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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
Published on: February 11, 2019
Protein evolution in yeast transcription factor subnetworks.
Yong Wang1, Eric A Franzosa, Xiang-Sun Zhang
1Bioinformatics Program, Boston University, Boston, MA 02215, USA.
Nucleic Acids Research
|May 15, 2010
Summary
Transcription factor (TF) hubs evolve faster than generic protein hubs, challenging the idea that network centrality slows evolution. This suggests distinct evolutionary principles govern different network components.
Area of Science:
- Evolutionary biology
- Systems biology
- Genomics
Background:
- Protein hubs with many interactions typically evolve slowly due to negative selection.
- Transcription factors (TFs) are key regulators within cellular networks.
Purpose of the Study:
- To investigate the evolutionary rates of yeast transcription factor hubs compared to generic protein hubs.
- To determine if network centrality influences TF evolution differently than general proteins.
Main Methods:
- Genome-wide analysis of yeast protein-protein interaction and transcriptional regulatory networks.
- Calculation of evolutionary rates (K(A)/K(S)) for transcription factor hubs and non-hubs.
- Comparison of evolutionary patterns between TF hubs and generic protein hubs.
Main Results:
- TF hubs, across various types (interaction, regulatory, co-regulatory), do not evolve significantly slower than TF non-hubs.
- TF regulatory in-degree hubs evolve significantly faster than TF non-hubs.
- Evolutionary rate correlations with degree are more positive for TFs than generic proteins, indicating relaxed negative selection or positive selection.
Conclusions:
- Transcription factor hubs exhibit distinct evolutionary dynamics compared to generic protein hubs within the same cellular networks.
- TF hubs may experience different evolutionary pressures, such as relaxed negative selection or positive selection via network rewiring, due to their higher network position.
- This highlights that components within a global network can follow different organizational and evolutionary principles.
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