ArticleNature microbiology2019
Single-cell imaging and RNA sequencing reveal patterns of gene expression heterogeneity during fission yeast growth and adaptation.
Article in Nature microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 66 citations in OpenAlex.
- Empowering fungal infection research with single-cell RNA sequencing.Communications biology · 2026Review
- Design of the biosensor-dependent coupling system stabilizes the high-synthesis phenotype of cell factory.Nature communications · 2026Article
- Unstressed cells are alike, but stressed cells differ: Environmental and single-cell heterogeneity in yeast stress responses.bioRxiv : the preprint server for biology · 2026Article
- Article
- Advances in Single-Cell Sequencing for Infectious Diseases: Progress and Perspectives.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Cellular heterogeneity in metabolism and associated microbiome of a non-model phytoflagellate.The ISME journal · 2025Article
- Shrinkage estimation of gene interaction networks in single-cell RNA sequencing data.BMC bioinformatics · 2024Article
- Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity.Nature communications · 2024Article
- Modelling how plant cell-cycle progression leads to cell size regulation.PLoS computational biology · 2023Article
- Identifying a Lung Stem Cell Subpopulation by Combining Single-Cell Morphometrics, Organoid Culture, and Transcriptomics.Stem cells (Dayton, Ohio) · 2023Article
- The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian.Science advances · 2023Article
- Modelling capture efficiency of single-cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics.Bioinformatics (Oxford, England) · 2023Article
- The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian.bioRxiv : the preprint server for biology · 2023Article
- Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC.Nature microbiology · 2023Article
- Robotic data acquisition with deep learning enables cell image-based prediction of transcriptomic phenotypes.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Assessing the growth kinetics and stoichiometry ofEngineering in life sciences · 2023Article
- Fungal biotechnology: From yesterday to tomorrow.Frontiers in fungal biology · 2023Review
- Mitotic checkpoint gene expression is tuned by codon usage bias.The EMBO journal · 2022Article
- Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation.BMC bioinformatics · 2022Article
- Stochastic expression of invasion genes in Plasmodium falciparum schizonts.Nature communications · 2022Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
Abstract
Phenotypic cell-to-cell variability is a fundamental determinant of microbial fitness that contributes to stress adaptation and drug resistance. Gene expression heterogeneity underpins this variability but is challenging to study genome-wide. Here we examine the transcriptomes of >2,000 single fission yeast cells exposed to various environmental conditions by combining imaging, single-cell RNA sequencing and Bayesian true count recovery. We identify sets of highly variable genes during rapid proliferation in constant culture conditions. By integrating single-cell RNA sequencing and cell-size data, we provide insights into genes that are regulated during cell growth and division, including genes whose expression does not scale with cell size. We further analyse the heterogeneity of gene expression during adaptive and acute responses to changing environments. Entry into the stationary phase is preceded by a gradual, synchronized adaptation in gene regulation that is followed by highly variable gene expression when growth decreases. Conversely, sudden and acute heat shock leads to a stronger, coordinated response and adaptation across cells. This analysis reveals that the magnitude of global gene expression heterogeneity is regulated in response to different physiological conditions within populations of a unicellular eukaryote.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.