Complex Genomic Patterns Characterize Variants in Transcription Factor Binding Associated with Gene Expression

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Although allele-specific transcription factor (TF) binding has been identified at a large number of human genetic variants, known as TF binding quantitative trait loci (bQTLs), very few bQTLs are also linked to detectable changes in gene expression. Classifying the bQTLs that are also gene expression QTLs (eQTLs) is a challenging problem with the potential to illuminate broad patterns underlying TF involvement in gene regulation and the implications for downstream phenotype. We were able to use a machine learning classifier to predict bQTLs that are also eQTLs with high performance using a relatively small number of functional genomics features. We show that linear and three-dimensional proximity between a bQTL and its target gene are most indicative of an association with expression, followed by complex interactions involving genomic structure, multiple TFs, and epigenetic modification, while also showing that bQTLs can mediate gene co-expression and long-range effects on transcription. Our results suggest that bQTLs are marked by diverse yet consistent genomic signatures that elicit future inquiry into the broader regulatory and functional significance of TFs.


Type of resource text
Date created June 10, 2016


Author Hie, Brian
Primary advisor Kundaje, Anshul
Advisor Fraser, Hunter
Advisor Kaplow, Irene
Degree granting institution Stanford University, Department of Computer Science


Subject computer science
Subject computational biology
Subject machine learning
Subject genetics
Subject genomics
Subject gene expression
Subject transcription factor
Genre Thesis

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This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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Hie, Brian. (2016). Complex Genomic Patterns Characterize Variants in Transcription Factor Binding Associated with Gene Expression. Stanford Digital Repository. Available at:


Undergraduate Theses, School of Engineering

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