Dynamic network-guided CRISPRi screen identifies CTCF-loop-constrained nonlinear enhancer gene regulatory activity during cell state transitions

动态网络引导的 CRISPRi 筛选可识别细胞状态转换期间 CTCF 环约束的非线性增强子基因调控活性

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作者:Renhe Luo, Jielin Yan, Jin Woo Oh, Wang Xi, Dustin Shigaki, Wilfred Wong, Hyein S Cho, Dylan Murphy, Ronald Cutler, Bess P Rosen, Julian Pulecio, Dapeng Yang, Rachel A Glenn, Tingxu Chen, Qing V Li, Thomas Vierbuchen, Simone Sidoli, Effie Apostolou, Danwei Huangfu, Michael A Beer

Abstract

Comprehensive enhancer discovery is challenging because most enhancers, especially those contributing to complex diseases, have weak effects on gene expression. Our gene regulatory network modeling identified that nonlinear enhancer gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Using human embryonic stem cell definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. We discovered a comprehensive set of enhancers for each of the core endoderm-specifying transcription factors. Many enhancers had strong effects mid-transition but weak effects post-transition, consistent with the nonlinear temporal responses to enhancer perturbation predicted by the modeling. Integrating three-dimensional genomic information, we were able to develop a CTCF-loop-constrained Interaction Activity 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 systematic enhancer discovery in both normal and pathological cell state transitions.

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