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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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CladeOScope-GSA: Revealing Evolutionary Associations Across Gene Sets.

Maya Braun1, Idit Bloch1, Dana Sherill-Rofe1

  • 1Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Hebrew University of Jerusalem, Jerusalem 9112102, Israel.

International Journal of Molecular Sciences
|February 13, 2026
PubMed
Summary

This study introduces CladeOScope-GSA, a novel tool that analyzes gene set evolution using normalized phylogenetic profiling (NPP). It reveals co-evolutionary patterns to uncover gene network structures and functions.

Keywords:
comparative genomicsfunctional genomicsgene set analysisphylogenetic profiling

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Area of Science:

  • Evolutionary Biology
  • Genomics
  • Bioinformatics

Background:

  • Understanding gene and protein functions is crucial in biology and medicine.
  • Existing gene set and multi-omics tools often neglect evolutionary patterns.
  • Gene conservation and loss patterns hold significant co-evolutionary signals.

Purpose of the Study:

  • To develop a tool that incorporates evolutionary patterns into gene set analysis.
  • To identify cohesive evolution or distinct co-evolving submodules within gene sets.
  • To reveal structural organization and key components of gene networks.

Main Methods:

  • Application of normalized phylogenetic profiling (NPP) across 1905 eukaryotic species.
  • Development of CladeOScope-GSA for analyzing user-defined gene sets.
  • Tracing gene set origins, diversification, and evolutionary histories.

Main Results:

  • CladeOScope-GSA uncovers common conservation signatures in gene sets.
  • The tool distinguishes between cohesive and modular evolution of gene sets.
  • Analysis of the porphyria pathway and dynein gene family revealed known substructures and new evolutionary insights.

Conclusions:

  • CladeOScope-GSA provides valuable insights into gene function and pathway evolution.
  • The tool enhances the understanding of gene network organization and relationships.
  • Incorporating evolutionary patterns offers a powerful approach to biological interpretation.