Inferring a Core Transcriptional Regulatory Network in Cows

Abstract Text: Most biological processes, like the production of milk in cattle, are the consequence of a complex network of interacting genes. The data-driven inference and analysis of regulatory networks is a crucial step towards a better understanding of such complex phenotypic traits. It is therefore one of the main challenges in computational systems biology. We aim for a more reliable and robust network reconstruction. To this end, we developed a consensus-driven approach to decipher regulatory relationships from gene expression patterns. We applied this approach to microarray gene expression data from three different tissues of early lactating cows. In this way, we inferred a core transcriptional regulatory network with interactions between putative transcription factors and target genes. In a subsequent network analysis we identified several hub genes, each regulating more than hundred target genes.

Keywords:
network inference
lactating cows
transcriptional regulatory networks