Biology subjects

Marguerat, S.

Publications and source records attributed to Marguerat, S..

4 recordsLinked to original sources

bioRxiv2018

Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription

Condensins are genome organisers that shape chromosomes and promote their accurate transmission. Several studies have also implicated condensins in gene expression, although the mechanisms have remained enigmatic. Here, we report on the role of condensin in gene expression in fission and budding yeasts. In contrast to previous studies, we provide compelling evidence that condensin plays no direct role in the maintenance of the transcriptome, neither during interphase nor during mitosis. We further show that the changes in gene expression in post-mitotic fission yeast cells that result from condensin inactivation are largely a consequence of chromosome missegregation during anaphase, which notably depletes the RNA-exosome from daughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normal transcriptome despite condensin inactivation. Thus, chromosome instability, rather than a direct role of condensin in the transcription process, changes gene expression. This knowledge challenges the concept of gene regulation by canonical condensin complexes.

molecular biology↗

bioRxiv2018

Single-cell phenotyping and RNA sequencing reveal novel patterns of gene expression heterogeneity and regulation during growth and stress adaptation in a unicellular eukaryote

Cell-to-cell variability is central for microbial populations and contributes to cell function, stress adaptation and drug resistance. Gene-expression heterogeneity underpins this variability, but has been challenging to study genome-wide. Here, we report an integrated approach for imaging of individual fission yeast cells followed by single-cell RNA sequencing (scRNA-seq) and novel Bayesian normalisation. We analyse >2000 single cells and >700 matching RNA controls in various environmental conditions and identify sets of highly variable genes. Combining scRNA-seq with cell-size measurements provides unique insights into genes regulated during cell growth and division in single cells, including genes whose expression does not scale with cell size. We further analyse the heterogeneity and dynamics of gene expression during adaptive and acute responses to changing environments. Entry into stationary phase is preceded by a gradual, synchronised adaptation in gene regulation, followed by highly variable gene expression when growth decreases. Conversely, a sudden and acute heat-shock leads to a stronger and coordinated response and adaptation across cells. This analysis reveals that the extent and dynamics of global gene-expression heterogeneity is regulated in response to different physiological conditions within populations of a unicellular eukaryote. In summary, this works illustrates the potential of combined transcriptomics and imaging analysis in single cells to provide comprehensive and unbiased mechanistic understanding of cell-to-cell variability in microbial communities.

genomics↗

bioRxiv2017

Impact of division rate and cell size on gene expression noise

The cell division rate, size, and gene expression programmes change in response to external conditions. These global changes impact on average concentrations of biomolecule and their variability or noise. Gene expression is inherently stochastic, and noise levels of individual proteins depend on synthesis and degradation rates as well as on cell-cycle dynamics. We have modelled stochastic gene expression inside growing and dividing cells to study the effect of division rates on noise in mRNA and protein expression. We use assumptions and parameters relevant to Escherichia coli, for which abundant quantitative data are available. We find that coupling of transcription, but not translation rates to the rate of cell division can result in protein concentration and noise homeostasis across conditions. Interestingly, we find that the increased cell size at fast division rates, observed in E. coli d other unicellular organisms, buffers noise levels even for proteins with decreased expression at faster growth. We then investigate the functional importance of these regulations using gene regulatory networks that exhibit bi-stability and oscillations. We find that network topology affects robustness to changes in division rate in complex and unexpected ways. In particular, a simple model of persistence, based on global physiological feedback, predicts increased proportion of persistors cells at slow division rates. Altogether, our study reveals how cell size regulation in response to cell division rate could help controlling gene expression noise. It also highlights that understanding of circuits robustness across growth conditions is key for the effective design of synthetic biological systems.

systems biology↗

bioRxiv2017

Long non-coding RNA repertoire and regulation by nuclear exosome, cytoplasmic exonuclease and RNAi in fission yeast

Transcriptomes feature pervasive, but poorly defined long non-coding RNAs (lncRNAs). We identify 5775 novel lncRNAs in Schizosaccharomyces pombe, nearly 4-times the previously annotated lncRNAs. Most lncRNAs become derepressed under genetic and physiological perturbations, especially during late meiosis. These lncRNAs are targeted by three RNA-processing pathways: the nuclear exosome, cytoplasmic exonuclease and RNAi, with substantial coordination and redundancy among pathways. We classify lncRNAs into cryptic unstable transcripts (CUTs), Xrn1-sensitive unstable transcripts (XUTs), and Dicer-sensitive unstable transcripts (DUTs). XUTs and DUTs are enriched for antisense lncRNAs, while CUTs are often bidirectional and actively translated. The cytoplasmic exonuclease and RNAi repress thousands of meiotically induced RNAs. Antisense lncRNA and sense mRNA expression often negatively correlate in the physiological, but not the genetic conditions. Intergenic and bidirectional lncRNAs emerge from nucleosome-depleted regions, upstream of positioned nucleosomes. This broad survey of the S. pombe lncRNA repertoire and characteristics provides a rich resource for functional analyses.

genomics↗