From markers to mechanisms: a comprehensive review of major genes and quantitative trait loci shaping the modern sheep (Ovis aries)

Genomic Approaches for the Conservation and Improvement of Korean Native Chickens – A Review

Understanding the genomic basis of indigenous livestock is essential for both conservation and sustainable improvement. Korean native chickens (KNCs), although representing a small fraction of the poultry industry in Korea, are distinguished by their unique meat quality, robustness, and adaptability. Recent genomic studies have investigated their genetic diversity, evolutionary history, and economically important traits. High-density SNP arrays and population structure analyses have clarified the distinct identity of KNC lines, while runs of homozygosity have provided insights into inbreeding, conservation progress, and functional loci. Selection signature analyses have identified candidate genes related to growth, metabolism, reproduction, and immune function, reflecting line-specific adaptation. Genome-wide association studies have further identified variants associated with taste-active compounds, fatty acid composition, and growth traits, offering a foundation for genomic selection. Moreover, research on disease-related genes, such as the major histocompatibility complex B genes, has documented substantial genetic variability in KNCs, establishing important genomic resources for subsequent studies on avian immunity and pathogen response. Together, these findings highlight KNCs as valuable reservoirs of genetic variation with implications for both conservation and breeding. More broadly, the genomic insights obtained from KNCs provide a cautious yet informative model for indigenous livestock worldwide, demonstrating how genomic tools can support sustainable breeding programs that balance biodiversity preservation with productivity.

Identification of candidate genes for reproductive traits in Chinese Holstein cattle using single-step genome-wide association study.

In dairy farming, reproductive efficiency is vital to both profitability and sustainability. However, years of selective breeding for increased milk yield have adversely affected reproductive potential. This study aimed to pinpoint genomic regions and identify potential candidate genes associated with reproductive traits in Chinese Holstein cattle. In this study, a single-step genome-wide association study (ssGWAS) was conducted using 33,202 phenotypic records from 16,379 animals, 55,244 pedigree records, and genomic data from 1,698 cows. These data were integrated into the ssGWAS analysis, resulting in a total pedigree structure of 21,635 animals. A total of 12 significant markers were identified for calving interval (IC), days open (DO), number of services per conception (NS), and conception rate (CR). Among these significant SNPs, 3 SNPs were for IC, 2 SNPs were for DO, 3 SNPs were for NS, and 4 SNPs were for CR. Several promising candidate genes located near these SNPs have been identified, including SFXN4, B3GAT2, GRK5, PRDX3, and MTHFD1L, highlighting their potential involvement in fertility-related biological processes. Furthermore, functional enrichment analysis identified significant enrichment of pathways associated with cell adhesion and embryonic development, suggesting a potential mechanistic role for DSG family members (DSG1, DSG2, DSG3, and DSG4) in fertility regulation. Collectively, our findings enhance understanding of the complex genetic basis of reproductive traits in dairy cattle and may offer a valuable set of genomic targets for precision breeding of Chinese Holsteins. Integrating these markers into genomic selection programs may contribute to genetic improvements in reproductive efficiency and support the long-term sustainability of dairy production.

Development and application of SNP chips in goat breeding: a mini review

Goats (Capra hircus) are among the world’s most important livestock, providing milk, meat, and fiber across diverse agro-ecological zones. Traditional breeding relying on pedigree-based estimated breeding values (EBVs) has driven steady genetic progress but is constrained by long generation intervals and limited accuracy for sex-limited or difficult-to-measure traits. High-throughput single nucleotide polymorphism (SNP) chips and genomic selection (GS) have transformed goat breeding by enabling early, accurate selection independent of phenotypic records. This review synthesizes the development of goat SNP chip platforms from the foundational 52 K GoatSNP50 BeadChip through high-density solid-phase arrays and low-cost liquid-phase capture panels, with emphasis on their relative performance, cost-effectiveness, imputation potential, and suitability for different breeding systems. In addition to genomic selection (GS), genome-wide association studies (GWAS), and genetic diversity assessment, we also discuss candidate-gene selection and marker-assisted selection (MAS) as practical intermediate approaches that remain relevant in many goat breeding programs. GS has achieved genomic estimated breeding value (GEBV) prediction accuracies of 0.35–0.79 for key production traits across multiple countries and breeds. GWAS has identified candidate genes for milk composition (DGAT1, CSN1S1), growth (PLAG1, HMGA2), reproduction (BMPR1B, GDF9), and fiber quality (KRT, KRTAP families). We compare GS with traditional BLUP-based approaches, assess economic benefits, and discuss key challenges including reference population construction, genotype imputation, inbreeding management via Optimum Contribution Selection (OCS), and multi-omics integration. Future directions include customized chip design, AI-assisted genomic prediction, climate adaptation breeding, and CRISPR/Cas9 gene editing for precision improvement.

