Background: Cashmere goats make an outstanding contribution to the livestock textile industry and their cashmere is famous for its slenderness and softness and has been extensively studied. However, there are few reports on the molecular regulatory mechanisms of the secondary hair follicle growth cycle in cashmere goats. In order to explore the regular transition through the follicle cycle and the role of key genes in this cycle, we used a transcriptome sequencing technique to sequence the skin of Inner Mongolian cashmere goats during different months. We analyzed the variation and difference in genes throughout the whole hair follicle cycle. We then verified the regulatory mechanism of the cashmere goat secondary hair follicle growth cycle using fluorescence quantitative PCR. Results: The growth cycle of cashmere hair could be divided into three distinct periods: a growth period (March–September), a regression period (September–December), and a resting period (December–March). The results of differential gene analyses showed that March was the most significant month. Cluster analysis of gene expression throughout the whole growth cycle further supported the key nodes of the three periods of cashmere growth, and the differential gene expression of keratin corresponding to the ground haircashmere growth cycle further supported the results from tissue slices. Quantitative fluorescence analysis showed that KAP3–1, KRTAP 8–1, and KRTAP 24–1 genes had close positive correlation with the cashmere growth cycle, and their regulation was consistent with the growth cycle of cashmere. Conclusion: The growth cycle of cashmere cashmere could be divided into three distinct periods: a growth period (March–September), a regression period (September–December) and a resting period (December–March). March was considered to be the beginning of the cycle. KAP and KRTAP showed close positive correlation with the growth cycle of secondary hair follicle cashmere growth, and their regulation was consistent with the cashmere growth cycle. But hair follicle development-related genes are expressed earlier than cashmere growth, indicating that cycle regulation could alter the temporal growth of cashmere. This study laid a theoretical foundation for the study of the cashmere development cycle and provided evidence for key genes during transition through the cashmere cycle. Our study provides a theoretical basis for cashmere goat breeding.

A complete goat (Capra hircus) reference genome enhances analyses of genetic variation, thus providing insights into domestication and selection in goats and related species. Here, we assemble a telomere-to-telomere (T2T) gap-free genome (2.86 Gb) from a cashmere goat (T2T-goat1.0), including a Y chromosome of 20.96 Mb. With a base accuracy of >99.999%, T2T-goat1.0 corrects numerous genome-wide structural and base errors in previous assemblies and adds 288.5 Mb of previously unresolved regions and 446 newly assembled genes to the reference genome. We sequence the genomes of five representative goat breeds for PacBio reads, and use T2T-goat1.0 as a reference to identify a total of 63,417 structural variations (SVs) with up to 4711 (7.42%) in the previously unresolved regions. T2T-goat1.0 was applied in population analyses of global wild and domestic goats, which revealed 32,419 SVs and 25,397,794 SNPs, including 870 SVs and 545,026 SNPs in the previously unresolved regions. Also, our analyses reveal a set of selective variants and genes associated with domestication (e.g., NKG2D and ABCC4) and cashmere traits (e.g., ABCC4 and ASIP).

The Inner Mongolia cashmere goat is an excellent local breed in China. According to the characteristics of wool quilts, the Inner Mongolia cashmere goat can be divided into three types: a long-hair type (hair length of >22 cm), a short-hair type (hair length of ≤13 cm), and an intermediate type (hair length of >13 cm and ≤22 cm). It is found that hair length has a certain reference value for the indirect selection of other important economic traits of cashmere. In order to explore the molecular mechanisms and related regulatory genes of the different hair types, a weighted gene coexpression network analysis (WGCNA) was carried out on the gene expression data and phenotypic data of 12-month-old Inner Mongolia cashmere goats with a long-hair type (LHG) and a short-hair type (SHG) to explore the coexpression modules related to different coat types and nine candidate genes, and detect the relative expression of key candidate genes. The results showed that the WGCNA divided these genes into 19 coexpression modules and found that there was a strong correlation between one module and different hair types. The expression trends of this module’s genes were different in the two hair types, with high expression in the LHG and low expression in the SHG. GO functions are mainly concentrated in cellular components, including intermediate filaments (GO:0005882), intermediate filament cytoskeletons (GO:0045111), and cytoskeletal parts (GO:0044430). The KEGG pathway is mainly enriched in arginine as well as proline metabolism (chx00330) and the MAPK signaling pathway (chx04010). The candidate genes of the different hair types, including the KRT39, KRT74, LOC100861184, LOC102177231, LOC102178767, LOC102179881, LOC106503203, LOC108638293, and LOC108638298 genes, were screened. Through qRT-PCR, it was found that there were significant differences in these candidate genes between the two hair types, and most of them had a significant positive correlation with hair length. It was preliminarily inferred that these candidate genes could regulate the different hair types of cashmere goats and provide molecular markers for hair growth.

