Comparative analysis of gene regulation in single cells using Compass

Area of Science:

• Genomics
• Computational Biology
• Molecular Biology

Background:

• Single-cell multi-omics technologies enable simultaneous measurement of gene expression and chromatin accessibility in individual cells.
• Current analyses often focus on single tissues, limiting the understanding of tissue-specific gene regulation.
• Distinguishing tissue-specific cis-regulatory element (CRE) functions from broadly acting ones remains a challenge.

Purpose of the Study:

• To develop a computational framework for comparative analysis of gene regulation across a large number of human and mouse tissues.
• To enable the identification of tissue-specific CRE-gene linkages and associated regulatory factors.
• To provide an accessible resource for exploring cross-tissue gene regulation.

Main Methods:

• Development of CompassDB, a comprehensive database of processed single-cell multi-omics data from over 2.8 million cells across diverse human and mouse tissues.
• Creation of CompassR, an open-source R software package for analyzing and visualizing data from CompassDB.
• Application of CompassR to identify CRE-gene associations and transcription factor activities in a multi-tissue context.

Main Results:

• CompassDB integrates extensive single-cell multi-omics data, facilitating large-scale comparative analyses.
• CompassR enables effective visualization and comparison of gene regulatory landscapes across multiple tissues.
• The framework successfully identified tissue-specific CRE-gene linkages and their relevant transcription factors in case studies.

Conclusions:

• Compass provides a powerful platform for dissecting tissue-specific gene regulation using single-cell multi-omics data.
• The developed tools facilitate the discovery of novel regulatory mechanisms underlying tissue diversity.
• This approach advances our understanding of how cis-regulatory elements contribute to cell-type and tissue-specific gene expression patterns.