An intersection network based on combining SNP coassociation and RNA coexpression networks for feed utilization traits in Japanese Black cattle.

摘要: Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect networks feed utilization growth Japanese Black cattle, which are matters concern. A SNP coassociation network was derived from significant correlations between SNPs effects estimated by across 7 phenotypic traits. resulting contained numbers annotations related the Using bovine transcriptome public database, an RNA coexpression inferred based on similarity expression patterns different tissues. An intersection then generated superimposing extracting shared interactions. This 4 tissue-specific modules: nervous system, reproductive muscular glands. To characterize structure (topographical properties) 3 networks, their scale-free properties were evaluated, revealed that most scale-free. In subnetwork containing connected transcription factors (URI1, ROCK2, ETV6), widely expressed tissues, previously shown be involved found. Results indicated current might construct better reflects biological information, providing encouragement for dissection economically important