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Related Experiment Video

Updated: May 17, 2026

A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis

A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis

Published on: August 11, 2010

A functional selection model explains evolutionary robustness despite plasticity in regulatory networks.

Naomi Habib¹, Ilan Wapinski, Hanah Margalit

¹School of Computer Science and Engineering, Hebrew University, Jerusalem, Israel.

Molecular Systems Biology

|October 24, 2012

Summary

This summary is machine-generated.

Regulatory networks evolve through rewiring, allowing species diversity. This study shows transcription factor DNA motifs are conserved, but their gene targets change, enabling functional fine-tuning during evolution.

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Published on: December 7, 2021

Area of Science:

Evolutionary biology
Genomics
Systems biology

Background:

Evolutionary rewiring of regulatory networks drives species diversity.
Assessing regulatory network plasticity is challenging due to data limitations and computational noise.

Purpose of the Study:

To systematically assess cis-regulatory evolution across species.
To trace the evolutionary history of transcription factor DNA motifs and their targets.

Main Methods:

Developed a novel computational approach to study cis-regulatory evolution.
Analyzed 88 DNA motifs of transcription factors in 23 Ascomycota fungi species.
Modeled selective pressures on transcription factor function and target gene regulation.

Main Results:

Transcription factor DNA motifs are generally conserved across species.
Significant gain and loss of target gene regulation by motifs were observed.
Biological processes regulated by motifs remained largely conserved despite target gene turnover.
A model explains these trends with strong selection on overall function and weaker selection on specific targets.

Conclusions:

Selective pressures on gene regulatory networks tolerate local rewiring.
This plasticity allows for subtle fine-tuning of gene regulation during evolution.
The findings provide insights into the mechanisms of regulatory network evolution and species diversification.