Based on comprehensive proteomic analysis conducted across various stages of secondary hair follicles (SHFs), the growth and development regulatory mechanisms of SHFs in Jiangnan cashmere goats were studied. Proteomic analysis of skin tissue from the SHF anagen (An), catagen (Cn), and telogen (Tn) revealed 145 differentially expressed proteins (DEPs) between the An and Tn, 53 DEPs between the Cn and An, and 168 DEPs between the Cn and Tn. Gene Ontology (GO) annotations indicated that the DEPs were predominantly involved in keratin filament formation (KRTAP3-1, KRT1, KRT8), intermediate filament formation (KRT26, KRT35, KRT19, etc.), and lipid metabolism (FA2H, CERS6, ECH1, TECR, etc.). Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis identified significant enrichment of DEPs in pathways related to hair follicle growth and development. Notably, these included the PPAR signaling pathway (PLIN2, PLIN4, ACSL5, etc.), the IL-17 signaling pathway (S100A7A, LOC108633164), and the estrogen signaling pathway (KRT26, KRT35, LOC102176457.). Western blotting (WB) experiments were then performed on five DEPs (KRT28, FA2H, PLIN2, FABP7, and VNN1) to validate the consistency of the WB results with the proteomic data. Overexpression and siRNA interference of PLIN2 in dermal papilla cells (DPCs) were followed by CCK8 and flow cytometry assays, revealing that PLIN2 knockdown significantly decreased DPC proliferation while inducing apoptosis, compared to controls. These findings suggest that the PLIN2 gene plays a crucial role in modulating SHF growth cycles in cashmere goats by influencing DPC proliferation. These results provide novel insights that could inform the development of breeding strategies aimed at enhancing the cashmere yield in such goats.

With economic development and improved living standards, the demand for mutton and wool continues to grow, and improving the production performance and genetic potential of sheep breeds has become the key to promoting the high-quality development of the sheep industry. Thus, this study analyzes the influencing factors of the early production traits of Yunnan semi-fine wool sheep, optimizes the genetic evaluation model, and relies on accurate genetic parameter estimation to provide a theoretical basis for formulating a scientific and efficient breeding strategy for this breed. Data were collected from the Laishishan and Xiaohai breeding farms in Qiaojia, Yunnan, covering production records of the core flock from 2018 to 2022. Using the GLM procedure in SAS 9.4 software, this study analyzed the non-genetic influences on early production traits in Yunnan semi-fine wool sheep. Concurrently, Danish Milk Unit 5 (DMU 5) software estimated the variance components across various animal models for each trait. Employing the Akaike Information Criterion (AIC) and likelihood ratio test (LRT), six models were tested, incorporating or excluding maternal inheritance and environmental impacts, to identify the optimal model for deriving the genetic parameters. The results show that the birth year, dam age, sex, flock and litter size significantly affect both the Birth Weight (BWT) and Weaning Weight (WWT) (p < 0.01). Additionally, the birth month was found to exert a significant effect on Birth Weight (BWT) (p < 0.01), the weaning month has a significant effect on the Weaning Weight (WWT) (p < 0.05). No significant effects of farm location were observed on either trait (p > 0.05). The most accurate genetic evaluation model determined the heritability of the Birth Weight (BWT) and Weaning Weight (WWT) as 0.3123 and 0.3471. From a production perspective, improving lamb birth, Weaning Weight (WWT), feed composition, and maternal nutrition during gestation is vital for breeding efficiency. This study not only identified the optimal animal models for early growth traits in Yunnan semi-fine wool sheep, offering a precise basis for estimating genetic parameters but also provides theoretical guidance for genetic selection and breed improvement in this population.

Background/Objectives: The Jiangnan cashmere goat is a newly developed national cashmere goat breed in China, and the genetic stability of its traits is the core of breeding work. Methods: This study used 353 Jiangnan cashmere goats as research subjects. Descriptive statistics were performed on the key economic traits of the experimental population. Polymorphisms in the CXCL10, FOS, HOXC13, and WNT4 genes were detected using multiplex PCR. The correlation between single-nucleotide polymorphism (SNP) loci and key economic traits was analyzed using the least squares variance method in SAS 9.4 software. Results: A total of 14 SNP loci were detected in the four genes, of which 5 were in the CXCL10 gene. Three SNPs were detected in the FOS, HOXC13, and WNT4 genes. SNP3, SNP4, SNP6, SNP10, SNP11, SNP12, SNP13, and SNP14 were in Hardy–Weinberg equilibrium. The results of the correlation analysis showed that SNP9 of the HOXC13 gene was significantly correlated with birth weight (BW) and mean fiber diameter (MFD), SNP10 of the HOXC13 gene was significantly correlated with yearling weight (YW), and SNP14 of the WNT4 gene was significantly correlated with birth weight (BW) (p < 0.05). Conclusions: The results of this study provide molecular markers for cashmere goat breeding and an experimental basis for accelerating the cultivation of new strains, which is conducive to further optimizing the economic traits of the Jiangnan cashmere goat and ensuring the stable inheritance of its economic traits through molecular breeding.