The growth of Inner Mongolian Cashmere goat skin hair follicle exhibits a periodic growth pattern. The hair growth cycle is distinguished as telogen, anagen, and catagen stages. The role of vimentin in the growth process of hair follicles is evident. To elucidate the mechanism underlying the vimentin activity in the growth cycle of hair follicles, transcriptome sequencing and liquid chromatography-tandem mass spectrometry were used to obtain the nucleic acid and amino acid sequences of VIIM gene and vimentin. The amino acid and nucleic acid sequences were analyzed by comparison. Real-time quantitative PCR, Western blot, and immunohistochemistry analyzed the expression level and sites of vimentin in the three growth stages of the Inner Mongolia Cashmere goat skin samples. VIM gene cDNA, obtained by transcriptome sequencing, was aligned against that of the Capra hircus VIM gene. The amino acid sequence of vimentin revealed a high similarity rate across other species. The expressions of both VIM gene and vimentin were highest during the growth period and lowest in the rest period. Furthermore, vimentin was primarily expressed in the outer root sheath of the hair follicle as assessed by staining. The sequences of the gene and protein are similar to that of other species and identical to Capra hircus. However, the expression of VIM and vimentin was proportional to that of the growth of hair follicles. And vimentin expressed only in the outer root sheath of hair follicles. Thus, vimentin was speculated to participate in the regulation of the hair follicle growth cycle by affecting the outer root sheath.

Epidermal development and cyclic hair follicle regeneration are governed by well-balanced programs of gene activation and silencing. Recent researches demonstrated that the expression profiles of miRNA showed tissue-specific expression patterns in the epidermis and hair follicles and stage-specific in cyclical development of hair follicles. Furthermore, a large number of miRNAs are involved in the development of epidermis and hair follicles, pigmentation, and the cyclical development of hair follicles. miRNAs in different cell types formed a comprehensive, multi-level network system through interaction with signal pathway and regulation factors. This review summarizes the available progress on how miRNAs are involved in the control of epidermal homeostasis and hair follicle development to enrich the research of gene regulatory networks and contribute to disease treatment and molecular breeding.

The measurements of body size data not only reflect the physical fitness, carcass structure, excellent growth condition, and developmental relationship among tissues and organs of animals but are also critical indicators to measure the growth and development of sheep. Computer vision-based body size identification is a non-contact and stress-free method. In this study, we analyzed different body size traits (height at wither, body slanting length, chest depth, chest circumference, shank circumference, hip height, shoulder width, and rump width) and the body weight of 332 Ujumqin sheep and significant correlations (P < 0.05) were obtained among all traits in Ujumqin sheep. Except for shoulder width, rump width, and shank circumference, all were positively correlated, and the effect of sex on Ujumqin sheep was highly significant. The main body size indexes affecting the body weight of rams and ewes were obtained through stepwise regression analysis of body size on body weight, in order of chest circumference, body slanting length, rump width, hip height, height at wither, and shoulder width for rams and body slanting length, chest circumference, rump width, hip height, height at wither and shoulder width for ewes. The body slanting length, chest circumference, and hip height of ewes were used to construct prediction equations for the body weight of Ujumqin sheep of different sexes. The model's prediction accuracy was 83.9% for the rams and 79.4% for ewes. Combined with a Mask R-CNN and machine vision methods, recognition models of important body size parameters of Ujumqin sheep were constructed. The prediction errors of body slanting length, height at wither, hip height, and chest circumference were ~5%, chest depth error was 9.63%, and shoulder width, rump width, and shank circumference errors were 14.95, 12.05, and 19.71%, respectively. The results show that the proposed method is effective and has great potential in precision management.