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Integrating genomic information into cattle breeding is an important approach to exploring the molecular mechanism for complex traits related to diary and meat production. To assist with genomic-based selection, a reference map of interactome is needed to fully understand genotype-phenotype relationships. To this end we constructed a co-expression analysis of 92 tissues and this represents the first systematic exploration of gene-gene relationship in cattle. By using robust WGCNA (Weighted Gene Correlation Network Analysis), we described the gene co-expression network of 13,405 protein-coding genes from the cattle genome. Using the 5,000 genes with majority variations in expression across 92 tissues, we compiled a network with 72,306 co-associations and that provides functional insights into thousands of poorly characterized proteins. Further module identifications found 55 highly organized functional clusters representing diverse cellular activities. To demonstrate the re-use of our interaction for functional genomics analysis, we extracted a sub-network associated with DNA binding genes in cattle. The subnetwork was enriched within regulation of transcription from RNA polymerase II promoter representing central cellular functions. In addition, we identified 28 novel linker genes associated with more than 100 DNA binding genes. Our WGCNA-based co-expression network reconstruction will be a valuable resource for exploring the molecular mechanisms of incompletely characterized proteins and for elucidating larger-scale patterns of functional modulization in the cattle genome.
This is a submission to PeerJ for review.
Table S1. The expression profile for the top 5,000 most variant genes across 92 tissue samples