Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations

Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1–4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer–gene connec...

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Bibliographic Details
Main Authors: Fulco, Charles P., Nasser, Joseph, Jones, Thouis R., Munson, Glen, Bergman, Drew T., Subramanian, Vidya, Grossman, Sharon Rachel, Anyoha, Rockwell, Doughty, Benjamin R., Patwardhan, Tejal A., Nguyen, Tung Hoang, Kane, Michael A., Perez, Elizabeth M., Durand, Neva C., Lareau, Caleb A., Stamenova, Elena K., Aiden, Erez Lieberman, Lander, Eric Steven, Engreitz, Jesse Michael
Other Authors: Broad Institute of MIT and Harvard
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2021
Online Access:https://hdl.handle.net/1721.1/129976
Description
Summary:Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1–4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer–gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test >3,500 potential enhancer–gene connections for 30 genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer–gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.