Dynamic network-guided CRISPRi screen identifies CTCF-loop-constrained nonlinear enhancer gene regulatory activity...

Area of Science:

• Genomics
• Systems Biology
• Developmental Biology

Background:

• Enhancer discovery is challenging due to weak gene expression effects, particularly for complex diseases.
• Gene regulatory network modeling suggests nonlinear dynamics during cell transitions can enhance enhancer discovery sensitivity.

Purpose of the Study:

• To leverage nonlinear gene regulation during cell state transitions for improved enhancer discovery.
• To identify enhancers for core endoderm transcription factors during human embryonic stem cell differentiation.

Main Methods:

• Utilized CRISPR interference (CRISPRi) screening during mid-transition of human embryonic stem cell definitive endoderm differentiation.
• Developed a CTCF-loop-constrained Interaction Activity model integrating 3D genomic data.
• Compared model performance against Hi-C-based enhancer-promoter contact frequency models.

Main Results:

• Discovered a comprehensive set of enhancers for endoderm transcription factors.
• Observed enhancers with strong mid-transition effects but weak post-transition effects, aligning with nonlinear temporal response predictions.
• The CTCF-loop-constrained model showed improved prediction of functional enhancers over Hi-C-based models.

Conclusions:

• Nonlinear enhancer gene regulation during cell state transitions is a powerful strategy for sensitive enhancer discovery.
• The developed model and screening approach offer generalizable methods for identifying functional enhancers.
• This work advances understanding of gene regulation in normal and pathological cell transitions.