Cell-cycle dependence of transcriptome gene modules: comparison of regression lines
Alexander E Vinogradov1, Olga V Anatskaya1
1Institute of Cytology, Russian Academy of Sciences, St. Petersburg, Russia.
The FEBS Journal
|February 22, 2020
Summary
Gene module expression is heavily influenced by cell-cycle activity, a dependency crucial for accurate transcriptome analysis. This study reveals consistent cell-cycle signatures across normal and cancer cells, impacting gene expression patterns.
Area of Science:
- Transcriptomics and Systems Biology
- Single-cell Analysis
- Cell Cycle Regulation
Background:
- Gene modules within the transcriptome exhibit interdependencies.
- Ignoring these dependencies, particularly on cell-cycle activity, can lead to misinterpretations.
- Cell-cycle progression significantly impacts gene expression profiles.
Purpose of the Study:
- To investigate and quantify gene module dependencies on cell-cycle signature using a large-scale meta-analysis.
- To develop a visual analysis method for gene module-specific regression lines as a complement to enrichment analysis.
- To explore cell-cycle variations independent of cell cycle progression and their implications in various biological contexts.
Main Methods:
- Meta-analysis of over 30,000 single-cell transcriptomes.
- Regression analysis of gene module transcript levels against cell-cycle signature.
- Visual analysis of gene module-specific regression lines.
- Application of the approach to study polyploidy, pluripotency, cancer, and phylostratigraphy.
Main Results:
- Consistent negative regression of receptors, plasma membrane, and differentiation genes on cell-cycle signature.
- Consistent positive regression of pluripotency, stress response, DNA repair, and chromatin remodeling genes on cell-cycle signature.
- Observed cell-cycle variations independent of progression, including G2/M checkpoint gene upregulation in polyploid cells and increased activity during stem cell differentiation.
- Upregulation of unicellular interactome in human cancers and greater heterogeneity in cancer cells.
Conclusions:
- Cell-cycle activity is a critical confounding factor in transcriptome analysis that must be accounted for.
- Visual analysis of gene module-specific regression lines provides insights into different cell conditions and biological states.
- The study reveals novel cell-cycle related phenomena in polyploidy, stem cell differentiation, and cancer, highlighting the importance of controlling for cell-cycle effects.
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