With the growing global population, the demand for beef is increasing, making the genetic improvement of beef cattle crucial for sustainable production. This study aimed to estimate genetic parameters using different models and predict body weight in Angus cattle to enhance the accuracy of genetic evaluation and support optimal breeding and selection programs. We used the inclusion or exclusion of maternal genetic effects, maternal permanent environmental effects, and the presence or absence of covariance between maternal and direct genetic effects to distinguish between the six animal models. The variance components and genetic parameters of 13,607 weight records from Angus cattle were estimated using the Average Information Restricted Maximum Likelihood (AI-REML) method. The best estimated model was selected based on the Akaike Information Criterion (AIC) and Likelihood Ratio Test (LRT). The results of this study revealed that, in addition to individual genetic effects, maternal genetic effects had a significant impact on unbiased and accurate genetic parameter estimates of body weight in Angus cattle. The total heritability estimated with the best model for body weight at birth (BW0), 3 months (BW3), 6 months (BW6), 12 months (BW12), and 18 months (BW18) was 0.215 ± 0.007, 0.340 ± 0.021, 0.239 ± 0.035, 0.362 ± 0.044, and 0.225 ± 0.048, respectively. The maternal heritability ranges from 0.017~0.438 and significantly affects Angus cattle throughout their growth and development stages, with the effect decreasing with increasing age. Positive correlations were observed between body weights at different months of age, ranging from 0.061 to 0.828. BW6 has a high positive genetic correlation with later age weight, and BW6 is a good predictor of later age weight. Thus, it is possible to optimize breeding programs and accelerate genetic progress by selecting for higher 6-month-old live weights for early Angus selection. In addition, our results emphasize the importance of considering maternal effects in genetic evaluation to improve the efficiency and accuracy of selection programs and thereby contribute to sustainable genetic improvement in beef cattle.

This study sought to investigate the impact of different levels of dietary maintenance energy metabolism on nutrient digestibility, rumen microbiota composition, and serum biochemical parameters in Lanzhou fat-tailed sheep rams. A total of twenty rams, each aged eight months and with an initial mean body weight of 27.81 ± 3.38 kg, were selected and randomly assigned to one of four experimental groups. These groups were administered with different levels of metabolizable energy (MEM): low energy (LE), intermediate energy (IE), high energy (HE), and extra high energy (EHE), corresponding to 6.77, 7.22, 7.72, and 8.20 MJ/d, respectively. The results showed a linear increase (p < 0.001) in average daily gain (ADG), dry matter (DM) intake, apparent DM digestibility, and crude protein (CP) digestibility. Conversely, the intake of nitrogen (NI), fecal nitrogen (FN), and manure nitrogen (MN) exhibited a significant linear decrease (p < 0.001). The N utilization efficiency rations of FN/NI and MN/NI linearly decreased (p < 0.001), while RN/NI linearly increased (p < 0.001). Additionally, the intake of gross energy (GE), methane energy (CH4-E), digestible energy (DE), and metabolizable energy (ME) exhibited a linear increase, whereas the ration of FE/GE intake linearly decreased (p < 0.001). The efficiency of energy utilization expressed as a proportion of GE intake (DE/GE intake, ME/GE intake, ME/DE intake, and CH4-E/GE intake) showed linear alterations (p < 0.05) with the increase in the dietary energy supplementation level. The dietary energy level did not exert a significant impact on serum biochemical indices (p > 0.05). At the phylum level, the average abundances of Verrucomicrobiota were significantly reduced in the EHE group compared to the IE group, while the average abundances of Desulfobacterota were significantly lower in the EHE group relative to the LE group. At the genus level, the average abundances of Succiniclasticum were significantly higher in the HE and EHE groups compared to the LE group. In conclusion, the energy level (8.20 MJ/d) significantly enhanced nutrient digestibility, energy, and nitrogen metabolism, and it significantly increased the relative abundances of Succiniclasticum.

