Imperial College London

DrSamuelMarguerat

Faculty of MedicineInstitute of Clinical Sciences

Honorary Senior Lecturer
 
 
 
//

Contact

 

+44 (0)20 3313 8331samuel.marguerat Website

 
 
//

Location

 

5003CRB (Clinical Research Building)Hammersmith Campus

//

Summary

 

Publications

Publication Type
Year
to

65 results found

Ellis DA, Reyes-Martín F, Rodríguez-López M, Cotobal C, Sun X-M, Saintain Q, Jeffares DC, Marguerat S, Tallada VA, Bähler Jet al., 2021, R-loops and regulatory changes in chronologically ageing fission yeast cells drive non-random patterns of genome rearrangements., PLoS Genet, Vol: 17

Aberrant repair of DNA double-strand breaks can recombine distant chromosomal breakpoints. Chromosomal rearrangements compromise genome function and are a hallmark of ageing. Rearrangements are challenging to detect in non-dividing cell populations, because they reflect individually rare, heterogeneous events. The genomic distribution of de novo rearrangements in non-dividing cells, and their dynamics during ageing, remain therefore poorly characterized. Studies of genomic instability during ageing have focussed on mitochondrial DNA, small genetic variants, or proliferating cells. To characterize genome rearrangements during cellular ageing in non-dividing cells, we interrogated a single diagnostic measure, DNA breakpoint junctions, using Schizosaccharomyces pombe as a model system. Aberrant DNA junctions that accumulated with age were associated with microhomology sequences and R-loops. Global hotspots for age-associated breakpoint formation were evident near telomeric genes and linked to remote breakpoints elsewhere in the genome, including the mitochondrial chromosome. Formation of breakpoint junctions at global hotspots was inhibited by the Sir2 histone deacetylase and might be triggered by an age-dependent de-repression of chromatin silencing. An unexpected mechanism of genomic instability may cause more local hotspots: age-associated reduction in an RNA-binding protein triggering R-loops at target loci. This result suggests that biological processes other than transcription or replication can drive genome rearrangements. Notably, we detected similar signatures of genome rearrangements that accumulated in old brain cells of humans. These findings provide insights into the unique patterns and possible mechanisms of genome rearrangements in non-dividing cells, which can be promoted by ageing-related changes in gene-regulatory proteins.

Journal article

Brooks LJ, Clements MP, Burden JJ, Kocher D, Richards L, Devesa SC, Zakka L, Woodberry M, Ellis M, Jaunmuktane Z, Brandner S, Morrison G, Pollard SM, Dirks PB, Marguerat S, Parrinello Set al., 2021, The white matter is a pro-differentiative niche for glioblastoma, NATURE COMMUNICATIONS, Vol: 12, ISSN: 2041-1723

Journal article

Bertaux F, von Kugelgen J, Marguerat S, Shahrezaei Vet al., 2020, A bacterial size law revealed by a coarse-grained model of cell physiology, PLOS COMPUTATIONAL BIOLOGY, Vol: 16, ISSN: 1553-734X

Journal article

Sun X-M, Bowman A, Priestman M, Bertaux F, Martinez-Segura A, Tang W, Whilding C, Dormann D, Shahrezaei V, Marguerat Set al., 2020, Size-Dependent Increase in RNA Polymerase II Initiation Rates Mediates Gene Expression Scaling with Cell Size., Curr Biol, Vol: 30, Pages: 1217-1230.e7

Cell size varies during the cell cycle and in response to external stimuli. This requires the tight coordination, or "scaling," of mRNA and protein quantities with the cell volume in order to maintain biomolecule concentrations and cell density. Evidence in cell populations and single cells indicates that scaling relies on the coordination of mRNA transcription rates with cell size. Here, we use a combination of single-molecule fluorescence in situ hybridization (smFISH), time-lapse microscopy, and mathematical modeling in single fission yeast cells to uncover the precise molecular mechanisms that control transcription rates scaling with cell size. Linear scaling of mRNA quantities is apparent in single fission yeast cells during a normal cell cycle. Transcription of both constitutive and periodic genes is a Poisson process with transcription rates scaling with cell size and without evidence for transcriptional off states. Modeling and experimental data indicate that scaling relies on the coordination of RNA polymerase II (RNAPII) transcription initiation rates with cell size and that RNAPII is a limiting factor. We show using real-time quantitative imaging that size increase is accompanied by a rapid concentration-independent recruitment of RNAPII onto chromatin. Finally, we find that, in multinucleated cells, scaling is set at the level of single nuclei and not the entire cell, making the nucleus a determinant of scaling. Integrating our observations in a mechanistic model of RNAPII-mediated transcription, we propose that scaling of gene expression with cell size is the consequence of competition between genes for limiting RNAPII.

