Follicle-stimulating hormone (FSH) regulates ovarian follicle development through specific gene expression programs. Granulosa cells (GCs) are somatic cells surrounding the oocytes, secreting gonadotropins to regulate ovulation and promote follicular development. By analyzing the effects of different doses of FSH on the proliferation of GCs, we found that adding 10 ng/mL of FSH, as the optimal concentration, could promote the growth of GCs. Furthermore, we have successfully constructed the first CRISPR-Cas9 knockout library targeting the genes on chromosomes 2 and 3 and the X chromosomes of the sheep massively parallel coding gene, as well as an ovarian GCs knockout cell library. For the first time, we have exposed the knockout cell library to a concentration of 10 ng/mL FSH to explore the underlying mechanisms. Through this screening, we have identified 836 positive–negative screening genes that are responsive to FSH, thereby revealing the regulatory mechanisms and screening the functionality of candidate genes. Next, RNA-Seq of control (0 ng/mL), low (10 ng/mL), and high (100 ng/mL) doses of FSH revealed 1708 differentially expressed genes, and combined with 836 genes, we obtained 129 FSH dose-dependent genes with extremely significant differences. This enables us to delve deeper into investigating and identifying the mechanisms by which FSH regulates GCs. More generally, we have discovered new regulatory factors and identified reproductivity-associated major effectors. These findings provide novel research directions for further studies on sheep reproduction.

Elucidating the molecular mechanisms underlying beef quality differences is crucial for precision breeding of high-quality cattle. In this study, we first characterized the myofibrillar morphology of high-quality (H group) and low-quality (L group) beef samples using hematoxylin–eosin (HE) staining. Transcriptomic and metabolomic analyses were then conducted to reveal the molecular regulatory basis of quality variation. HE staining revealed highly significant differences in muscle fiber area and diameter between H and L groups (p < 0.01), along with significant differences in muscle fiber density (p < 0.05), but no significant differences in muscle fiber perimeter. Furthermore, by focusing on five core metabolic pathways shared across the transcriptome and metabolome datasets, 30 differentially expressed genes (DEGs) and 14 differentially accumulated metabolites (DAMs) were identified. Pearson correlation analysis revealed synergistic regulation between DEGs and DAMs: AMPD2 modulates umami flavor by regulating inosine accumulation via the purine metabolism pathway; ACOX3 promotes unsaturated fatty acid synthesis and intramuscular fat deposition through carbohydrate metabolism; genes in the glycolysis/gluconeogenesis pathway maintain post-slaughter muscle pH homeostasis, thereby influencing beef tenderness. Collectively, this study integrates morphological and molecular evidence to elucidate the multi-level basis of beef quality formation, providing key candidate genes, metabolites, and pathways for molecular breeding. These findings offer comprehensive theoretical and technical support for the sustainable development of the premium beef industry.

The Krüppel-like factor (KLF) family of transcription regulators plays pivotal roles in adipogenesis, myogenesis, and metabolism. While comprehensively studied in humans and mice, its characterization in cattle remains limited, especially within the skeletal muscle niche. This study aimed to systematically characterize the KLF family in Bos taurus and elucidate its role in breed-specific muscular development. We employed an integrated approach of comparative genomics and single-nucleus RNA sequencing (snRNA-seq) on longissimus dorsi muscle from Angus (ANG, beef breed) and Holstein (HST, dairy breed) cattle. Phylogenomic analysis identified 14 KLF genes, revealing evolutionary conservation and potential functional divergence. snRNA-seq delineated 11 distinct cell populations and uncovered cell-type-specific expression patterns of KLFs. Further machine learning based analysis pinpointed KLF6, KLF9, KLF10, and KLF12 as key global drivers of transcriptional differences between breeds, while KLF6 was identified as a major cell-type-specific contributor in lymphatic endothelial cells. Our work provides a foundational resource for understanding the KLF family in cattle and identifies promising candidate genes for improving meat production traits through molecular breeding.