Identifying selection signatures associated with production traits in Matou goats using whole-genome sequencing

Abstract Investigating the genetic attributes of indigenous goat breeds is crucial for their conservation and breeding. The Matou goat, a valued native breed of Southern China, is characterized by high meat quality and reproductive efficiency, representing an important genetic resource for livestock production. Its genetic basis underlying productive traits remains unclear at the whole-genome level. Therefore, this study aimed to elucidate its genomic diversity and selection signatures with whole-genome sequencing (WGS), in order to provide a basis for its future conservation and breeding. Population structure analyses, including principal component analysis, phylogenetic tree construction, and admixture analysis, revealed that the 128 sampled individuals could be divided into two subgroups. One subgroup exhibited greater genetic diversity, as reflected by higher heterozygosity and lower inbreeding coefficients, along with a higher frequency of private alleles indicative of a more closed breeding history. The slower linkage disequilibrium decay observed in this subgroup suggests it has undergone stronger selection. By integrating Fst, XP‑CLR, and XP‑EHH analyses, we identified 215 genes within 306 candidate regions under selection. Several of these genes (ARHGAP31, CHURC1, ITGA11, and GFOD1) harbor variants that overlap with QTLs and are associated with production traits in livestock. These findings provide a basis for conservation and breeding of the Matou goat.

Molecular Genetic Markers in the Studies of Conifer Species

Integrating selective signature analysis and genome-wide association study to identify candidate genes associated with litter size in Leizhou goat （A revised version）.

Objective Litter size is a key trait for evaluating reproductive performance of goats, which can directly influence the breeding efficiency and profitability of production cycles. However, a comprehensive understanding of its genetic architecture, including the causative mutations and their functional impacts, remains scarce, thus hindering its application in precision breed-ing. Methods A total of 92 female Leizhou goats were genotyped through whole-genome se-quencing (WGS), and their litter size were measured for three consecutive births. Subsequently, based on the genotype and phenotype data, population genetic structure analysis, selection signature analysis, and genome-wide association study (GWAS) were performed. Results We identified a total of 20,802,514 SNPs in the 92 Leizhou goats. Analysis of genetic structure revealed that the high-litter-size group exhibited greater genetic diversity than the low-litter-size group, although no significant genetic differentiation was detected between them. We identified 340 putative selective regions and 346 candidate genes across the genome. A total of 37 candidate genes were identified as being closely associated with reproductive traits, including BMP6, MAPK8, RPTOR, etc. In GWAS results, we identified 63 quantitative trait loci (QTLs) for litter size at suggestive significance (P＜1×10-5). After, 207 candidate genes were annotated, and 4 of them were highlighted that have been previously reported to be associated with reproductive processes (e.g., TMEM100, PDGFD, NLRP9, and ARHGAP22). By integrating the results from both approaches, we identified MAPK8 as a potential candidate gene associated with litter size. Furthermore, our findings from motif recognition, transcrip-tion factor prediction, and previous studies lead us to propose that the BMP6-GATA4-MAPK8 signaling pathway may play a key role in regulating litter size in goats. Conclusion Our findings identify several candidate genes and putative associated variants for litter size, providing valuable insights into the genetic basis of reproductive traits in goats.