Journal article

Sun X-M, Bowman A, Priestman M, Bertaux F, Martinez-Segura A, Tang W, Whilding C, Dormann D, Shahrezaei V, Marguerat Set al., 2020, Size-dependent increase in RNA Polymerase II initiation rates mediates gene expression scaling with cell size, Current Biology, Vol: 30, Pages: 1217-1230.e7, ISSN: 0960-9822

Cell size varies during the cell cycle and in response to external stimuli. This requires the tight coordination, or “scaling”, of mRNA and protein quantities with the cell volume in order to maintain biomolecules concentrations and cell density. Evidence in cell populations and single cells indicates that scaling relies on the coordination of mRNA transcription rates with cell size. Here we use a combination of single-molecule fluorescence in situ hybridisation (smFISH), time-lapse microscopy and mathematical modelling in single fission yeast cells to uncover the precise molecular mechanisms that control transcription rates scaling with cell size. Linear scaling of mRNA quantities is apparent in single fission yeast cells during a normal cell cycle. Transcription rates of both constitutive and regulated genes scale with cell size without evidence for transcriptional bursting. Modelling and experimental data indicate that scaling relies on the coordination of RNAPII transcription initiation rates with cell size and that RNAPII is a limiting factor. We show using real-time quantitative imaging that size increase is accompanied by a rapid concentration independent recruitment of RNAPII onto chromatin. Finally, we find that in multinucleated cells, scaling is set at the level of single nuclei and not the entire cell, making the nucleus the transcriptional scaling unit. Integrating our observations in a mechanistic model of RNAPII mediated transcription, we propose that scaling of gene expression with cell size is the consequence of competition between genes for limiting RNAPII.

Journal article

Tang W, Bertaux F, Thomas P, Stefanelli C, Saint M, Marguerat S, Shahrezaei Vet al., 2020, bayNorm: Bayesian gene expression recovery, imputation and normalisation for single cell RNA-sequencing data, Bioinformatics, Vol: 36, Pages: 1174-1181, ISSN: 1367-4803

Motivation:Normalisation of single cell RNA sequencing (scRNA-seq) data is a prerequisite to theirinterpretation. The marked technical variability, high amounts of missing observations and batch effecttypical of scRNA-seq datasets make this task particularly challenging. There is a need for an efficient andunified approach for normalisation, imputation and batch effect correction.Results:Here, we introduce bayNorm, a novel Bayesian approach for scaling and inference of scRNA-seq counts. The method’s likelihood function follows a binomial model of mRNA capture, while priorsare estimated from expression values across cells using an empirical Bayes approach. We first validateour assumptions by showing this model can reproduce different statistics observed in real scRNA-seqdata. We demonstrate using publicly-available scRNA-seq datasets and simulated expression data thatbayNorm allows robust imputation of missing values generating realistic transcript distributions that matchsingle molecule FISH measurements. Moreover, by using priors informed by dataset structures, bayNormimproves accuracy and sensitivity of differential expression analysis and reduces batch effect comparedto other existing methods. Altogether, bayNorm provides an efficient, integrated solution for global scalingnormalisation, imputation and true count recovery of gene expression measurements from scRNA-seqdata.Availability:The R package “bayNorm” is available at https://github.com/WT215/bayNorm. The code foranalysing data in this paper is available at https://github.com/WT215/bayNorm_papercode.Contact:samuel.marguerat@imperial.ac.uk or v.shahrezaei@imperial.ac.ukSupplementary information:Supplementary data are available atBioinformaticsonline.

