Biology

Dr Abhijeet Sonawane
Brigham and Women\'s Hospital and Harvard Medical School, Boston, USA

Abstract:

The biological processes that drive cellular function can be modeled by a complex network of interactions between regulators (transcription factors) and their targets(genes), summarized by gene regulatory networks (GRNs). In order to correctly interpret perturbations of gene regulation in human disease, it is critical that we develop a holistic understanding of transcriptional regulation in non­diseased tissue. We investigate the regulation of genes across 38 tissues profiled as part of the Genotype Tissue [removed]GTEx) project by estimating regulatory networks for each tissue. We start by evaluating the tissue­specificity of various elements in these regulatory networks. To better understand how this specificity is maintained within the global regulatory context, we analyzed the topological structure of each tissue­specific network. The cell’s “epigenetic state” governs the potential targeting of genes by influencing chromatin accessibility. However, integrating such information to construct GRNs remains a challenge. Here, we demonstrate an approach SPIDER using epigenetic information (DNase-I Seq data) and message-passing algorithm to estimate networks between transcription factors and genes in multiple cell-lines. We validated our predictions against public ChIP-Seq data. We show that SPIDER is more accurate, in predicting GRNs that other methods that integrate epigenetics. I will also elucidate plans to integrate methylation, histone modifications, chromatin conformations and other omics’ data.