Exogenous melatonin could induce cashmere growth. However, induced growth of cashmere fleece by melatonin implants cannot be combined with the typical growth, resulting in earlier shedding followed by another cycle of cashmere growth. To address this issue, we examine the effects on the cashmere yield, fibre characteristics, and the growth and reproductive performance of cashmere goats of planned administration of melatonin. Eighteen half-sib, female goats were assigned to two treatments (n = 9) including a control and a treatment where melatonin (2 mg/kg BW) was implanted at the end of April and end of June. Cashmere growth and shedding were observed for approximately 1 year following implantation. Fibre samples were collected monthly to determine cumulative cashmere length. Initiation and cessation dates for cashmere growth as well as the rate of cashmere growth were calculated. Cashmere yield, weight gain of dam, kidding date, litter size, and birth weight were also recorded. Melatonin implantation increased cashmere yield by 34.5 % (control 553.7 g vs. melatonin 745.0 g; P < 0.01), cashmere length by 21.3 % (control 95.2 mm vs. melatonin 115.4 mm; P < 0.01), and decreased fibre diameter by 4.4 % (control 14.6 μm vs. melatonin 14.0 μm; P < 0.03). In melatonin-treated goats, the average initiation date was earlier than in control goats (May 18, 2013 vs. July 2, 2013; P < 0.01) but there was a similar cessation date (March 22, 2014 vs. March 27, 2014). Consequently, the duration of cashmere growth was longer in melatonin-treated goats than in control goats (307 vs.270 days; P < 0.01). The final BW, average daily gain, kidding date, litter size, and birth weight were not influenced by melatonin implantation. These data indicate that melatonin implantation (2 mg/kg BW) on two occasions (late April and June) increased cashmere yield by combining the induced growth of cashmere fleece with the typical growth and decreased the fibre diameter without changing dam growth rate or reproductive performance.

In this study, we aimed to establish the correlation between ruminal fermentation parameters and the bacterial community by comparing those of the goat, sheep, and cow, thus illustrating the main bacteria causing the difference in rumen fermentation among goats, sheep, and cows and providing a new idea for improving the feed digestibility of ruminants. Rumen fluid from goats (Taihang White cashmere goat, n = 6), sheep (Hu sheep, n = 6), and cows (Holstein cow, n = 6) was collected using oral intubation and immediately brought back to the laboratory for a fermentation test with the same total mixed ration (TMR) feed in vitro. The rumen bacterial composition was measured by high-throughput sequencing of 16S rRNA genes in the MiSeq platform, the gas production (GP) was recorded after 2, 4, 6, 8, 10, 12, 24, 36, and 48 h of fermentation, and the feed nutrient digestibility and the rumen fluid parameters were determined after 48 h of fermentation. The results showed that the 48 h GP of the sheep group was higher than that of the cow group (p < 0.05), and the theoretical maximum GP was higher than that of the goat and cow groups (p < 0.05). The organic matter digestibility (OMD), dry matter digestibility (DMD), crude protein digestibility (CPD), and gross energy digestibility (GED) of the sheep group were higher than those of the goat and cow groups (p < 0.05). The ammonia nitrogen (NH₃-N), microbial protein (MCP), and total volatile fatty acids (TVFA) concentrations of the sheep group were higher than those of the other groups (p < 0.05), and the pH of the sheep group was lower than those of the other groups (p < 0.05). The 16S rRNA gene sequencing revealed that bacterial composition also differed in the rumens of the sheep, goat, and cow groups (ANOSIM, p < 0.05). We then used a random forest machine learning algorithm to establish models to predict the fermentation parameters by rumen bacterial composition, and the results showed that rumen bacterial composition could explain most of the ruminal fermentation parameter variation (66.56%, 56.13%, 65.75%, 80.85%, 61.30%, 4.59%, 1.41%, −3.13%, 34.76%, −25.62%, 2.73%, 60.74%, 76.23%, 47.48%, −13.2%, 80.16%, 4.15%, 69.03%, 32.29%, and 89.96% for 48 h GP, a (GP of quickly degraded part), b (GP of slowly degraded part), c (GP rate), a + b (theoretical maximum GP), DMD, OMD, GED, CPD, NDFD, ANDF, pH, NH₃-N, MCP, acetic acid, propionic acid, butyric acid, valeric acid, TVFA, and A:P (acetic acid–propionic acid ratio), respectively). A correlation analysis revealed that Lactobacillus, Prevotellaceae_UCG-003, Selenomonas, Peptostreptococcus, and Olsenella significantly correlated with most in vitro fermentation parameters (p < 0.05). A comprehensive analysis showed that rumen fermentation parameters and bacterial composition differed in goats, sheep, and cows. The ruminal fermentation parameters of GP, a, b, c, a + b, pH, NH₃-N, propionic acid, valeric acid, and A:P could be accurately predicted by rumen bacteria (explanation > 55% of variation), and the Lactobacillus, Prevotellaceae_UCG-003, Olsenella, Selenomonas, and Peptostreptococcus were the main bacteria that affected the in vitro fermentation parameters of goats, sheep, and cows.

