One of the fundamental questions in human biology is how one genome sequence can direct the cellular response to so many developmental and environmental cues. The answer lies, at least in part, in the intricate regulation of transcription such that different cues elicit different programs of gene expression. It is now clear that 3D genome organization is a key factor in the regulation of gene expression. In this component, we propose to generate a robust foundation of 3D interactome datasets that can support a paradigm shift in the study of the structure and function of our genome. The work proposed here will address major gaps in our knowledge of 3D genome organization by first mapping 3D interactions at high resolution in a diverse set of human cell types using improved methodology and data analysis strategies.
In Aim 1, we plan to focus on the differentiation of human embryonic stem cells to pancreatic progenitor cells, a multi-stage process that offers the opportunity for systematic assessment of the dynamics of chromatin organization and the functional relationship between chromatin architecture and lineage-specific gene expression. These high-resolution interactome maps will be analyzed together with complementary trasncriptome and epigenome datasets to illuminate the relationship between 3D genome organization and genome function.
In Aim 2, we will characterize chromatin organization at high resolution in a diverse panel of 30 primary human cell types, and leverage rich datasets of public transcriptome and epigenome data to illuminate the relationship between genome organization and lineage-specific gene expression. The proposed research, if completed, will help uncover functional interactions between cis-regulatory elements across a diverse panel of human cell types. Such datasets will be able to link distal regulatory regions to putative target genes, which will be of major value to the broader biomedical research community and will be useful in furthering our understanding of the mechanisms of distal disease associated regulatory variants in our genome.
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