T-ChroNet: Time-aware chromatin network reconstruction to detect dynamic regulatory programs in longitudinal...

Area of Science:

• Genomics
• Systems Biology
• Computational Biology

Background:

• Biological networks are vital for understanding complex biological systems.
• Gene co-expression and regulatory networks have advanced transcriptional modulation studies.
• Limited computational methods exist to integrate cis-regulatory element (CRE) activity into networks.

Purpose of the Study:

• To develop a network-based computational method for modeling temporal CRE activity.
• To infer upstream regulators and downstream pathways involved in cell fate and disease.
• To capture dynamic regulatory programs using time-aware network analysis.

Main Methods:

• Introduced T-ChroNet (Time-aware Chromatin Network), a method modeling CREs as nodes and temporal co-accessibility as edges.
• Utilized temporally-resolved chromatin accessibility (ATAC-seq) and H3K27ac ChIP-seq data from human and mouse.
• Detected CREs with similar accessibility patterns over time to infer regulatory relationships.

Main Results:

• T-ChroNet successfully identified known regulators and enriched pathways across species and data types.
• The method uncovered novel putative factors and mechanisms regulating key biological processes.
• Demonstrated the ability to model temporal CRE dynamics for biological insights.

Conclusions:

• T-ChroNet provides a powerful framework for network-based analysis of temporal CRE activity.
• The method aids in understanding regulatory mechanisms in cell identity, development, and disease.
• Highlights the importance of integrating temporal dynamics into network biology approaches.