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

Stefano Di Giovenale1,2, Ottavio Lischio1, Clelia Cortile1,3

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Summary

We developed T-ChroNet, a novel network method to model cis-regulatory element (CRE) co-accessibility over time. This approach reveals regulatory programs crucial for cell fate, development, and disease.

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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.