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10-1101-gr-275107-120 |
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|a 10889051 (ISSN)
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|a Predicting genotype-specific gene regulatory networks
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|b Cold Spring Harbor Laboratory Press
|c 2022
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|a 10
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|z View Fulltext in Publisher
|u https://doi.org/10.1101/gr.275107.120
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|a Understanding how each person's unique genotype influences their individual patterns of gene regulation has the potential to improve our understanding of human health and development, and to refine genotype-specific disease risk assessments and treatments. However, the effects of genetic variants are not typically considered when constructing gene regulatory networks, despite the fact that many disease-associated genetic variants are thought to have regulatory effects, including the disruption of transcription factor (TF) binding. We developed EGRET (Estimating the Genetic Regulatory Effect on TFs), which infers a genotype-specific gene regulatory network for each individual in a study population. EGRET begins by constructing a genotype-informed TF-gene prior network derived using TF motif predictions, expression quantitative trait locus (eQTL) data, individual genotypes, and the predicted effects of genetic variants on TF binding. It then uses a technique known as message passing to integrate this prior network with gene expression and TF protein-protein interaction data to produce a refined, genotype-specific regulatory network. We used EGRET to infer gene regulatory networks for two blood-derived cell lines and identified genotype-associated, cell line-specific regulatory differences that we subsequently validated using allele-specific expression, chromatin accessibility QTLs, and differential ChIP-seq TF binding. We also inferred EGRET networks for three cell types from each of 119 individuals and identified cell type-specific regulatory differences associated with diseases related to those cell types. EGRET is, to our knowledge, the first method that infers networks reflective of individual genetic variation in a way that provides insight into the genetic regulatory associations driving complex phenotypes. © 2022 Weighill et al.
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|a chromatin
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|a Chromatin
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|a chromatin immunoprecipitation
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|a Chromatin Immunoprecipitation
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|a gene regulatory network
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|a Gene Regulatory Networks
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|a genetics
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|a genotype
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|a Genotype
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|a human
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|a Humans
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|a metabolism
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|a transcription factor
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|a Transcription Factors
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|a Glass, K.
|e author
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|a Guebila, M.B.
|e author
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|a Platig, J.
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|a Quackenbush, J.
|e author
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|a Weighill, D.
|e author
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|t Genome Research
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