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.

DNA methylation (DNAm) is associated with the reproductive system. However, the genetic mechanism through which DNAm regulates gene expression and thus affects litter size in goats is unclear. Therefore, in the present work, genome-wide DNAm profiles of HP and LP Jining Grey goat ovary tissues were comprehensively analyzed via WGBS, and RNA-Seq data were combined to identify candidate genes associated with litter size traits in the Jining Grey goat. Finally, BSP and RT-qPCR were used to verify the sequencing results of the key genes. Notably, the DNMT genes were downregulated at the expression level in the HP group. Both groups exhibited comparable levels of methylation. A total of 976 differentially methylated regions (DMRs) (973 DMRs for CG and 3 DMRs for CHG) and 310 differentially methylated genes (DMGs) were identified in this study. Through integration of WGBS and RNA-Seq data, we identified 59 differentially methylated and differentially expressed genes (DEGs) and ultimately screened 8 key DMGs (9 DMRS) associated with litter size traits in Jining Grey goats (SERPINB2: chr24_62258801_62259000, NDRG4: chr18_27599201_27599400, CFAP43: chr26_27046601_27046800, LRP1B. chr2_79720201_79720400, EPHA6: chr1_40088601_40088800, TTC29: chr17_59385801_59386000, PDE11A: chr2_117418601_117418800 and PGF: chr10_ 16913801_16914000 and chr10_16916401_16916600). In summary, our research comprehensively analyzed the genome-wide DNAm profiles of HP and LP Jining Grey goat ovary tissues. The data findings suggest that DNAm in goat ovaries may play an important role in determining litter size.

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.

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.

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.