Abstract：Youzhou dark goat (Capra hircus) is the genetic resources of local characteristic goat. It is of great significance to study the forming mechanism of its characteristic traits. This study collected the transcriptome data of a total of 15 samples from the heart, liver, longissimus dorsi, anterior lip and skin of Youzhou dark goat (3 samples for each tissue) for analysis. The weighted gene co-expression network analysis (WGCNA) software package was used to construct the co-expression network, and the GO and KEGG enrichment analysis was performed on the genes in the specific modules. Results showed that one specific expression module was identified in the heart and liver respectively. The genes in the heart specific blue module were mainly enriched in the citric acid cycle signal pathway and various metabolic processes. The genes in the liver specific yellow module were mainly enriched in the functions of peroxidase, amino acid metabolic process and chemical carcinogenesis. Genes in the turquoise module are mainly enriched in protein binding and other functions, genes in the green module are mainly enriched in phosphatidylinositol binding and other functions, and genes in the brown module are mainly enriched in biological processes such as cell protein metabolism. Through the CytoHubba plug-in algorithm, the 10 genes with the highest connectivity in the turquoise, blue and brown modules were defined as core genes. The tissue expression level of 6 core genes in the 3 modules were verified by qRT-PCR, and the results showed that ADCY9 and ADCY6 genes had the highest expression in heart tissue, AKT2 and MAPK3 genes were highly expressed in the anterior lip tissue, and the CAMK2G and CAMK2B genes were highly expressed in the longissimus dorsi, which were consistent with the transcriptome sequencing results. The above results have reference value for further bioinformatics research on functional genes of Youzhou dark goat. This study provides basic data for the mining, development and utilization of characteristic traits of local goat genetic resources in China.
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