Integrating GWAS and Expression Data for Functional Characterization of Disease-Associated SNPs: An Application to Follicular Lymphoma

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• 作者：Lucia Conde¹ ; ⁴ ; Paige M. Bracci² ; Rhea Richardson³ ; Stephen B. Montgomery³ ; ^{smontgom@stanford.edu} ; Christine F. Skibola¹ ; ⁴ ; ^{chrisfs@berkeley.edu}
• 刊名：The American Journal of Human Genetics
• 出版年：2013
• 出版时间：10 January, 2013
• 年：2013
• 卷：92
• 期：1
• 页码：126-130
• 全文大小：201 K

文摘

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¡ªrs10484561, rs2647012, and rs6457327¡ªby 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.