CAGEE

CAGEE infers genome-wide evolutionary changes in gene expression across phylogenies to estimate rates and ancestral states from whole-transcriptome data.

Key Features:

• Phylogenetic integration: Integrates phylogenetic information rather than analyzing genes independently to provide a genome-wide view of gene expression evolution.
• Genome-wide rate estimation: Calculates genome-wide rates of change in gene expression across a phylogenetic tree.
• Ancestral state inference: Infers ancestral expression states for each gene on a phylogeny.
• Lineage-specific rate shifts: Identifies lineage-specific shifts in evolutionary rates of gene expression across the genome.
• Tissue-specific analysis: Compares differences in gene expression evolution rates among multiple tissues sampled from the same species.
• Statistical framework: Employs a statistical framework that has been validated by simulations and applied to empirical datasets.
• Empirical application: Applied to ovule gene expression data from self-compatible and self-incompatible species in the genus Solanum to test hypotheses about evolutionary forces during mating system shifts.

Scientific Applications:

• Phylogenetic transcriptomics: Analysis of transcriptome-wide gene expression evolution across species using phylogenies.
• Rate-shift detection: Detection and characterization of lineage- and tissue-specific shifts in rates of gene expression evolution.
• Evolutionary hypothesis testing: Testing hypotheses about evolutionary processes such as mating system shifts (e.g., self-compatible vs self-incompatible Solanum).
• Mechanistic inference: Investigating patterns and rates of gene expression change to infer genetic mechanisms underlying evolutionary adaptations and trait development.

Methodology:

Integrates whole-transcriptome data with phylogenetic trees to calculate genome-wide rates of expression change and infer ancestral states using a statistical framework validated by simulations and applied to empirical datasets.