Background: Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features. Results: We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model. Conclusions: A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

Background: The historical importation of Chinese pigs into Western countries has facilitated the introduction of Chinese haplotypes into European pig breeds, thereby shaping their genetic diversity and phenotypic traits. However, the genetic and biological implications of this introgression remain poorly understood. Results: Based on SNP chip and resequencing data, we confirmed significant genetic introgression from Chinese pigs into commercial European lines. The genetic origins of the introgressed segments predominantly derive from Southern Chinese domestic pigs (CSDP), with additional contributions from other populations, such as Eastern Chinese domestic pigs (CEDP). Our study demonstrates that the selection pressure for Chinese pig introgression was stronger in Duroc pigs compared to the Large White and Landrace breeds. Based on ancestral haplotypes from CEDP and CSDP, we conducted a genome-wide association study (GWAS) and identified 10 quantitative trait loci (QTLs), five of which were not identified in previous studies or using SNPs. Expression genome-wide association studies (eGWAS) based on these introgressed haplotypes, using gene expression profiles from the duodenum, liver, and muscle tissues in the Duroc population, revealed eGWAS signals that were enriched near transcript start sites. By integrating GWAS signals for loin muscle depth with eGWAS signals in muscle tissue, we confirmed that a region 300 Kb from TAF11 , which is enriched with open chromatin regions and encompasses a super-enhancer located within the same topologically associating domain as TAF11 , was associated with both TAF11 expression and loin muscle depth, highlighting the profound influence of Chinese introgression. Conclusions: These findings offer valuable insights into the genetic influences of Chinese pig introgression on the Duroc breed, as well as the molecular basis for its effects on economically important traits in Duroc pigs.

The Diqing Tibetan pig (DQTP) is a local breed in China, renowned for its high adaptation to plateau climates. However, it has undergone less human selection compared to modern commercial pigs, resulting in smaller but a wide range of body sizes and meat production within its population. The cellular transcriptional variation in this breed related to muscle phenotypes remains unexplored. In this study, we performed single-nucleus transcriptome analysis to investigate the muscle cell profiles of 6-month-old pigs with differing body sizes. Cell clustering analysis indicated muscle cells can be categorized into myogenic lineages (myocytes and satellite cells), fibro-adipogenic progenitors (FAPs), endothelial and vascular-related cells (EVRCs), and immune cells (both myeloid and lymphoid). The composition of cell types reflected subtypes of myocytes and mitochondrial metabolism-related FAPs and endothelial cells, with significant differences observed among cell subtypes. We discovered some genes with cell subtype-specific differential expression levels, such as TECRL and MYOZ2 (slow-twitch muscle), and MYL1, AMPD, and FILIP1L (Myocyte-like FAPs). Additionally, ligand-receptor analysis identified significantly stronger cell interaction activities in larger DQTP pigs, suggesting a potential association with the observed the body size variation. The pathways involving COLLAGEN, LAMININ, and PTPRM, which are crucial for extracellular matrix organization and adhesion, were mostly enriched in interactions between FAPs and EVRCs. This work provides a comprehensive overview of muscle-resident cell profiles and identifies differences in cell type composition, cellular gene expression levels, and cell communication intensity in DQTP, which may enhance the understanding of the mechanisms underlying discrepancies in porcine muscle growth.

Domestic cattle represent one of the most significant evolutionary successes in the history of human–animal mutualism. This review synthesizes evidence from paleogenomics and modern population genetics, particularly recent pangenome analyses, to reconstruct a comprehensive evolutionary trajectory of cattle. We outline the two domestication events: the emergence of taurine cattle (Bos taurus) in the Fertile Crescent (~10,500 years ago) and zebu cattle (Bos indicus) in the Indus Valley (~8000 years ago). Following domestication, cattle dispersed globally alongside human migration, resulting in a complex genetic mosaic shaped by introgression with wild relatives and extensive admixture between lineages. By integrating data from mitochondrial DNA, Y-chromosome haplotypes, and whole-genome sequencing of modern, ancient, and wild samples, we reconstruct the detailed global dispersal of cattle. Furthermore, we dissect the molecular mechanisms underlying phenotypic diversity, emphasizing how natural selection has driven environmental adaptation, how artificial selection has optimized production traits, and how the emerging bovine pangenome is unveiling “hidden” genetic variations critical for climate resilience and disease resistance. Ultimately, this review summarizes the origin, dispersal, and genomic diversity of cattle, offering vital insights for the conservation of indigenous genetic resources and the advancement of molecular breeding strategies in the face of a changing global climate.

This study investigates the genetic diversity, population structure, and adaptive differentiation of Yunnan native cattle (YNC) using whole-genome SNP data from 457 individuals, representing eight cattle populations and two closely related bovine species (Zhongdian yak and Dulong gayal). Genetic diversity analyses revealed a distinct latitudinal gradient from north to south, with the highest diversity observed in the northern Diqing (DQC) and Zhaotong (ZTC) populations. The observed population structure was largely consistent with geographic distribution, identifying distinct ancestral components and complex admixture patterns. Genome-wide selective sweep scans revealed several key candidate genes underlying local adaptation. Notably, GRIA4 and DUOXA2 were associated with cold tolerance in northern populations, and ST3GAL3 and MST1 were implicated in heat stress adaptation in southern populations. Genome-wide balancing selection analyses further detected significant loci, such as MGST1 and SLC36A1, where divergent haplotype frequencies reflected differential selective pressures on milk-related traits between northern and southern populations. Additionally, we detected signals of historical introgression from Zhongdian yak into DQC cattle, highlighting the introgressed gene SLIT3 as a potential candidate associated with high-altitude thermogenesis. Collectively, these results provide a comprehensive genomic framework for the management and conservation of indigenous bovine genetic resources in Southwest China.

A genome-wide association study (GWAS) of daughter pregnancy rate (DPR) was conducted using 75,133 SNPs and 40,203 first lactation crossbred dairy cows mostly from Jersey–Holstein crosses. The GWAS analysis detected 6528 additive effects, 65 dominance effects, 1638 additive × additive (A × A) effects, 3 additive × dominance effects, and 18 intra-chromosome dominance × dominance (D × D) effects. Of the 1638 A × A effects, 1634 were intra-chromosome and four were inter-chromosome A × A effects. The distance between two SNPs with intra-chromosome epistasis effects was in the range of 3.61 Kb to 2.68 Mb, and many interacting SNP pairs were within the same genes. The additive and A × A effects were distributed on all chromosomes showing genome-wide involvement in DPR heterosis. The dominance and D × D effects all had homozygous advantages and heterozygous disadvantages. The GWAS results identified four genetic mechanisms underlying DPR heterosis in crossbred dairy cows: complementary additive effects from different breeds and new additive effects due to cross breeding, two-locus allelic interactions between loci and between breeds, within-locus allelic interactions between breeds, and genotype × genotype interactions enabled by allelic interactions between breeds. Results in this study provided a novel understanding about the genetic factors and mechanisms underlying DPR heterosis in crossbred dairy cows.