Prolactin (PRL) has been reported to influence reproductive performance and cell apoptosis. However, its mechanism remains unclear. Hence, in the present study, ovine ovarian granulosa cells (GCs) were used as a cell model to investigate the relationship between PRL concentration and GC apoptosis, as well as its possible mechanisms. We examined the relationship between serum PRL concentration and follicle counts in sexually mature ewes. GCs were isolated from adult ewes and treated with different concentrations of PRL, while 500 ng/mL PRL was selected as the high concentration of prolactin (HPC). Then, we applied the transcriptome sequencing (RNA-Seq) combined with a gene editing approach to explore the HPC contributing to cell apoptosis and steroid hormones. The apoptosis of GCs gradually increased at PRL concentrations above 20 ng/mL, while 500 ng/mL PRL significantly decreased the secretion of steroid hormones and the expression of L-PRLR and S-PRLR. The results indicated that PRL regulates GC development and steroid hormones mainly through the target gene MAPK12. The expression of MAPK12 was increased after knocked-down L-PRLR and S-PRLR, while it decreased after overexpressed L-PRLR and S-PRLR. Cell apoptosis was inhibited and the secretion of steroid hormones increased after interfering with MAPK12, while the overexpression of MAPK12 showed the opposite trend. Overall, the number of follicles gradually decreased with increasing PRL concentration. HPCs promoted apoptosis and inhibited steroid hormone secretion in GCs by upregulating MAPK12 through reducing L-PRLR and S-PRLR.

Exogenous melatonin (MT) has been used to promote the growth of secondary hair follicles and improve cashmere fiber quality, but the specific cellular-level mechanisms involved are unclear. This study was carried out to investigate the effect of MT on the development of secondary hair follicles and on cashmere fiber quality in cashmere goats. The results showed that MT improved secondary follicle numbers and function as well as enhanced cashmere fiber quality and yield. The MT-treated goat groups had high secondary-to-primary ratios (S:P) for hair follicles, greater in the elderly group (p < 0.05). Antioxidant capacities of secondary hair follicles improved fiber quality and yield in comparison with control groups (p < 0.05/0.01). Levels of reactive oxygen and nitrogen species (ROS, RNS) and malondialdehyde (MDA) were lowered (p < 0.05/0.01) by MT. There was significant upregulation of antioxidant genes (for SOD-3; GPX-1; NFE2L2) and the protein of nuclear factor (Nrf2), and downregulation of the Keap1 protein. There were significant differences in the expression of genes for secretory senescence-associated phenotype (SASP) cytokines (IL-1β, IL-6, MMP-9, MMP-27, CCL-21, CXCL-12, CXCL-14, TIMP-1,2,3) plus their protein of key transcription factors, nuclear factor kappa B (NFκB) and activator protein-1 (AP-1), in comparison with the controls. We concluded that MT could enhance antioxidant capacity and reduce ROS and RNS levels of secondary hair follicles through the Keap1-Nrf2 pathway in adult cashmere goats. Furthermore, MT reduced the expression of the SASP cytokines genes by inhibiting the protein of NFκB and AP-1 in the secondary hair follicles in older cashmere goats, thus delaying skin aging, improving follicle survival, and increasing the number of secondary hair follicles. Collectively, these effects of exogenous MT enhanced the quality and yield of cashmere fibers, especially at 5–7 years old.

Solid-state fermentation is known to improve plant-based feed nutritional quality; however, the association between microbes and metabolite production in fermented feed remains unclear. We inoculated corn–soybean–wheat bran (CSW) meal feed with Bacillus licheniformis Y5-39, Bacillus subtilis B-1, and lactic acid bacteria RSG-1. Then, 16S rDNA sequencing and untargeted metabolomic profiling were applied to investigate changes in the microflora and metabolites, respectively, and their integrated correlations during fermentation were assessed. The results indicated that trichloroacetic acid soluble protein levels showed a sharp increase, while glycinin and β-conglycinin levels showed a sharp decrease in the fermented feed, as confirmed by sodium dodecyl sulfate–polyacrylamide gel electrophoresis. Pediococcus, Enterococcus, and Lactobacillus were predominant in the fermented feed. Overall, 699 significantly different metabolites were identified before and after fermentation. Arginine and proline, cysteine and methionine, and phenylalanine and tryptophan metabolism were the key pathways, with arginine and proline metabolism being the most important pathway in the fermentation process. By analyzing the correlation between the microbiota and metabolite production, lysyl–valine and lysyl–proline levels were found to be positively correlated with Enterococcus and Lactobacillus abundance. However, Pediococcus was positively correlated with some metabolites contributing to nutritional status and immune function. According to our data, Pediococcus, Enterococcus, and Lactobacillus mainly participate in protein degradation, amino acid metabolism, and lactic acid production in fermented feed. Our results provide new insights into the dynamic changes in metabolism that occurred during the solid-state fermentation of corn–soybean meal feed using compound strains and should facilitate the optimization of fermentation production efficiency and feed quality.

Long non-coding RNAs (lncRNAs) have been shown to play important roles in livestock fecundity, and many lncRNAs that affect follicular development and reproductive diseases have been identified in the ovary. However, only a few of them have been functionally annotated and mechanistically validated. In this study, we identified a new lncRNA (lncGSAR) and investigated its effects on the proliferation and steroidogenesis of ovine granulosa cells (GCs). High concentrations of glucose (add 33.6 mM glucose) caused high expression of lncGSAR in GCs by regulating its stability, and lncGSAR overexpression promoted GCs proliferation, estrogen secretion, and inhibited progesterone secretion, whereas interference with lncGASR had the opposite effect. Next, we found that the RNA molecules of lncGSAR act on MiR-125b as competitive endogenous RNA (ceRNA), and SREBP-cleavage-activating protein (SCAP) was verified as a target of MiR-125b. LncGASR overexpression increased the expression of SCAP, SREBP, and steroid hormone-related proteins, which can be attenuated by MiR-125b. Our results demonstrated that lncGSAR can act as a ceRNA to activate SCAP/SREBP signaling by sponging MiR-125b to regulate steroid hormone secretion in GCs. These findings provide new insights into the mechanisms of nutrient-regulated follicle development in ewes.