Gene Expression Dynamics After System Perturbation
Author Information
Author(s): Neretti Nicola, Remondini Daniel, Tatar Marc, Sedivy John M, Pierini Michela, Mazzatti Dawn, Powell Jonathan, Franceschi Claudio, Castellani Gastrone C
Primary Institution: Institute for Brain and Neural Systems, Brown University
Hypothesis
How does gene expression change in response to different perturbations?
Conclusion
The study found that gene expression dynamics exhibit similar coherence patterns across different perturbations.
Supporting Evidence
- The study analyzed three datasets: cMyc activation in rat fibroblasts, nutritional changes in D. melanogaster, and aging in human T-cells.
- Significant gene changes were identified using ANOVA and change-point analysis.
- Correlation networks showed a transition from uncorrelated to correlated gene expression patterns.
Takeaway
When scientists change something in cells, like adding a drug or changing food, the way genes work together can change a lot, and this study looked at those changes.
Methodology
The study used correlation-based methods to analyze time series gene expression data from three different datasets.
Limitations
The datasets were heterogeneous, and not all pathways had been measured due to microarray limitations.
Participant Demographics
The human aging dataset included T-cells from 20 healthy male donors aged 25 to 80.
Statistical Information
P-Value
<0.01
Confidence Interval
95%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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