The Xinjiang Brown cattle (XJBC) is one of China’s five major dual-purpose dairy and beef breeds. Analyzing the genetic diversity of the Xinjiang Brown cattle population lays the theoretical groundwork for identifying and conserving its genetic resources. This study employed the Illumina Bovine SNP 150K chip to analyze genetic diversity, inbreeding coefficient, kinship, and genetic distance in a population of 750 Xinjiang Brown cattle from three breeding farms in Xinjiang. Genetic diversity was assessed by calculating minimum allele frequency (MAF), observed heterozygosity (Ho), expected heterozygosity (He), polymorphic information content (PIC), and linkage disequilibrium (LD). Population structure was analyzed using PCA. ROH was calculated to derive ROH-based inbreeding coefficients, pedigree-based inbreeding coefficients (F_PED) were estimated using CFC software for comparison, and candidate genes within high-frequency ROH regions in Xinjiang Brown cattle were identified. A G matrix was constructed to analyze population kinship. Results revealed 94,173 high-quality SNP loci in Xinjiang Brown cattle, with an average MAF of 0.276, PIC of 0.376, Ho of 0.345, and He of 0.376. Breeding farm 3 exhibited the fastest LD decay, indicating relatively high genetic diversity across Xinjiang Brown cattle populations, with farm 3 demonstrating greater diversity. The IBS genetic distance was 0.313. The G matrix results aligned with the IBS distance matrix, both indicating close kinship among some individuals within the Xinjiang Brown cattle population. The ranges for average F_PED and average F_ROH across farms were 0.0017–0.0189 and 0.0609–0.0878, respectively. Short ROH segments (0.5–2 Mb) constituted the largest proportion (51.31%) of all ROHs. Within high-frequency ROH enrichment regions, 61 genes, including LCORL, FAM110B, NR4A1, and PER2, were identified as potentially associated with economic traits in Xinjiang Brown cattle. These findings provide relevant marker sites for genomic selection in Xinjiang Brown cattle and lay a theoretical foundation for subsequent research.

The aim of this research was to employ 16S rRNA high-throughput sequencing to thoroughly explore the interplay between milk and hindgut microbial communities and the effects of microorganisms in milk and the hindgut on the dairy quality of XJBC and CSC. In this study, 96 XJBC milk samples, 94 XJBC hindgut samples, 100 CSC milk samples, and 93 CSC hindgut samples were collected for microbial community analysis. The 16S rRNA sequencing data revealed that the microbial species richness in the milk of CSC exceeded that of XJBC, whereas the opposite was true for the hindgut microbial communities. A chi-square test was conducted using SPSS 19.0. The milk and posterior intestinal microbiota between individuals were analyzed with the Pearson chi-square test, maximum likelihood ratio, and Fisher’s exact test. Nongenetic factors substantially influenced microbial community dynamics in both milk and the hindgut. In the milk of dairy cows, a significant negative correlation was observed between one genus and milk protein production. Nine genera were significantly negatively correlated with milk fat production, whereas one genus was positively correlated. Additionally, six genera were negatively correlated with lactose production, and two genera exhibited positive correlations. Notably, Phascolarctobacterium and Turicibacter were identified as genera originating from the hindgut, which led to reduced milk quality. In the hindgut microbial community of dairy cows, seven genera were significantly negatively associated with milk fat production, whereas one genus was positively associated with milk fat production. These findings indicate that certain mammary microorganisms may migrate from the hindgut, either endogenously or exogenously, disrupting the equilibrium of the mammary microbial community in dairy cows and potentially leading to inflammation. By enhancing feeding conditions and standardizing production practices, the invasion of harmful flora into mammary tissues can be minimized, reducing the risk of inflammation and thereby preserving the health of dairy cows and enhancing milk quality.

