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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
The effects of network neighbours on protein evolution
Guang-Zhong Wang1, Martin J Lercher
1Institute for Computer Science, Heinrich-Heine-University, Düsseldorf, Germany.
Plos One
|May 3, 2011
Summary
Neighbouring proteins in biological networks evolve at similar rates, especially when they have similar expression levels. This evolutionary correlation holds across various network types, including protein-protein, co-expression, and metabolic networks.
Area of Science:
- Evolutionary Biology
- Systems Biology
- Bioinformatics
Background:
- Interacting proteins often face similar evolutionary pressures.
- Previous studies demonstrated correlated evolution rates in protein-protein interaction networks.
Purpose of the Study:
- To investigate if correlated evolutionary rates extend to other biological networks.
- To determine the factors driving these correlated rates.
Main Methods:
- Analysis of evolutionary rates in protein-protein, co-expression, metabolic, and synthetic lethal genetic interaction networks.
- Statistical analysis to quantify correlation magnitudes and control for confounding factors like expression level, gene essentiality, and gene length.
Main Results:
- Correlated evolutionary rates were found in all investigated network types, though the effect size was small (2-7%).
- Protein expression level was a significant predictor of evolutionary rates, explaining correlations in protein-protein and metabolic networks.
- Even after controlling for expression, essentiality, and length, co-expression and synthetic lethal networks showed residual correlations, suggesting functional relatedness.
Conclusions:
- Similar expression levels and functional relatedness (inferred from network interactions) explain correlated evolutionary rates of network neighbors across diverse biological networks.
- While network effects are statistically significant, they explain a small portion of the variation in protein evolution rates compared to expression levels.
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