Abstract：
:Eukaryotic gene expression regulation involves thousands of distal regulatory elements. Understanding the quantitative contribution of individual enhancers to gene expression is critical for assessing the role of disease-associated genetic risk variants. Yet, we lack the ability to accurately link genes with their distal regulatory elements. To address this, we used 3D enhancer-promoter (E-P) associations identified using split-pool recognition of interactions by tag extension (SPRITE) to build a predictive model of gene expression. Our model dramatically outperforms models using genomic proximity and can be used to determine the quantitative impact of enhancer loss on gene expression in different genetic backgrounds. We show that genes that form stable E-P hubs have less cell-to-cell variability in gene expression. Finally, we identified transcription factors that regulate stimulation-dependent E-P interactions. Together, our results provide a framework for understanding quantitative contributions of E-P interactions and associated genetic variants to gene expression.
journal_name
Mol Celljournal_title
Molecular cellauthors
Vangala P,Murphy R,Quinodoz SA,Gellatly K,McDonel P,Guttman M,Garber Mdoi
10.1016/j.molcel.2020.09.005subject
Has Abstractpub_date
2020-10-15 00:00:00pages
359-373.e8issue
2eissn
1097-2765issn
1097-4164pii
S1097-2765(20)30613-4journal_volume
80pub_type
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