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• W2913620844 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." @default.
• W2913620844 created "2019-02-21" @default.
• W2913620844 creator A5005733086 @default.
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• W2913620844 date "2019-02-04" @default.
• W2913620844 modified "2023-10-13" @default.
• W2913620844 title "Single-cell imaging and RNA sequencing reveal patterns of gene expression heterogeneity during fission yeast growth and adaptation" @default.
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• W2913620844 doi "https://doi.org/10.1038/s41564-018-0330-4" @default.
• W2913620844 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30718845" @default.
• W2913620844 hasPublicationYear "2019" @default.
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