Defining interaction quantitative trait loci (iQTLs) in the human genome

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Abstract My research aims to understand the role of three-dimensional (3D) chromatin structure in gene regulation. This involves studying associations among genotype, histone modifications, transcription factor binding, non-coding RNAs, chromatin interactions and gene expression. In order to transform this genome-wide information into new biological discoveries, my laboratory develops scalable and interpretable computational methods based on statistics, graph theory and machine learning. Our recent focus is to address an important gap in the current knowledge of the role of 3D chromatin structure in gene regulation. That is, we aim to define how genotypic variation affects 3D organization of gene promoters, and in turn, their expression. To achieve this at a genome-wide scale is an ambitious goal, because it requires having at a minimum, genotype, gene expression and chromatin interaction profiles in pure populations of specific cell types from a large number of donors. However, my laboratory is uniquely positioned to perform this research because: i) we are involved in a study at the La Jolla Institute (LJI-R24AI108564) that has already genotyped ~100 donors and expression-profiled more than 15 different pure populations of human immune cell types, and we have access to the same samples for chromatin interaction mapping, ii) in collaboration with other groups at LJI, we have already discovered a prototypical example of an interaction quantitative trait locus (iQTL) that alters and rewires interactions from the promoter of a specific gene that is associated with asthma susceptibility, iii) we have the necessary expertise and proven track record in experimental design and computational analyses of various chromatin conformation capture assays. Leveraging the resources available at LJI and our expertise in the field, we will build a unique research program around the novel concept of iQTLs. The emerging set of three main questions we propose to address within the next five years are: Q1) How do we define cell-type-specific iQTLs for common genetic variants? Q2) What is the extent of overlap between iQTLs and GWAS SNPs? Q3) Can we build predictive models for the cell-type specificity of chromatin interactions and iQTLs? Although we propose to define iQTLs only in two abundant, easily accessible, and highly disease-relevant immune cell types, the concept of iQTLs is equally important in other cell types implicated in diseases with a genetic component. Hence, the proof-of-concept developed by this work, without a doubt, will open up a new field in studying a previously uncharacterized role for disease-susceptibility variants, specifically non-coding SNPs, from genome-wide association studies (GWAS) in gene regulation.