Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics

Area of Science:

• Molecular Biology
• Genomics
• Systems Biology

Background:

• Gene regulatory networks (GRNs) govern cell function and identity.
• Challenges persist in inferring dynamic, context-specific GRNs and their feedback loops.

Purpose of the Study:

• To develop an advanced method, Dictys, for dynamic GRN inference and analysis.
• To address limitations in current GRN inference methods, including dynamic rewiring and context specificity.

Main Methods:

• Dictys integrates multiomic single-cell assays (chromatin accessibility, gene expression).
• It employs context-specific transcription factor footprinting and stochastic process networks.
• Probabilistic modeling of single-cell RNA-sequencing data is utilized for efficient analysis.

Main Results:

• Dictys enhances GRN reconstruction accuracy and reproducibility.
• It enables inference and comparison of context-specific and dynamic GRNs across developmental stages.
• Network analyses provide novel insights into human blood and mouse skin development.

Conclusions:

• Dictys offers a powerful tool for understanding dynamic GRNs in development and disease.
• Dynamic network visualizations facilitate the discovery of key developmental transcription factors.
• The open-source Python package Dictys is accessible for broad scientific use.