Upcoming Events : C3BI Seminars – Large audience – 08/31/2015 at 11:00 am in
Date : 08/31/2015 at 11:00 am Location : Institut Curie, Centre de Recherche – Paris – Amphithéâtre Biologie du développement et cancer Speakers/Trainers : Manolis Kellis, Professor , MIT Computer Science and Artificial Intelligence Lab from Broad Institute of MIT and Harvard For any questions, suggestions (or to volunteer) for future talks/trainings or general feedback please contact us at firstname.lastname@example.org
From Genomics to Medicine: Uncovering and targeting the genetic circuits underlying GWAS and cancer
Perhaps the greatest surprise of genome-wide association studies (GWAS) of human disease is that 90% of top-scoring disease-associated loci lie outside protein-coding regions. This has increased the urgency of mapping non-coding DNA elements and regulatory circuits, in order to understand the molecular basis of human disease. To address this challenge, we have developed and applying new methods to systematically characterize the epigenomic landscape of diverse primary human cells and tissues, resulting in the annotation of 2.3M enhancer elements across 127 primary human tissues and cell types. We also predicted tissue-specific regulatory networks linking these enhancers to their upstream regulators and target genes, and enable us to weave genetic information from GWAS through these networks to recognize preferentially-disrupted genes, regulators, and biological processes. In this talk, I will describe the use of non-coding annotations and circuits for understanding the molecular basis of genetic differences underlying common disease and cancer: (1) We uncover the mechanistic basis of GWAS hits, predicting and experimentally validating the causal variants, cell types of action, upstream regulators, downstream genes, and their molecular, cellular and organismal phenotypes in the context of obesity. (2) We combine genetic and epigenomic evidence to prioritize and experimentally validate weakly-associated variants in the context of cardiac repolarization phenotypes, showing that epigenomic data enables robust discovery with much smaller cohorts. (3) We use our regulatory predictions to identify new cancer genes based on recurrent somatic mutations in their linked upstream regulatory elements, revealing out-of-context de-repression as a common cancer strategy in the context of prostate cancer. These three applications, spanning the spectrum of common, rare, and somatic variants, illustrate the power and broad applicability of epigenomic annotations and regulatory networks for understanding human disease and cancer. More Manolis Kellis is a Professor of Computer Science at MIT, where he directs the MIT Computational Biology Group (compbio.mit.edu). He has helped direct several large-scale genomics projects, including the NIH Roadmap Epigenomics project, the comparative analysis of 29 mammals, the Encyclopedia of DNA Elements (ENCODE) project, and the Genotype Tissue-Expression (GTEx) project. He received the US Presidential Early Career Award in Science and Engineering (PECASE), the NSF CAREER award, the Alfred P. Sloan Fellowship. He obtained his Ph.D. from MIT, where he received the Sprowls award for the best doctorate thesis in computer science. He lived in Greece and France before moving to the US.