Dissecting dynamic genetic variation that controls temporal gene response in yeast
Avital Brodt1, Maya Botzman1, Eyal David1
1Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel.
Plos Computational Biology
|December 5, 2014
Summary
This study introduces a computational method to track how genetic variants dynamically affect gene expression over time. It reveals coordinated gene modules with distinct temporal patterns, offering insights into regulatory mechanisms.
Area of Science:
- Genetics
- Systems Biology
- Computational Biology
Background:
- Inter-individual variation in gene expression regulation offers functional insights.
- Genetic variants influence cell circuitry, but their dynamic effects over time are not well understood.
Purpose of the Study:
- To develop a computational method for capturing temporal changes in genetic effects on gene expression.
- To analyze dynamic transcriptional responses during TOR signaling pathway inhibition in yeast.
Main Methods:
- Developed a novel computational procedure to quantify time-varying genetic effects.
- Applied the method to yeast transcription data following TOR pathway inhibition.
- Analyzed temporal genetic effects across co-regulated gene modules.
Main Results:
- Identified high-order coordination of gene modules with shared temporal genetic effect patterns.
- Observed distinct temporal patterns, including state transitions (e.g., phosphate utilization) and impulse responses (e.g., nitrogen utilization).
- Found that inter-individual variation in response timing, not magnitude, characterized some modules.
Conclusions:
- The same underlying mechanisms likely drive both inter-individual variation and temporal genetic effects in gene modules.
- The developed methodology offers a quantitative genetic approach to dissecting dynamic transcriptional regulation.
- This work enhances understanding of molecular mechanisms governing dynamic transcriptional responses.
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