Cellular Noise Regulons Underlie Fluctuations in Saccharomyces cerevisiae
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Stochasticity is a hallmark of cellular processes, and different classes of genes show large differences in their cell-to-cell variability (noise). To decipher the sources and consequences of this noise, we systematically measured pairwise correlations between large numbers of genes, including those with high variability. We find that there is substantial pathway variability shared across similarly regulated genes. This induces quantitative correlations in the expression of functionally related genes such as those involved in the Msn2/4 stress response pathway, amino-acid biosynthesis, and mitochondrial maintenance. Bioinformatic analyses and genetic perturbations suggest that fluctuations in PKA and Tor signaling contribute to pathway-specific variability. Our results argue that a limited number of well-delineated "noise regulons" operate across a yeast cell and that such coordinated fluctuations enable a stochastic but coherent induction of functionally related genes. Finally, we show that pathway noise is a quantitative tool for exploring pathway features and regulatory relationships in un-stimulated systems.
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Allele-intrinsic variation is due to stochastic factors intrinsic to the molecular mechanisms that control gene expression.
“The second is allele-intrinsic variation, namely stochastic factors intrinsic to the molecular mechanisms that control gene expression40–42.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [41]
Several studies have analyzed the covariation structure between transcripts or proteins across single cells to infer regulatory relations.
“Leveraging this insight, several studies have analyzed the covariation structure between transcripts or proteins across single cells to infer regulatory relations1–3,41,135,137,168–172.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [41]
Correlating the expression profiles of genes or proteins opens the way to elucidating the regulatory mechanisms that control them.
“In analogy to simple observational approaches for inferring gene regulation, correlating the expression profiles of genes or proteins opens the way to elucidating the regulatory mechanisms that control them2,3,41,169,170.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [41]
Because of both stochastic and regulated differences between cells, each cell forms its own 'perturbation system', in which multiple regulators are subtly or more strongly perturbed, possibly reducing the need for additional experimental perturbations.
“Second, because of both stochastic and regulated differences between the cells, each cell forms its own ‘perturbation system’, in which multiple regulators are subtly, or more strongly, perturbed, possibly reducing the need for additional experimental perturbations3,41.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [41]
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- Authors
- Stewart-Ornstein, J., Weissman, J. S., & El-Samad, H.
- Affiliations
- QB3 (US)
- Corresponding author
- Weissman, Jonathan S.
- Venue
- Molecular Cell
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 45
- Issue
- 4
- Pages
- 483-493
- ISSN
- 1097-2765 (ISSN-L)
- PMC
- PMC3327736
- OpenAlex
- W2018864252
- Cited by
- 177
- References
- 46
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 20 · 2023: 6 · 2022: 11 · 2021: 8 · 2020: 5 · 2019: 10 · 2018: 10 · 2017: 17 · 2016: 9 · 2015: 20 · 2014: 17 · 2013: 20 · 2012: 8
- FWCI
- 8.36
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 532 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Molecular Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- University of California, San Francisco
- National Institute of General Medical Sciences (P50GM081879)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- stochastic gene expression, Saccharomyces cerevisiae, gene expression correlation, amino acid biosynthesis, mitochondrial maintenance, PKA signaling, TOR signaling, stochastic gene regulation, cell-to-cell variability
- MeSH terms
- Luminescent Proteins, Promoter Regions, Genetic, Saccharomyces cerevisiae, Stochastic Processes, Stress, Physiological, Signal Transduction, Gene Expression Regulation, Fungal, Protein Serine-Threonine Kinases, Cyclic AMP-Dependent Protein Kinases, Regulon, Computational Biology, Saccharomyces cerevisiae Proteins, Gene Regulatory Networks
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