Kavli Affiliate: Michael Beer
| Authors: Renhe Luo, Jielin Yan, Jin Woo Oh, Wang Xi, Dustin Shigaki, Wilfred Wong, Hyunwoo Cho, Dylan Murphy, Ronald Cutler, Bess P. Rosen, Julian Pulecio, Dapeng Yang, Rachel Glenn, Tingxu Chen, Qing V. Li, Thomas Vierbuchen, Simone Sidoli, Effie Apostolou, Danwei Huangfu and Michael A. Beer
| Summary:
Comprehensive enhancer discovery is challenging because most enhancers, especially those affected in complex diseases, have weak effects on gene expression. Our network modeling revealed that nonlinear enhancer-gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Utilizing hESC definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. The screen discovered a comprehensive set of enhancers (4 to 9 per locus) for each of the core endoderm lineage-specifying transcription factors, and many enhancers had strong effects mid-transition but weak effects post-transition. Through integrating enhancer activity measurements and three-dimensional enhancer-promoter interaction information, we were able to develop a CTCF loop-constrained Interaction Activity (CIA) model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and more comprehensive enhancer discovery in both normal and pathological cell state transitions.