MASSIVELY PARALLEL CIS-REGULATORY ELEMENT ANALYSIS IN MAMMALIAN CELLS

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for 1R01HG006790-01 Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. Next-generation sequencing (NGS) technologies such as ChIP-seq are driving the discovery of putative cis-regulatory elements (CREs; i.e., enhancers/promoters) at an astonishing pace. Testing the regulatory potential of these predictions is a serious bottleneck in our efforts to understand the logic of gene regulation in the human genome. Currently there are no viable technologies for functionally testing the thousands of predictions that can be generated from even a single ChIP-seq experiment, let alone the millions of predictions being generated by ENCODE and other consortium-based efforts. Breaking the logjam of CRE predictions requires a new technology that enables massively parallel cis-regulatory analysis in mammalian cells. In this proposal, we introduce CRE-seq (Cis-Regulatory Element analysis by sequencing), a novel technique for assaying thousands of CREs in a single experiment in mammalian cells. Our strategy is to fuse libraries of CREs to barcoded reporter genes, transfect these libraries into cells and quantify their output by NGS. We will develop CRE-seq as an efficient, robust and highly parallel technology for assessing the cis-regulatory activity of thousands of ChIP-seq peaks in a single experiment. If successful, this strategy should make it possible to quantify the promoter activity of entire 'cis-regulomes' (i.e., the entire complement of cis-regulatory regions controlling gene expression in a given cell type). We will demonstrate the utility of this assay by studying cis-regulation in two different mammalian cell types, retinal photoreceptors (a differentiated neuronal cell type) and undifferentiated embryonic stem cells. CRE-seq promises to advance our understanding of human gene regulation and will serve as a novel source of personalized genomic information available for diagnosis and treatment of disease.