Journal article

Ragdale HS, Clements M, Zakka L, Conde L, Marguerat S, Parrinello Set al., 2019, Injury signals drive lineage conversion of premalignant astrocytes: insights into tumour initiation, 14th European Meeting on Glial Cells in Health and Disease (GLIA), Publisher: WILEY, Pages: E147-E147, ISSN: 0894-1491

Conference paper

Saint M, Bertaux F, Tang W, Sun X-M, Game L, Köferle A, Bähler J, Shahrezaei V, Marguerat Set al., 2019, Single-cell imaging and RNA sequencing reveal patterns of gene expression heterogeneity during fission yeast growth and adaptation, Nature Microbiology, Vol: 4, Pages: 480-491, ISSN: 2058-5276

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.

Journal article

Hocquet C, Robellet X, Modolo L, Sun X-M, Burny C, Cuylen-Haering S, Toselli E, Clauder-Muenster S, Steinmetz L, Haering CH, Marguerat S, Bernard Pet al., 2018, Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription, eLife, Vol: 7, ISSN: 2050-084X

Condensins are genome organisers that shape chromosomes and promote theiraccurate transmission. Several studies have also implicated condensins in gene expression,although any mechanisms have remained enigmatic. Here, we report on the role of condensin ingene expression in fission and budding yeasts. In contrast to previous studies, we providecompelling 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 expressionin post-mitotic fission yeast cells that result from condensin inactivation are largely a consequenceof chromosome missegregation during anaphase, which notably depletes the RNA-exosome fromdaughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normaltranscriptome despite condensin inactivation. Thus, chromosome instability, rather than a directrole of condensin in the transcription process, changes gene expression. This knowledge challengesthe concept of gene regulation by canonical condensin complexes.

Journal article

Atkinson S, Marguerat S, Bitton D, Bachand F, Rodriguez-Lopez M, Rallis C, Lemay J-F, Cotobal C, Malecki M, Smialowski P, Mata J, Korber P, Bahler Jet al., 2018, Long non-coding RNA repertoire and targeting by nuclear exosome, cytoplasmic exonuclease and RNAi in fission yeast, RNA, Vol: 24, Pages: 1195-1213, ISSN: 1355-8382

Long non-coding RNAs (lncRNAs), which are longer than 200 nucleotides but often unstable, contribute a substantial and diverse portion to pervasive non-coding transcriptomes. Most lncRNAs are poorly annotated and understood, although several play important roles in gene regulation and diseases. Here we systematically uncover and analyse lncRNAs in Schizosaccharomyces pombe. Based on RNA-seq data from twelve RNA-processing mutants and nine physiological conditions, we identify 5775 novel lncRNAs, nearly 4-times the previously annotated lncRNAs. The expression of most lncRNAs becomes strongly induced under the genetic and physiological perturbations, most notably during late meiosis. Most lncRNAs are cryptic and suppressed by three RNA-processing pathways: the nuclear exosome, cytoplasmic exonuclease, and RNAi. Double-mutant analyses reveal substantial coordination and redundancy among these pathways. We classify lncRNAs by their dominant pathway 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, along with RNAi, dampens the expression of thousands of lncRNAs and mRNAs that become induced during meiosis. Antisense lncRNA expression mostly negatively correlates with sense mRNA expression in the physiological, but not the genetic conditions. Intergenic and bidirectional lncRNAs emerge from nucleosome-depleted regions, upstream of positioned nucleosomes. Our results highlight both similarities and differences to lncRNA regulation in budding yeast. This broad survey of the lncRNA repertoire and characteristics in S. pombe, and the interwoven regulatory pathways that target lncRNAs, provides a rich framework for their further functional analyses.

Journal article

Bertaux F, Marguerat S, Shahrezaei V, 2018, Division rate, cell size and proteome allocation: impact on gene expression noise and implications for the dynamics of genetic circuits, ROYAL SOCIETY OPEN SCIENCE, Vol: 5, ISSN: 2054-5703

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 and 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 persister 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 circuits' robustness across growth conditions is key for the effective design of synthetic biological systems.

