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CAGEE: Computational Analysis of Gene Expression Evolution.

Jason Bertram1,2, Ben Fulton1,3, Jason P Tourigny1,4

  • 1Department of Biology, Indiana University, Bloomington, IN.

Molecular Biology and Evolution
|May 9, 2023
PubMed
Summary
This summary is machine-generated.

We developed Computational Analysis of Gene Expression Evolution (CAGEE), a new software tool to analyze gene expression changes across species evolution. CAGEE infers genome-wide expression patterns, rates, and ancestral states, aiding evolutionary studies.

Keywords:
SolanumBrownian motionRNA-seqphylogenetic comparative methods

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Area of Science:

  • Evolutionary biology
  • Genomics
  • Bioinformatics

Background:

  • Analyzing global gene expression across species phylogenies is challenging due to limited available methods.
  • Existing methods often analyze genes independently, hindering genome-wide evolutionary insights.

Purpose of the Study:

  • To introduce Computational Analysis of Gene Expression Evolution (CAGEE), a novel software package for phylogenetic gene expression analysis.
  • To enable inference of gene expression changes, rates, and ancestral states across evolutionary lineages.

Main Methods:

  • CAGEE employs a statistical approach to analyze genome-wide gene expression patterns.
  • It infers lineage-specific shifts in evolutionary rates and differences among tissues.
  • The method's accuracy and robustness are validated using simulated data.

Main Results:

  • CAGEE successfully infers genome-wide rates of gene expression evolution and ancestral states.
  • The software identified lineage-specific rate shifts and tissue-specific expression rate differences.
  • Application to *Solanum* ovule expression data revealed insights into mating system shifts.

Conclusions:

  • CAGEE provides a powerful tool for analyzing gene expression evolution across diverse phylogenetic scales.
  • The software is applicable to various empirical systems and aids in studying morphological trait evolution.
  • CAGEE facilitates a deeper understanding of evolutionary forces shaping gene expression.