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Related Experiment Video

Updated: May 20, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Identifying functional links between genes by evolutionary transcriptomics.

David H Silver¹, Michal Levin, Itai Yanai

¹Department of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel. yanai@technion.ac.il

Molecular Biosystems

|July 10, 2012

Summary

This summary is machine-generated.

Evo-links identify gene functional relationships by analyzing expression patterns across species. This method reveals gene communities and developmental pathways, outperforming traditional correlation measures.

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Area of Science:

Comparative genomics
Systems biology
Evolutionary biology

Background:

Gene expression profiles across species can reveal functional gene relationships.
Divergence in gene expression across species is significant and underexplored for functional link detection.
Transcriptome data can distinguish functionally related from independent genes.

Purpose of the Study:

Introduce evo-links, a novel method for inferring functional gene relationships.
Validate evo-links against conventional correlation measures for accuracy.
Utilize evo-links to uncover gene communities and developmental pathways.

Main Methods:

Linking gene pairs with consistent within-species expression similarity and low cross-species conservation.
Analyzing gene networks constructed via evo-links.
Classifying gene communities to identify cell types and developmental timelines.

Main Results:

Genes connected by evo-links show higher enrichment in known functional interactions compared to correlation-based links.
The evo-links network identifies distinct gene communities representing functional pathways.
A temporal developmental map for Caenorhabditis elegans tissue specification was derived, showing sequential activation of endoderm, muscle, neurons, and pharynx.

Conclusions:

Evo-links provide a robust method for detecting functional gene relationships using comparative transcriptomics.
The method effectively disentangles complex developmental pathways, even in data lacking spatial resolution.
Evo-links advance the analysis of cross-species gene expression data for biological discovery.