Wool is produced and controlled by hair follicles (HFs). However, little is known about the mechanisms involved in HF development and regulation. Sheep dermal fibroblasts (SDFs) play a key role in the initial stage of HF development. Analyzing the molecular mechanism that regulates early HF development in superfine wool sheep is of great importance for better understanding the HF morphogenesis process and for the breeding of fine wool sheep. Here, we show that two microRNAs (miRNAs) affect the development of HFs by targeting two genes that are expressed by SDFs. Meanwhile, the overexpression and inhibition of oar-miR-23b and oar-miR-133 in SDFs cells and cell proliferation, apoptosis, and migration were further detected using a CCK-8 assay, an Annexin V-FITC assay, a Transwell assay, and flow cytometry. We found that oar-miR-23b, oar-miR-133, and their cotarget genes TGFβ2 and NOTCH1 were differentially expressed during the six stages of HF development in superfine wool sheep. Oar-miR-23b and oar-miR-133 inhibited the proliferation and migration of SDFs and promoted the apoptosis of SDFs through TGFβ2 and NOTCH1. oar-miR-23b and oar-miR-133 inhibited the proliferation and migration of SDFs by jointly targeting TGFβ2 and NOTCH1, thereby inhibiting the development of superfine wool HFs. Our research provides a molecular marker that can be used to guide the breeding of ultrafine wool sheep.

In this study, six different animal models were fitted, and the constrained maximum likelihood method was used to assess the genetic parameters and genetic trends of early growth traits in Luzhong mutton sheep. The experimental data of this study included the newborn weight (BWT, N = 2464), weaning weight (WWT, N = 2923), weight at 6 months of age (6WT, N = 2428), average daily weight gain from birth to weaning (ADG1, N = 2424), and average daily weight gain from weaning to 6 months of age (ADG2, N = 1836) in Luzhong mutton sheep (2015~2019). The best model for the genetic parameters of the five traits in Luzhong mutton sheep was identified as Model 4 using the Akaike information criterion (AIC) and likelihood ratio test (LRT) methods, in which the estimated values of direct heritability for the BWT, WWT, 6WT, ADG1, and ADG2 were 0.156 ± 0.057, 0.547 ± 0.031, 0.653 ± 0.031, 0.531 ± 0.035, and 0.052 ± 0.046, respectively, and the values for maternal heritability were 0.201 ± 0.100, 0.280 ± 0.047, 0.197 ± 0.053, 0.275 ± 0.052, and 0.081 ± 0.092, respectively. The genetic correlation between the ADG2 and WWT was negative, and the genetic and phenotypic correlations among the remaining traits were positive. In this study, maternal effects had a more significant influence on early growth traits in Luzhong mutton sheep. In conclusion, to effectively improve the accuracy of genetic parameter estimation, maternal effects must be fully considered to ensure more accurate and better breeding planning.

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.

Background: The Jining grey goat is a renowned local goat breed in China that has exceptional reproductive performance; thereby, it serves as an ideal animal model for studying prolificacy in goats. Recent research on the reproductive traits of Jining grey goats has focused primarily on variations in the expression of key genes, hormone regulatory mechanisms, and breeding techniques, with the aim of enhancing reproductive performance through molecular marker-assisted breeding. Methods: In this study, 8 healthy adult female Jining grey goats of similar age and weight were selected. Ovarian and uterine tissues were collected from Jining grey goats in the high litter size group (HL, high size ≥ 3 in three consecutive litters, n = 4) and the low litter size group (LL, litter size = 1 in three consecutive litters, n = 4) for transcriptome sequencing. Bioinformatics analysis was conducted to investigate key regulatory pathways and candidate genes in ovarian and uterine tissues. Ultimately, 5 pathways (cAMP signalling pathway, neuroactive ligand‒receptor interaction, ABC transporters, cytokine‒cytokine receptor interaction and metabolic pathways) and 10 candidate genes ( 3BHSD , CLSTN2 , BMP5 , DRD1 , CXCL14 , CFAP43 , WNT10B , ENO4 , GABRA1 and the DNAH1 gene) were revealed to be associated with multiple births in Jining grey goats. RT‒qPCR was used to verify the sequencing results, and the relative expression levels of the 10 candidate genes in different tissues were compared. Among them, 3BHSD , CLSTN2 , and GABRA1 were found to be closely related to prolificacy in the Jining grey goat. Conclusion: In this study, key regulatory pathways and candidate genes influencing the prolificacy of Jining Grey goats were investigated through transcriptome analysis, providing in-depth insights into the molecular mechanisms through which the expression of genes related to prolificacy in different tissues affects reproductive performance. These findings provide a theoretical foundation and reference for the selective breeding of Jining grey goats.

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.

Optimal litter size on goat farms is an important trait for production and economic efficiency. The ovary and uterus, key components of the reproductive system, play essential roles in reproductive performance. In recent years, numerous genes linked to goat reproductive performance have been identified. However, reliable marker genes that are specifically associated with litter size require further exploration. In this study, eight Jining Grey goats were divided into high-yield (n = 4) and low-yield (n = 4) groups on the basis of their kidding records to identify key regulatory genes associated with litter size. Ovarian and uterine tissues were collected during oestrus for RNA sequencing (RNA-seq). After two outlier uterine tissue samples were excluded, the remaining 14 samples were subjected to WGCNA and differential expression gene (DEG) analysis. A total of 1224 DEGs were identified (|log2(fold change) ≥ 1|, p ≤ 0.05), including 912 in ovarian tissues (monozygotic vs. polyzygotic, MO vs. PO) and 312 in uterine tissues (MU vs. PU). Through WGCNA, we identified 15 coexpression modules, among which four key modules were significantly correlated with litter size. Our analysis focused on the magenta and green modules, as they contained 11 and 3 candidate genes overlapping with the DEGs, respectively. Notably, three genes—FOXC1, FOSB, and FGL2—were found to play important roles in both ovarian and uterine tissues. These genes mainly participate in regulatory processes such as RNA polymerase II transcription factor activity, calcium ion binding, and extracellular space organization, highlighting their potential as key candidates for future research. Overall, we identified several gene modules associated with litter size in goats, providing potential molecular markers for investigating litter size traits in Jining Grey goats.