Milk fat composition and content are crucial indicators that influence the taste, flavor and nutritional value of milk, and they are regulated by various non-coding RNAs. To enhance milk quality, it is essential to investigate the regulatory mechanisms underlying milk fat metabolism. This study analyzed significantly up-regulated circ_0009058 and circ_0004021 and significantly down-regulated circ_0011934 and circ_0008056 in bovine mammary epithelial cells (BMECs) with high and low milk fat percentages (MFP). RNase R digestion assays and Sanger sequencing were conducted to confirm their presence and high expression in the mammary tissue of dairy cows. Subcellular localization indicated that these RNA may exhibit regulatory functions through the competing endogenous RNA (ceRNA) network. Consequently, a ceRNA regulatory network was constructed, identifying six hub target genes in the ceRNA network (VAV1, PTPN6, PIK3R1, RHOA, ERBB3, PIK3CG) using the CytoHubba and MCODE plugins in Cytoscape (version 3.9). Quantitative real-time PCR (RT-qPCR) and dual luciferase reporter gene assays validated the existence of the interactive regulatory networks circ_0004021/bta-miR-541/PTPN6, circ_0008056/bta-miR-2309/ERBB3, and bta-miR-10175-3p/RHOA in BMECs. Functional validation of miRNAs within the ceRNA network demonstrated that bta-miR-541 and bta-miR-10175-3p reduced triglyceride and cholesterol levels while inhibiting lipid droplet secretion in BMECs. Conversely, the function of bta-miR-2309 was found to be opposite to that of bta-miR-541 and bta-miR-10175-3p. This study identified several critical candidate ceRNA networks involved in fatty acid metabolism in dairy cows through data analysis and a series of experiments. These functional and mechanistic studies provide a theoretical foundation for improving milk quality.

Methane (CH₄), a significant greenhouse gas, ranks second only to carbon dioxide in its contribution to global warming. The application of Chinese herbs as a strategy to mitigate CH₄ emissions in ruminants has shown promise. However, there is limited information regarding the efficacy of Chinese herb straw in reducing CH₄ emissions in ruminants. This research aimed to investigate the beneficial effects of varying levels of Astragalus straw supplementation on methane emissions and to elucidate the underlying molecular mechanisms. The study examined the effects of different supplementation levels (0%, 5%, 10%, 15%, 20%) on in vitro rumen fermentation, CH₄ emissions, and ruminal microbial community in Lanzhou fat-tailed sheep using an in vitro fermentation method. The findings indicated that IVDMD, gas production, and CH₄ production significantly decreased with increasing levels of Astragalus straw supplementation (p < 0.05). Simultaneously, the lowest levels of AA, AA/PA, and NH₃-N, along with the highest concentrations of PA, BA, and MCP, were observed in the 20% supplementation group after 48 h of fermentation. In addition, supplementation with Astragalus straw resulted in an increased abundance of Bacteroidota, Spirochaetota, and Actinobacteriota, while decreasing the abundance of Firmicutes, Fibrobacterota, and Verrucomicrobiota. At the genus level, there was an observed increase in the abundance of Prevotella and Streptococcus, accompanied by a decrease in Rikenellaceae_RC9_gut_group. In conclusion, the supplementation of Astragalus straw has the potential to reduce CH₄ production by altering ruminal fermentation patterns, fermentation parameters, and microbial dynamics.

The molecular architecture of the growth-regulating hypothalamus-pituitary-muscle (H-P-M) axis is poorly understood. We performed integrative transcriptomic analysis of the hypothalamus, pituitary, and longissimus dorsi muscle from Liangshan black sheep with superior growth performance to dissect this regulatory network. Analysis of 3,422 differentially expressed genes (DEGs) identified across pairwise tissue comparisons revealed a three-tiered regulatory architecture: (1) tissue-specific interfaces defining spatial hierarchy, (2) relay modules for temporal dynamics, and (3) shared core hubs (131 genes) establishing neuro-endocrine-muscle integration. This study provides a multi-level regulatory map of the H-P-M axis, identifying key pathways such as pituitary calcium signaling and hub genes (e.g., NPY), with 12 of 14 candidate genes validated by quantitative PCR. These findings deepen the understanding of neuroendocrine control over skeletal muscle growth and offer novel molecular targets for genetic improvement in livestock.