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CroCoNet: A framework for the quantitative comparison of gene regulatory networks across species.
Genome Biol. 27:228 (2026)
To understand phenotypic evolution, it is essential to investigate the underlying gene regulatory networks (GRNs). However, most comparative GRN analyzes remain descriptive due to the low signal-to-noise ratio inherent in single-cell transcriptomics data. To address this, we introduce CroCoNet (Cross-species Comparison of Networks), an R-package for quantitative GRN comparison across species. CroCoNet builds comparable network modules centered on putative regulators and compares module topologies within and between species, distinguishing true evolutionary divergence from technical and biological confounders. We demonstrate its utility by comparing early neural differentiation across primates and validating results with a CRISPRi analysis of the diverged POU5F1 module.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Gene Regulatory Network ; Divergence (linguistics) ; Human Genetics ; Gene ; Network Topology ; Regulatory Sequence ; Transcriptome ; Network Analysis; Cell Fate; Expression; Evolution; Progenitor; Differentiation; Induction; Inference; Binding; Pax6; Es
ISSN (print) / ISBN
1474-760X
e-ISSN
1465-6906
Journal
Genome Biology
Quellenangaben
Volume: 27,
Issue: 1,
Article Number: 228
Publisher
Springer
Publishing Place
Campus, 4 Crinan St, London N1 9xw, England
Reviewing status
Peer reviewed
Institute(s)
Research Unit Brain Epigenomics (BEG)
Grants
BioHPC hosted at Leibniz Rechenzentrum Munich funded by the DFG
Deutsche Forschungsgemeinschaft (DFG)
European Research Council Consolidator Grant
Deutsche Forschungsgemeinschaft (DFG)
European Research Council Consolidator Grant