that developmental regulation, immune and stress responses, environmental perception, and cellular homeostasis may contribute to the adaptive differentiation of Leiwuqi yak. Overall, this study provides new genomic evidence for understanding the genetic uniqueness and adaptive evolution of Leiwuqi yak and offers a scientific basis for its conservation and sustainable utilization.
Chenbo Shi, Lin Fu, Tengxiang Wang et al.· Frontiers in Veterinary Scie...· 0 citations
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