Background: Characterization of the molecular mechanisms underlying hair follicle development is of paramount importance in the genetic improvement of wool-related traits in sheep and skin-related traits in humans. The Merino is the most important breed of fine-wooled sheep in the world. In this study, we systematically investigated the complexity of sheep hair follicle development by integrating transcriptome and methylome datasets from Merino sheep skin.Results: We analysed 72 sequence datasets, including DNA methylome and the whole transcriptome of four gene types, i.e. protein-coding genes (PCGs), lncRNAs, circRNAs, and miRNAs, across four embryonic days (E65, E85, E105, and E135) and two postnatal days (P7 and P30) from the skin tissue of 18 Merino sheep. We revealed distinct expression profiles of these four gene types across six hair follicle developmental stages, and demonstrated their complex interactions with DNA methylation. PCGs with stage-specific expression or regulated by stage-specific lncRNAs, circRNAs, and miRNAs were significantly enriched in epithelial differentiation and hair follicle morphogenesis. Regulatory network and gene co-expression analyses identified key transcripts controlling hair follicle development. We further predicted transcriptional factors (e.g. KLF4, LEF1, HOXC13, RBPJ, VDR, RARA, and STAT3) with stage-specific involvement in hair follicle morphogenesis. Through integrating these stage-specific genomic features with results from genome-wide association studies (GWAS) of five wool-related traits in 7135 Merino sheep, we detected developmental stages and genes that were relevant with wool-related traits in sheep. For instance, genes that were specifically upregulated at E105 were significantly associated with most of wool-related traits. A phenome-wide association study (PheWAS) demonstrated that candidate genes of wool-related traits (e.g.SPHK1,GHR,PPP1R27,CSRP2,EEF1A2, andPTPN1) in sheep were also significantly associated with dermatological, metabolic, and immune traits in humans.Conclusions: Our study provides novel insights into the molecular basis of hair follicle morphogenesis and will serve as a foundation to improve breeding for wool traits in sheep. It also indicates the importance of studying gene expression in the normal development of organs in understanding the genetic architecture of economically important traits in livestock. The datasets generated here are useful resources for functionally annotating the sheep genome, and for elucidating early skin development in mammals, including humans.

Mastitis causes serious economic losses in the dairy industry, but there are no effective treatments or preventive measures. In this study, the ZRANB3, PIAS1, ACTR3, LPCAT2, MGAT5, and SLC37A2 genes in Xinjiang brown cattle, which are associated with mastitis resistance, were identified using a GWAS. Pyrosequencing analysis showed that the promoter methylation levels of the FHIT and PIAS1 genes in the mastitis group were higher and lower, respectively, than those in the healthy group (65.97 ± 19.82% and 58.00 ± 23.52%). However, the methylation level of the PIAS1 gene promoter region in the mastitis group was lower than that in the healthy group (11.48 ± 4.12% and 12.17 ± 4.25%). Meanwhile, the methylation levels of CpG3, CpG5, CpG8, and CpG15 in the promoter region of the FHIT and PIAS1 genes in the mastitis group were significantly higher than those in the healthy group (p < 0.01), respectively. RT-qPCR showed that the expression levels of the FHIT and PIAS1 genes were significantly higher in the healthy group than those in the mastitis group (p < 0.01). Correlation analysis showed that the promoter methylation level of the FHIT gene was negatively correlated with its expression. Hence, increased methylation in the promoter of the FHIT gene reduces the mastitis resistance in Xinjiang brown cattle. Finally, this study provides a reference for the molecular-marker-assisted selection of mastitis resistance in dairy cattle.

Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h² values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

Sheep are a vital species in the global agricultural economy, providing essential resources such as meat, milk, and wool. Merino sheep (Junken type) are a key breed of fine wool sheep in China. However, research on fine wool traits has largely overlooked the role of SNPs and their association with phenotypes. Copy number variations (CNVs) have emerged as one of the most important sources of genetic variation, influencing phenotypic traits by altering gene expression and dosage. To generate a comprehensive CNVR map of the ovine genome, we conducted genome-wide CNV detection using genotyping data from 285 fine wool sheep. This analysis revealed 656 CNVRs, including 628 on autosomes and 28 on the X chromosome, covering a total of 43.9 Mbs of the sheep genome. The proportion of CNVRs varied across chromosomes, from 0.45% on chromosome 26 to 3.72% on chromosome 10. Functional annotation through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses highlighted significantly enriched GO terms, including odorant binding, ATP binding, and sulfuric ester hydrolase activity. The KEGG analysis identified involvement in pathways such as neuroactive ligand–receptor interaction, axon guidance, ECM–receptor interaction, the one-carbon pool by folate, and focal adhesion (p < 0.05). To validate these CNVRs, we performed quantitative real-time PCR experiments to verify copy number predictions made by PennCNV software (v1.0.5). Out of 11 selected CNVRs with predicted gain, loss, or gain–loss statuses, 8 (IDs 68, 156, 201, 284, 307, 352, 411, 601) were successfully confirmed. This study marks a significant step forward in mapping CNVs in the ovine genome and offers a valuable resource for future research on genetic variation in sheep.

Composting serves as a pivotal technology for recycling livestock manure and reducing antibiotic resistance genes (ARGs). However, optimizing only its physicochemical properties or microbial community yields limited success in ARG removal. In contrast, persulfate radical-driven advanced oxidation processes (AOPs) have proven highly effective in eliminating ARGs. This study demonstrates that the biological heat generated during composting can activates persulfate, not only boosting the ARGs removal rate to 96% but also effectively suppressing the rebound and re-enrichment of ARGs during the compost maturation stage, maintaining a removal rate of 55%. Specifically, this approach reduces the abundances of mobile genetic elements (MGEs, e.g., intI2, IncQ-oriV) and target ARGs (tetA, tetQ, strA, sul3). The mechanisms underlying ARG removal involve two key aspects: First, strong oxidative radicals produced by persulfate activation directly oxidize and damage resistant bacteria, thereby decreasing the abundances of ARGs and MGEs. Second, persulfate primarily inhibits ARGs transmission by reshaping the bacterial community structure. In traditional composting, non-host core bacteria act as "bridges" connecting distinct microbial modules, directly facilitating inter-modular ARGs transmission. Dominant genera such as Bacillus, norank_f__Limnochordaceae, Marinimicrobium, and Tepidimicrobium mainly carry key MGEs (intI2, Tn916/1545, tnpA, IS613), which further amplify the risk of ARGs dissemination. In contrast, following persulfate addition, only Truepera is detected as a non-host core bacterium, significantly reducing cross-module ARGs transmission pathways. This study offers a promising regulation strategy for mitigating ARG-related risks during composting.

Due to the mycelial structure and extracellular secretions of fungi, fungal communities have been found to have a potential role in the spread of antibiotic resistance genes (ARGs) in soil and other environments. However, the effect of fungi on bacterial hosts and resistance genes during facultative composting remains unclear. Therefore, a fungal inhibition experiment was conducted to explore this effect. The results showed that with the addition of fungicides (cycloheximide), the activity of culturable fungi gradually decreased, but there was no significant effect on bacteria. The decrease in the abundance of active fungi that can promote bacterial activity and diffusion led to a synchronous decrease in the cooperation of the fungal community, the bacterial community, and bacterial-fungal cross-species networks. The addition of fungicides enhanced the removal of antibiotic- and metal resistance genes (from 34.32% to 51.50%, and from −173.18% to 20.97%, respectively) and mobile genetic elements (MGEs, from 38.61% to 68.02%), and the removal of hard-to-remove and high-risk ARGs was enhanced simultaneously. The decrease in the abundance of key fungi induced a decrease in the abundance of hosts (such as Lactobacillus and Anaerococcus) carrying resistance genes and MGEs, which indicated that core fungi affected the proliferation and horizontal transfer of ARGs in bacterial hosts during facultative composting, which in turn affected the succession of ARGs. This study provides direct evidence for the driving effect of fungi on resistance genes in facultative composting.