This study aims to elucidate the population structure and genetic diversity of Xinjiang brown cattle (XJBC) and Chinese Simmental cattle (CSC) while conducting genome-wide selective signatures analyses to identify selected genes associated with milk production traits in both breeds. Based on whole-genome resequencing technology, whole-genome single nucleotide polymorphisms (SNPs) of 83 Xinjiang brown cattle and 80 Chinese Simmental cattle were detected to resolve the genetic diversity and genetic structure of the two populations, whole-genome selective elimination analysis was performed for the two breeds of cattle using the fixation index (F_st) and nucleotide diversity (θπ ratio), and enrichment analysis was performed to explore their biological functions further. Both breeds exhibited relatively rich genetic diversity, with the Chinese Simmental cattle demonstrating higher genetic diversity than Xinjiang brown cattle. The IBS and G matrix results indicated that most individuals in the two populations were farther apart from each other. The PCA and neighbor-joining tree revealed no hybridization between the two breeds, but there was a certain degree of genetic differences among the individuals in the two breeds. Population structure analysis revealed that the optimal number of ancestors was three when K = 3. This resulted in clear genetic differentiation between the two populations, with only a few individuals having one ancestor and the majority having two or three common ancestors. A combined analysis of F_st and θπ was used to screen 112 candidate genes related to milk production traits in Xinjiang brown cattle and Chinese Simmental cattle. This study used genome-wide SNP markers to reveal the genetic diversity, population structure, and selection characteristics of two breeds. This study also screened candidate genes related to milk production traits, providing a theoretical basis for conserving genetic resources and improving genetic selection for milk production traits in Xinjiang brown cattle and Chinese Simmental cattle.

Xinjiang Brown cattle is an elite dual-purpose breed (raised for dairy and beef) developed in China. To elucidate its genomic architecture, we conducted whole-genome resequencing of 169 Xinjiang Brown cattle, followed by structural variation (SV) detection and a genome-wide association study (GWAS). We identified 71,668 SVs, among which deletions were the most prevalent, followed by translocations, inversions, duplications, and insertions. We further identified 1286 high-frequency SVs involving 2016 protein-coding genes. Through functional enrichment analysis of these genes, we revealed associations of genetic variation at genomic positions near genes implicated in immune response and disease resistance (NFKBIZ and PTPRT), growth and development (HDAC4 and MEF2A), and milk production (TP63, FABP4, and MEF2A). GWAS analysis of 31 body conformation traits revealed 58 SVs significantly associated with five traits (chest width, rear udder width, udder depth, rump width, and heel depth) at the genome-wide level. Additionally, nine candidate genes (CLINT1, EBF1, PAM16, GRIP1, CFAP54, SLC22A16, DOK5, ETAA1, and IPMK) were identified as potentially involved in the genetic regulation of body conformation traits. These findings provide novel insights for genetic improvement strategies and indicate that precision breeding could further enhance the production performance of this breed in the future.

Chinese Simmental cattle are a high-quality breed developed through long-term crossbreeding and selection after their introduction into China and have become the main dual-purpose cattle population in the Xinjiang region. To deeply dissect the population structure, characteristics of the population structure, and the genetic basis of the twinning trait, this study focused on Xinjiang Chinese Simmental cattle as the main research subject. It integrated genomic data from global public databases to systematically conduct population structure analysis, genetic relationship analysis, and genome-wide selection signature analysis. Population genetic analysis revealed that the IBS matrix and G matrix indicated that some individuals from different geographical origins exhibited distant genetic relationships; the Xinjiang population showed the fastest LD decay, suggesting abundant genetic diversity; the inbreeding coefficient based on Runs of Homozygosity (ROH) across populations ranged from 0.036 to 0.063; principal component analysis and phylogenetic tree showed that some individuals from different geographical origins had certain genetic interconnections; admixture analysis indicated that K = 5 was the optimal model, with each population exhibiting clear genetic differentiation and admixture characteristics. Furthermore, by combining F_st and θπ analysis (comparing the Xinjiang population with other geographical populations), a total of 89 candidate genes associated with the twinning trait in Xinjiang Chinese Simmental cattle were screened, including CYP19A1, HORMAD1, GRB14, CADM2, CXCR4, and others that have been reported to be closely related to oogenesis and reproductive function. In summary, this study explores genome-wide genetic differences among Simmental cattle populations from different regions, deepens our understanding of their population structures, and offers new candidate genes and molecular markers for high-fecundity breeding in Simmental cattle.

The litter size of goats is a key factor affecting their reproductive performance. The ovary plays a central role in the reproductive process of goats. How