Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences
Open accessAbstract
Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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Intrinsic variability arises from random biochemical reactions of biological molecules over time.
“Intrinsic variability arises from random biochemical reactions of biological molecules over time23.”
From Intra- and Inter-individual Variability of microRNA Levels in Human Cerebrospinal Fluid: Critical Implications for Biomarker Discovery (2017) · cites this paper as [23]
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 [42]
Allele-extrinsic variation is due to factors extrinsic to transcription, such as the presence of certain regulators or differences in stable chromatin state.
“The third is allele-extrinsic variation, due to factors42,43 extrinsic to the process of transcription, such as the presence of certain regulators or differences in stable chromatin state.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [42]
Transcript abundance is affected not only by allele-extrinsic factors, but also by allele-intrinsic stochasticity, resulting in its divergence across cells exposed to the same extrinsic triggers.
“First, transcript abundance is affected not only by allele-extrinsic factors, but also by allele-intrinsic stochasticity, resulting in its divergence across cells exposed to the same extrinsic triggers42,43 (see above and Fig. 2).”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [42]
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“Thus, using stable eGFP reporter, as done in our assay, can buffer the effect of rapid fluctuations in mRNA levels (Raj and van Oudenaarden 2008).”
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- Authors
- Raj, A., & van Oudenaarden, A.
- Affiliations
- Massachusetts Institute of Technology (US)
- ORCID
- Raj, Arjun
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2008-10
- Volume
- 135
- Issue
- 2
- Pages
- 216-226
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3118044
- OpenAlex
- W2114870653
- Cited by
- 2,593
- References
- 108
- Citations by year
- 2026: 104 · 2025: 141 · 2024: 153 · 2023: 140 · 2022: 147 · 2021: 163 · 2020: 186 · 2019: 173 · 2018: 169 · 2017: 170 · 2016: 160 · 2015: 160 · 2014: 136 · 2013: 150 · 2012: 134
- FWCI
- 7.85
- 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, 1750 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
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM068957, R01GM077183)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Keywords
- stochastic gene expression, transcriptional noise, cell-to-cell variability, mRNA levels, protein abundance, gene regulatory networks, biophysical parameters, stress response, metabolism, development (biology), cell cycle, circadian rhythm, aging
- MeSH terms
- Animals, Bacteria, Eukaryotic Cells, Humans, Stochastic Processes, Transcription, Genetic, Gene Expression
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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