Abstract
Background Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), varies across tissues in complex patterns ranging from highly tissue-specific effects to effects shared across many or all tissues. Improved characterization of these patterns may allow us to better understand the biological mechanisms that underlie tissue-specific gene regulation and disease etiology.
Results We develop a constrained matrix factorization model to learn patterns of tissue sharing and tissue specificity of eQTLs across 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors include patterns reflecting tissues with known biological similarity or shared cell types, in addition to a dense factor representing a universal genetic effect across all tissues. To explore the regulatory mechanisms that generate tissue-specific patterns of expression, we evaluate chromatin state enrichment and identify specific transcription factors with binding sites enriched for eQTLs from each factor.
Conclusions Our results demonstrate that matrix factorization can be applied to learn the tissue specificity pattern of eQTLs and that it exhibits better biological interpretability than heuristic methods. We present a framework to characterize the tissue specificity of eQTLs, and we identify examples of tissue-specific eQTLs that may be driven by tissue-specific transcription factor (TF) binding, with relevance to interpretation of disease association.
