This study was conducted to evaluate the influences of supplementing Ampelopsis grossedentata flavonoids (AGF) on the rumen bacterial microbiome, plasma physiology and biochemistry, and growth performance of goats. Twenty-four Nubian kids were randomly allocated to three dietary treatments: the control (CON, basal diet), the 1.0 g/kg AGF treatment (AGF), and the 12.5 mg/kg monensin treatment (MN). This trial consisted of 10 days for adaptation and 90 days for data and sample collection. The results reveal that Bacteroidetes, Firmicutes, and Proteobacteria are the dominant phyla in kids’ rumen. Compared with the CON group, the alpha diversity in the MN and AGF groups significantly increased (p < 0.01). Beta-diversity shows that rumen microbial composition is more similar in the MN and AGF groups. LEfSe analysis shows that Prevotella_1 in the AGF group were significantly higher than those in the MN and CON group. The high-density lipoprotein cholesterol and glucose levels in the AGF group were significantly higher than those in the CON group (p < 0.05), whereas the low-density lipoprotein cholesterol, glutamic-pyruvic transaminase, and alkaline phosphatase levels exhibited the opposite trend. The average daily gains in the AGF and MN groups significantly increased, while the feed-to-gain ratios were significantly decreased (p < 0.05). The results suggest that adding AGF to the diet improves microbial composition and has important implications for studying juvenile livestock growth and improving economic benefits.

Bovine spongiform encephalopathy (BSE) is a fatal disease in cattle caused by misfolded prion proteins and linked to indel polymorphisms in the promoter and intron 1 of the PRNP gene. The aim of this study was to determine the allele, genotype, and haplotype frequencies of PRNP indel polymorphisms and to investigate the effect of PRNP gene expressions of 23 bp and 12 bp indels via polymerase chain reaction (PCR) in Zhongdian Yak (Bos-grunniens) (YK), Zhongdian Yellow cattle (Bos-taurus) (YC), and Zhongdian Yakow (Bos-primigenius taurus × Bos-grunniens) (PK). Resultant high allelic frequencies were found in 23− and 12+, while haplotype frequencies were very low in 23+/12 in YK, YC, and PK. PRNP expression was higher in the +−/−− diplotype of the PK and (mean ± SE) was 3.6578 ± 1.85964. Furthermore, two variable sites were investigated—a 23 bp indel polymorphism holding AP1 binding site and a 12 bp indel polymorphism holding SP1 binding site. Additionally, reporter gene assays revealed a link between two proposed transcription factors and lower expression levels of the +/+ allele compared with the −/− allele. The expression level of PRNP was shown to be dependent on two indel polymorphisms in the bovine PRNP promoter, which includes binding sites for RP58 and SP1 transcription factors. These findings raised the possibility that the PRNP genotype may contribute to the high variation in PRNP expression.

Pigs are a major source of animal protein and an important model for studying domestication, adaptation, and the genetics of complex traits. Over the past decade, pig genomics has progressed from generating reference assemblies and variant catalogues toward reconstructing population history and interpreting phenotypic divergence with greater resolution. Improvements in reference continuity, breed-matched assemblies, and pangenome/graph representations reduce reference bias in repeat-rich and structural-variant-prone regions, strengthening cross-population comparisons and fine-mapping across cohorts. Time-stratified ancient genomes provide an explicit temporal framework for evaluating lineage turnover and gene flow and support a multi-stage, network-based view of domestication. In parallel, genetic analyses of growth, carcass composition, meat quality, and disease resilience increasingly integrate association signals with regulatory annotation, gene expression, and tissue- or stage-specific context. Across these lines of work, maintaining comparability across reference frameworks remains central, including stable coordinate systems, robust imputation resources, and reproducible approaches for structural-variant genotyping. Together, these developments support more consistent inference and interpretation while providing a clearer basis for translation in breeding and biomedical research with attention to genetic diversity.