Determining causality and consequence of expression quantitative trait loci.
Expression quantitative trait loci (eQTLs) are currently the most abundant and systematically-surveyed class of functional consequence for genetic variation. Recent genetic studies of gene expression have identified thousands of eQTLs in diverse tissue types for the majority of human genes. Application of this large eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases. However, only now has both the availability of individuals with full genomes and corresponding advances in functional genomics provided the opportunity to dissect eQTLs to identify causal regulatory variants. Resolving the properties of such causal regulatory variants is improving understanding of the molecular mechanisms that influence traits and guiding the development of new genome-scale approaches to variant interpretation. In this review, we provide an overview of current computational and experimental methods for identifying causal regulatory variants and predicting their phenotypic consequences.
Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA, ajbattle@cs.stanford.edu.
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D003198:Computer Simulation; D030541:Databases, Genetic; D044127:Epigenesis, Genetic; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D005819:Genetic Markers; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci
D005819:Genetic Markers