CAREER: Computational methods for interpreting epigenomics datasets

Joan And Sanford I. Weill Medical College Of Cornell University, New York NY

Investigators

Abstract

This project will develop novel computational methods to perform integrative analysis of epigenomics and chromatin interaction datasets obtained from ChIP-seq and Hi-C experiments, respectively, and use these methods to discover the principles by which enhancers and other distal regulatory elements contribute to the regulation of transcription in cells. The primary objectives are (1) to create a novel user-friendly computational framework for the identification, annotation and comprehensive integrative interpretation of epigenomics datasets obtained by deep sequencing, (2) to extend this framework to provide methods for analyzing the chromatin interaction network which links together genomic elements revealed by epigenomic analysis, including promoters and distal regulatory elements and (3) to use the framework to systematically discover and characterize distal regulatory elements in the human genome, determine their cis-regulatory code, reconstruct and characterize the network of chromatin interactions in which they are embedded. Reporter-based assays will then be performed to test these predictions and further characterize the function of these regulatory elements. The framework will include several innovative computational methodologies for ChIP-seq peak detection, Hi-C interaction detection, information-theoretic discovery of sequence regulatory codes, information-theoretic cellular pathway analysis, graph theoretical analysis of chromatin interaction networks, and data visualization including immersive 3D visualization. The proposed framework, associated source code and extensive documentation will be made freely available online through our website (http://physiology.med.cornell.edu/faculty/elemento/lab/). Moreover, educational workshops and seminars will be developed to propagate the proposed framework and its use by investigators at all levels, from undergraduate, graduate students and postdoctoral scientists to faculty and research staff. This project will create novel computational methods to analyze and interpret epigenomics and chromatin interaction datasets and use these methods together with experimentation to discover and characterize the principles by which regulatory elements situated far away from genes contribute to the regulation of transcription in cells. The educational component of the project will include the organization of technical workshops to propagate the methodologies and software to be developed during the course of this project. It will also include seminars on epigenomic analysis for the broader scientific community, as well as mentored undergraduate research in our laboratory.