Control of Transcript Variability in Single Mammalian Cells
Open accessAbstract
A central question in biology is whether variability between genetically identical cells exposed to the same culture conditions is largely stochastic or deterministic. Using image-based transcriptomics in millions of single human cells, we find that while variability of cytoplasmic transcript abundance is large, it is for most genes minimally stochastic and can be predicted with multivariate models of the phenotypic state and population context of single cells. Computational multiplexing of these predictive signatures across hundreds of genes revealed a complex regulatory system that controls the observed variability of transcript abundance between individual cells. Mathematical modeling and experimental validation show that nuclear retention and transport of transcripts between the nucleus and the cytoplasm is central to buffering stochastic transcriptional fluctuations in mammalian gene expression. Our work indicates that cellular compartmentalization confines transcriptional noise to the nucleus, thereby preventing it from interfering with the control of single-cell transcript abundance in the cytoplasm.
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High confluence in cell culture can lead to spatial dependency in gene expression.
“This indicates that high confluence in cell culture can lead to spatial dependency in gene expression17.”
From SpatialDE: identification of spatially variable genes (2018) · cites this paper as [17]
The number of mRNA molecules may sometimes not correlate well with the numbers of their protein products at the same time point.
“Third, the number of mRNA molecules may sometimes not correlate well with the numbers of their protein products at the same time point180–184”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [184]
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- Authors
- Battich, N., Stoeger, T., & Pelkmans, L.
- Affiliations
- University of Zurich (CH)
- Corresponding author
- Pelkmans, Lucas
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-12
- Volume
- 163
- Issue
- 7
- Pages
- 1596-1610
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2211016425
- Cited by
- 324
- References
- 49
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 24 · 2023: 26 · 2022: 27 · 2021: 35 · 2020: 43 · 2019: 43 · 2018: 42 · 2017: 38 · 2016: 19 · 2015: 2
- FWCI
- 14.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Universität Zürich
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- single-cell transcriptomics, transcriptional noise, nuclear transport, gene expression regulation, cellular compartmentalization, human cells
- MeSH terms
- Animals, Cell Nucleus, Cytoplasm, Humans, Stochastic Processes, Transcription, Genetic, Keratinocytes, In Situ Hybridization, Fluorescence, Gene Expression Profiling, Single-Cell Analysis
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