Objective To elucidate the functions of MSTN, BDNF, and DKK3 genes associated with slow-to-fast muscle fiber conversion in Xinyang buffalo and their effects on meat quality characteristics, in order to provide reference for the improvement of Xinyang buffalo breeds. Method Three muscle fiber-related genes (MSTN, BDNF, DKK3) were selected from relevant literature. Their amino acid sequences were downloaded from NCBI, domain prediction was performed using MEME, and protein interaction analysis was conducted through the online software STRING for bioinformatics evaluation. Tissue samples from three 36-month-old bulls (Liver, spleen, lung, kidney, heart, foreleg muscle, hindleg muscle, longissimus dorsi muscle, subcutaneous muscle, large intestine, small intestine) were collected for tissue expression profiling. Collect the longissimus dorsi muscle from a 1-day-old newborn calf, isolate and culture the primary cells, induce their differentiation, and analyze time-course gene expression. Result Bioinformatics analysis reveals that the protein encoded by the MSTN gene contains domains associated with the TGF-β signaling pathway and is predominantly highly expressed in skeletal muscle tissue. The protein encoded by the BDNF gene possesses domains related to neurotrophic factors and is primarily highly expressed in neural tissues and skeletal muscle. The protein encoded by the DKK3 gene contains domains associated with the Wnt signaling pathway and is mainly highly expressed in adipose and liver tissues. GO and KEGG analyses further indicated that these genes were respectively enriched in the TGF-β signaling pathway, neurotrophic factor signaling pathway, and Wnt signaling pathway. The temporal differentiation results showed that the expression of MSTN was upregulated in the early stage of differentiation and then rapidly downregulated; the expression level of the BDNF gene exhibited a gradual upward trend and was reactivated and upregulated at the late differentiation stage; DKK3 was not expressed during the differentiation of primary myoblasts. Conclusion These results indicate that the expression of MSTN, BDNF, and DKK3 genes is associated with the formation of muscle fibers in buffalo.

Objective This study aimed to investigate the transcriptional differences in the ovarian tissues of 300-day-old and 900-day-old laying ducks, and to identify the key genes or signaling pathways that affect ovarian aging. Method Ovarian tissues of 300-day-old young laying ducks and 900-day-old old laying ducks were collected, and deep sequencing was performed on the Illumina HiSeq platform. The differentially expressed genes (DEGs) were annotated for Gene ontology (GO) function, KEGG pathway enrichment analysis, and verified by real-time fluorescent quantitative PCR. Result The results showed that 403 genes were significantly differentially expressed between the 900-day-old and 300-day-old laying duck ovaries. Among them, 235 genes were upregulated and 168 genes were downregulated. The GO functions were significantly enriched in metabolic processes, immune system processes, reproduction processes, and transcriptional regulatory activities; the KEGG pathways were significantly enriched in interleukin-17 signaling pathway, ECM-receptor interaction, and arachidonic acid metabolism, etc. The qRT-PCR results revealed that 10 genes, including ADRA2B, TF, APOC3, RXRG, MMP9, GRIA4, OXTR, ATP6V1G3, TRPC5 and STMN4, showed consistent expression patterns between the 900-day-old and 300-day-old laying duck ovarian tissues and the results of transcriptome sequencing, indicating the reliability of the RNA-Seq results. Conclusion Transcriptome sequencing identified 403 significantly DEGs, among which TF, APOC3, TRPC5, etc. may be related to ovarian aging. The KEGG enrichment analysis showed that the interleukin-17 signaling pathway, ECM receptor interaction, and arachidonic acid metabolism pathways can affect inflammatory responses and damage and participate in the aging of laying duck ovaries.

Objective This study was conducted to investigate the dynamic expression characteristics of CYP17A1 during testicular development in Small-tail han sheep, clarify its biological function and expression pattern, and provide a theoretical reference for further research. Method In this study, multiple bioinformatics tools were used to analyze the molecular characteristics of sheep CYP17A1 and construct a phylogenetic tree. Meanwhile, quantitative real‑time polymerase chain reaction (qRT‑PCR) and Western blot were performed to detect the expression of CYP17A1 in the testes of Small‑Tail Han sheep at 2, 6, and 12 months of age. Result The full length of the CDS region of the sheep CYP17A1 gene is 1576 bp, and it shows the closest genetic relationship with ruminants such as goats and cattle. The gene encodes 509 amino acids. The molecular formula of the CYP17A1 protein is C₂₆₀₅H₄₁₄₀N₆₉₆S₁₅, with a molecular weight of 57.39 kDa and a theoretical isoelectric point of 8.60. It is a slightly hydrophilic protein that contains phosphorylation sites but has no signal peptide. The secondary and tertiary structures of CYP17A1 are mainly composed of α-helix, β-sheet, extended strand, and random coil. Both the CYP17A1 gene and its protein were expressed in testicular tissue at all three developmental stages, and their expression levels showed a gradually decreasing trend with increasing age: the highest expression was observed at 2 months of age, followed by 6 months of age, and the lowest at 12 months of age. Conclusion Taken together, these findings demonstrate that CYP17A1 is involved in and exerts an essential regulatory effect on testicular development in Small-tail han sheep.

