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<p>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 <i>POU5F1</i> module.</p>

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CroCoNet: a framework for the quantitative comparison of gene regulatory networks across species

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月15日

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  • Anita Térmeg,
  • Vladyslav Storozhuk,
  • Zane Kliesmete,
  • Fiona C. Edenhofer,
  • Johanna Geuder,
  • Tamina Dietl,
  • Beate Vieth,
  • Philipp Janssen,
  • Daniel Richter,
  • Boyan Bonev,
  • Ines Hellmann

摘要

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.