Fibroblast growth factor 9 (FGF9) is crucial for the growth and development of hair follicles (HFs); however, its role in sheep wool growth is unknown. Here, we clarified the role of FGF9 in HF growth in the small-tailed Han sheep by quantifying FGF9 expression in skin tissue sections collected at different periods. Moreover, we evaluated the effects of FGF9 protein supplementation on hair shaft growth in vitro and FGF9 knockdown on cultured dermal papilla cells (DPCs). The relationship between FGF9 and the Wnt/β-catenin signaling pathway was examined, and the underlying mechanisms of FGF9-mediated DPC proliferation were investigated. The results show that FGF9 expression varies throughout the HF cycle and participates in wool growth. The proliferation rate and cell cycle of FGF9-treated DPCs substantially increase compared to that of the control group, and the mRNA and protein expression of CTNNB1, a Wnt/β-catenin signaling pathway marker gene, is considerably lower than that in the control group. The opposite occurs in FGF9-knockdown DPCs. Moreover, other signaling pathways are enriched in the FGF9-treated group. In conclusion, FGF9 accelerates the proliferation and cell cycle of DPCs and may regulate HF growth and development through the Wnt/β-catenin signaling pathway.

Liaoning Cashmere Goats are a high-quality dual-purpose breed valued for both their cashmere and meat. They are also a key national genetic resource for the protection of livestock and poultry in China, with their intensive farming model currently taking shape. Leveraging new productivity advantages and reducing labor costs are urgent issues for intensive breeding. Recognizing goatbehavior in large-scale intelligent breeding not only improves health monitoring and saves labor, but also improves welfare standards by providing management insights. Traditional methods of goat behavior detection are inefficient and prone to cause stress in goats. Therefore, the development of a convenient and rapid detection method is crucial for the efficiency and quality improvement of the industry. This study introduces a deep learning-based behavior recognition and online detection system for Liaoning Cashmere Goats. We compared the convergence speed and detection accuracy of the two-stage algorithm Faster R-CNN and the one-stage algorithm YOLO in behavior recognition tasks. YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. Our improved model achieved the highest detection accuracy of 98.11% compared to other state-of-the-art (SOTA) target detection algorithms. The Liaoning Cashmere Goat Online Behavior Detection System demonstrated real-time detection capabilities, with a relatively low error rate compared to manual video review, and can effectively replace manual labor for online behavior detection. This study introduces detection algorithms and develops the Liaoning Cashmere Goat Online Behavior Detection System, offering an effective solution for intelligent goat management.

Simple sequence repeats (SSRs), the markers with the highest polymorphism and co-dominance degrees, offer a crucial genetic research resource. Limited SSR markers in blackhead seabream have been reported. The availability of the blackhead seabream genome assembly provided the opportunity to carry out genome-wide identification for all microsatellite markers, and bioinformatic analyses open the way for developing a microsatellite genome-wide database in blackhead seabream. In this study, a total of 412,381 SSRs were identified in the 688.08 Mb genome by Krait software. Whole-genome sequences (10×) of 42 samples were aligned against the reference genome and genotyped using the HipSTR tools by comparing and counting repeat number variation across the SSR loci. A total of 156,086 SSRs with a 2–4 bp repeat were genotyped by HipSTR tools, which accounted for 55.78% of the 2–4 bp SSRs in the reference genome. High accuracy of genotyping was observed by comparing HipSTR tools and PCR amplification. A set of 109,131 loci with a number of alleles ≥ 3 and with a number of genotyped individuals ≥ 6 were reserved to constitute the polymorphic SSR database. Fifty-one polymorphic SSR loci were identified through PCR amplification. This strategy to develop polymorphic SSR markers not only obtained a large set of polymorphic SSRs but also eliminated the need for laborious experimental screening. SSR markers developed in this study may facilitate blackhead seabream research, which lays a certain foundation for further gene tagging and genetic linkage analysis, such as marker-assisted selection, genetic mapping, as well as comparative genomic analysis.