Objective This study aims to analyze the genetic diversity and population genetic structure of the conservation population of Jinnan cattle, evaluate genomic relationships among individuals, and conduct molecular mating, thereby better protecting and utilizing the genetic resources of Jinnan cattle. Method A total of 161 Jinnan cattle (46 bulls and 115 cows) were genotyped using the bovine 20 K single nucleotide polymorphism (SNP) chip. After quality control, the genotypic data were used to analyze genetic diversity, population genetic structure, and calculate genomic relationships. Genetic contributions of bulls were optimized to minimize inbreeding coefficients in the next generation while maintaining population genetic diversity. Result The results showed that after quality control, 17070 SNP loci were retained. The average observed heterozygosity of the individuals was 0.387, the average expected heterozygosity was 0.386, and the mean SNP polymorphism information content was 0.305. A total of 1,907 runs of homozygosity (ROH) were detected, with an average length of 7.754 Mb and an average of 12.973 ROH segments per individual. The average inbreeding coefficient based on ROH was 0.060. According to the family evolutionary tree, this Jinnan cattle population can be clearly divided into more than 8 families. The genetic diversity of this population is 0.888. Based on the relationship matrix constructed by whole-genome SNP loci, the genetic relationship between individuals ranges from -0.107 to 0.521.When SNPs were divided into haplotype blocks to build the relationship matrix, pairwise relationships ranged from 0 to 0.269 with a mean of 0.112. By optimizing bull genetic contributions to minimize next-generation inbreeding, the top 10 bulls accounted for 57.639% of the total genetic contribution. Conclusion In summary, the conservation population of Jinnan cattle has abundant genetic diversity and low inbreeding level. The kinship estimated based on haplotypes can provide a theoretical basis for scientific mating and conservation utilization of Jinnan cattle.

Objective The purpose of this study was to reveal the role of DNA methylation regulation in the formation of goose fat liver, in order to further screen and explore the key metabolic pathways and differential methylation genes related to the formation of goose fat liver, so as to improve the epigenetic regulation mechanism of goose fat liver formation. Methods In this study, three 70-day-old Lander geese with the same physiological status and health status were selected from the same batch for liver sample collection in the early stage (7 days), middle stage (16 days) and late stage of feeding (25 days). Results The results showed that a total of 266.2G of valid data were obtained by sequencing, with an average Q30 of 87.57%, a match rate of about 74%, and a CT conversion efficiency of > 99.4%. Among the methylated cytosine detected in the whole genome, the CpG context type accounted for about 65% and the methylation level was about 20%. CHG and CHH types accounted for about 0.7%, and the methylation levels were about 4% and 1.4%, respectively. Principal component analysis showed that the samples at each feeding stage were clearly differentiated. Among the gene function regions, the exon region had the highest methylation level and the lowest promoter region. In the comparison group in the early and middle stage of feeding, 524 differential methylated region (DMR) methylation levels increased and 427 DMR methylation levels decreased. In the middle and late stage of feeding, 432 DMR methylation levels increased and 236 DMR methylation levels decreased. The differential genes in the early and middle stages were significantly enriched in 121 KEGG pathways, and 829 GO entries were obtained, among which insulin signaling pathway and FoxO signaling pathway were closely related to lipid deposition, involving 6 genes such as MAPK10 and IL6. The differential genes in metaphase and late stage were enriched into 96 KEGG pathways, and 629 GO entries were obtained, among which MAPK signaling pathway and FoxO signaling pathway were significantly enriched, and 13 related genes including MAPK10, PCK1, and PLA2G4A were obtained. Conclusion The DMR is mainly enriched in key genes related to lipid metabolism, and its formation is synergisticly regulated by multiple pathways such as FoxO signaling pathway, adipocytokine signaling pathway, PPAR signaling pathway, insulin signaling pathway, etc., and the methylation levels of key candidate genes MAPK10, PCK1, PLA2G4A are associated with the formation of goose fat liver.