Fast and powerful statistical method for context-specific QTL mapping in multi-context genomic studies

Abstract

Recent studies suggest that context-specific eQTLs underlie genetic risk factors for complex diseases. However, methods for identifying them are still nascent, limiting their comprehensive characterization and downstream interpretation of disease-associated variants. Here, we introduce FastGxC, a method to efficiently and powerfully map context-specific eQTLs by leveraging the correlation structure of multi-context studies. We first show via simulations that FastGxC is orders of magnitude more powerful and computationally efficient than previous approaches, making previously year-long computations possible in minutes. We next apply FastGxC to bulk multi-tissue and single-cell RNA-seq data sets to produce the most comprehensive tissue- and cell-type-specific eQTL maps to date. We then validate these maps by establishing that context-specific eQTLs are enriched in corresponding functional genomic annotations. Finally, we examine the relationship between context-specific eQTLs and human disease and show that FastGxC context-specific eQTLs provide a three-fold increase in precision to identify relevant tissues and cell types for GWAS variants than standard eQTLs. In summary, FastGxC enables the construction of context-specific eQTL maps that can be used to understand the context-specific gene regulatory mechanisms underlying complex human diseases.

Single-cell RNA-seq reveals cell type–specific molecular and genetic associations to lupus

“…Cis-eQTLs were mapped ±100 kb of each gene using the MatrixEQTL package accounting for genotype PCs, expression PCs, age, sex, SLE status, and batch as covariates in the linear model. Cell type–specific eQTLs were mapped using the fastGxC method ( 31 ). CLUES Asian, CLUES European, and ImmVar samples were analyzed separately, then meta-analyzed using the METASOFT package.…”

“…The rG and rE estimates suggest that pleiotropic genetic and shared residual effects are common across immune cell types, which may confound the ability to detect cell type–specific signals among CBC-eQTLs. To account for pleiotropy, we decomposed per–cell type expression profiles into a shared component across all cell types and eight cell type–specific components, then mapped cis-eQTLs associated with each component ( 31 ). We identified 535 genes with at least one cell type–specific cis - eQTL (cs-eQTL) (FDR < 0.05) and 1207 shared cis - eQTLs (sh-eQTLs) (Fig.…”

Multi-context genetic modeling of transcriptional regulation resolves novel disease loci

“…We developed CONTENT, a method for generating genetic predictors of gene expression across contexts for use in downstream applications such as TWAS. Briefly, for each individual, CONTENT leverages our recently developed FastGxC method 16 to decompose the gene expression across C contexts into one context-shared component and C context-specific components (Fig. 1).…”

“…We used simulation parameters from GTEx, the largest multicontext eQTL study to-date, as a guideline. Specifically, we generated gene expression and genotype data such that context-specific genetic effects mostly lie on the same loci as context-shared eQTLs, and context-specific eQTLs without context-shared effects are rare 2,16 . Intuitively, this framework assumes that, most often, SNPs affect expression of a gene in all contexts, but to a different extent in each context (rather than, for example, acting as an eQTL in only a single context).…”

“…Here, we introduce CONTENT-CONtexT spEcific geNeTics-a method that leverages the correlation structure of multi-context studies to efficiently and powerfully generate genetic predictors of gene expression. Briefly, CONTENT decomposes the gene expression of each individual across contexts into context-shared and contextspecific components 16 , builds genetic predictors for each component separately, and creates a final predictor using both components. To identify genes with significant disease associations, CONTENT employs a hierarchical testing procedure (termed "hFDR"; see Supplementary Fig.…”