2013 Poster Sessions : Computational Methods for Studying the Variation in Expression and Chromatin State Across Individuals and Populations

Student Name : Sofia Kyriazopoulou-Panagiotopoulou
Advisor : Serafim Batzoglou
Research Areas: Artificial Intelligence
Abstract:
The vast majority of disease-associated variants lie outside protein-coding regions, suggesting that variation in regulatory regions may play a major role in disease predisposition. However, despite extensive studies of gene expression differences between individuals, little is known about the underlying regulatory mechanisms. Here, we study the gene expression and chromatin state in lymphoblastoid cell lines from 14 individuals of diverse ancestry. We find that enhancer activity is heritable in trios and much more variable across individuals than gene expression. Using the co-varying patterns of enhancer and gene activity, we are able to assign distal enhancers to the genes they regulate. We present computational methods to identify enhancer regions that are divergent across populations and show that these regions are enriched for signals of positive selection. Finally, we use a novel machine learning framework to associate the genetic differences across individuals to changes in gene expression and demonstrate that this model can improve our understanding of the regulatory interactions between transcription factors. Overall, our results provide fundamental insights into the relationship between genetic diversity across individuals and variability in expression and epigenetic state.

Bio:
I am a Ph.D. student at Stanford University working on computational genomics. My research focuses on developing machine learning algorithms to infer the mechanisms of gene expression in cells from different cell lines. My work involves integrating large genomic datasets, such as the data from the ENCODE Consortium and the 1000 Genomes Project, in order to study the variability of gene expression and to model the regulatory interactions within a human cell. I am also interested in developing computational tools to study cancer progression from sequencing data. At Stanford, I have served as a teaching assistant for classes in algorithms and computational genomics. I received my B.S. in Computer Science from the Athens University of Economics and Business, where I worked on statistics and databases.