Functional genomics and epigenomics of complex disease genetics

2 Nov 2012

Manolis Kellis
Department of Computer Science and Engineering, MIT, and
The Broad Institute of Harvard and MIT

Abstract

Most disease-associated variants for complex disease lie in non-coding regions, have weak effects, and remain functionally uncharacterized. Genome-wide functional genomics datasets provide the opportunity to build regulatory models that seek to interpret how these contribute to the disease phenotype. In this talk, I will present our efforts to integrate genomic variation, epigenomic variation, and functional genomics datasets with genome-wide association studies to understand the molecular basis of complex disease.

• We use reference epigenomic maps of in multiple human cell types to dramatically expand the annotation of non-coding regions and to link active enhancers to their upstream regulators and their downstream target genes using coordinated patterns of activity across cell types.
• We use the resulting regulatory predictions to revisit disease-associated loci, revealing SNPs that disrupt or create predicted enhancer and causal regulatory motifs, providing mechanistic hypotheses for the observed associations for individual loci.
• Beyond the few genome-wide significant loci retained by traditional GWAS, we find functional enrichments across 1000s of type-1-diabetes-associated SNPs in cell type-specific enhancers using a rank-based statistical test for enrichment.
• Beyond reference epigenomes, we study both genomic and epigenomic variation in Alzheimer's disease across 750 individuals, revealing a global hyper-methylation signature in brain-specific enhancers containing specific motifs and methyl-QTLs for 60,000 probes.
• We systematically validate 1,000s of our regulatory predictions using Massively Parallel Reporter Assays by disrupting individual binding sites and individual nucleotides of predicted causal regulators, revealing their distinct roles in specifying enhancer activity.