Integrating GWAS and Expression Data for Functional Characterization of Disease-Associated SNPs: An Application to Follicular Lymphoma |
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| Authors: | Lucia Conde Paige?M. Bracci Rhea Richardson Stephen?B. Montgomery Christine?F. Skibola |
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| Affiliation: | 1.Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-7360, USA;2.Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA 94118-1944, USA;3.Departments of Pathology and Genetics, Stanford University, Stanford, CA 94305-5324, USA |
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| Abstract: | Development of post-GWAS (genome-wide association study) methods are greatly needed for characterizing the function of trait-associated SNPs. Strategies integrating various biological data sets with GWAS results will provide insights into the mechanistic role of associated SNPs. Here, we present a method that integrates RNA sequencing (RNA-seq) and allele-specific expression data with GWAS data to further characterize SNPs associated with follicular lymphoma (FL). We investigated the influence on gene expression of three established FL-associated loci—rs10484561, rs2647012, and rs6457327—by measuring their correlation with human-leukocyte-antigen (HLA) expression levels obtained from publicly available RNA-seq expression data sets from lymphoblastoid cell lines. Our results suggest that SNPs linked to the protective variant rs2647012 exert their effect by a cis-regulatory mechanism involving modulation of HLA-DQB1 expression. In contrast, no effect on HLA expression was observed for the colocalized risk variant rs10484561. The application of integrative methods, such as those presented here, to other post-GWAS investigations will help identify causal disease variants and enhance our understanding of biological disease mechanisms. |
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