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Background Merino sheep are the most famous fine wool sheep in the world. They have high wool production and excellent wool quality and have attracted worldwide attention. The fleece of the Merino sheep is composed predominantly of wool fibers grown from secondary wool follicles. Therefore, it is necessary to study the development of hair follicles to understand the mechanism of wool production. The hair follicle is a complex biological system involved in a dynamic process governed by gene regulation. The hair follicle development process is very complex and poorly understood. The purpose of our research is to identify candidate genes related to hair follicle development, provide a theoretical molecular breeding basis for the cultivation of fine wool sheep, and provide a reference for the problems of hair loss and alopecia areata that affect human beings. Results We analyzed mRNAs data in skin tissues of 18 Merino sheep at four embryonic days (E65, E85, E105 and E135) and two postnatal days (P7 and P30). G1 to G6 represent hair follicles developmental at six stages (i.e. E65 to P30). We identified 7879 differentially expressed genes (DEGs) and 12623 novel DEGs, revealed different expression patterns of these DEGs at six stages of hair follicle development, and demonstrated their complex interactions. DEGs with stage-specific expression were significantly enriched in epidermal differentiation and development, hair follicle development and hair follicle morphogenesis and were enriched in many pathways related to hair follicle development. The key genes (LAMA5, WNT10A, KRT25, SOSTDC1, ZDHHC21, FZD1, BMP7, LRP4, TGFβ2, TMEM79, SOX10, ITGB4, KRT14, ITGA6, and GLI2) affecting hair follicle morphogenesis were identified by network analysis. Conclusion This study provides a new reference for the molecular basis of hair follicle development and lays a foundation for further improving sheep hair follicle breeding. Candidate genes related to hair follicular development were found, which provided a theoretical basis for molecular breeding for the culture of fine wool sheep. These results are a valuable resource for biological investigations of fleece evolution in animals.

BackgroundCharacterization 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.ResultsWe 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.ConclusionsOur 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.

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&ndash, 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.