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Related Concept Videos

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Related Experiment Video

Updated: Jun 13, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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Comparative analysis of gene regulation in single cells using Compass.

Changxin Wan1, Yilong Qu2, Zhiyou Ye3

  • 1Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA; Program of Computational Biology and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.

Cell Reports Methods
|May 9, 2025
PubMed
Summary

We developed Compass, a tool to compare gene regulation across many tissues using single-cell multi-omics data. Compass identifies tissue-specific gene regulatory elements and their transcription factors.

Keywords:
CP: Systems biologycis-regulatory elementsgene regulationsingle-cell ATAC-seqsingle-cell multi-omics

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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.