Journal article

Björklund M, Marguerat S, 2017, Editorial: Determinants of Cell Size., Frontiers in Cell and Developmental Biology, Vol: 5, ISSN: 2296-634X

Journal article

Clements MP, Byrne E, Camarillo Guerrero LF, Cattin A-L, Zakka L, Ashraf A, Burden JJ, Khadayate S, Lloyd AC, Marguerat S, Parrinello Set al., 2017, The wound microenvironment reprogrammes Schwann cells to invasive mesenchymal- like cells to drive peripheral nerve regeneration, Neuron, Vol: 96, Pages: 98-114.e7, ISSN: 0896-6273

Schwann cell dedifferentiation from a myelinating to a progenitor-like cell underlies the remarkable ability of peripheral nerves to regenerate following injury. However, the molecular identity of the differentiated and dedifferentiated states in vivo has been elusive. Here, we profiled Schwann cells acutely purified from intact nerves and from the wound and distal regions of severed nerves. Our analysis reveals novel facets of the dedifferentiation response, including acquisition of mesenchymal traits and a Myc module. Furthermore, wound and distal dedifferentiated Schwann cells constitute different populations, with wound cells displaying increased mesenchymal character induced by localized TGFβ signaling. TGFβ promotes invasion and crosstalks with Eph signaling via N-cadherin to drive collective migration of the Schwann cells across the wound. Consistently, Tgfbr2 deletion in Schwann cells resulted in misdirected and delayed reinnervation. Thus, the wound microenvironment is a key determinant of Schwann cell identity, and it promotes nerve repair through integration of multiple concerted signals.

Journal article

Keifenheim D, Sun X-M, D'Souza E, Ohira MJ, Magner M, Mayhew MB, Marguerat S, Rhind Net al., 2017, Size-Dependent Expression of the Mitotic Activator Cdc25 Suggests a Mechanism of Size Control in Fission Yeast, Current Biology, Vol: 27, Pages: 1491-1497.e4, ISSN: 1879-0445

Proper cell size is essential for cellular function. Nonetheless, despite more than 100 years of work on the subject, the mechanisms that maintain cell-size homeostasis are largely mysterious [ 1 ]. Cells in growing populations maintain cell size within a narrow range by coordinating growth and division. Bacterial and eukaryotic cells both demonstrate homeostatic size control, which maintains population-level variation in cell size within a certain range and returns the population average to that range if it is perturbed [ 1, 2 ]. Recent work has proposed two different strategies for size control: budding yeast has been proposed to use an inhibitor-dilution strategy to regulate size at the G1/S transition [ 3 ], whereas bacteria appear to use an adder strategy, in which a fixed amount of growth each generation causes cell size to converge on a stable average [ 4–6 ]. Here we present evidence that cell size in the fission yeast Schizosaccharomyces pombe is regulated by a third strategy: the size-dependent expression of the mitotic activator Cdc25. cdc25 transcript levels are regulated such that smaller cells express less Cdc25 and larger cells express more Cdc25, creating an increasing concentration of Cdc25 as cells grow and providing a mechanism for cells to trigger cell division when they reach a threshold concentration of Cdc25. Because regulation of mitotic entry by Cdc25 is well conserved, this mechanism may provide a widespread solution to the problem of size control in eukaryotes.

Journal article

Lemay JF, Marguerat S, Larochelle M, Liu X, van Nues R, Hunyadkürti J, Hoque M, Tian B, Granneman S, Bähler J, Bachand Fet al., 2016, The Nrd1-like protein Seb1 coordinates cotranscriptional 3′ end processing and polyadenylation site selection, Genes & Development, Vol: 30, Pages: 1558-1572, ISSN: 1549-5477

Termination of RNA polymerase II (RNAPII) transcription is associated with RNA 3′ end formation. For coding genes, termination is initiated by the cleavage/polyadenylation machinery. In contrast, a majority of noncoding transcription events in Saccharomyces cerevisiae does not rely on RNA cleavage for termination but instead terminates via a pathway that requires the Nrd1–Nab3–Sen1 (NNS) complex. Here we show that the Schizosaccharomyces pombe ortholog of Nrd1, Seb1, does not function in NNS-like termination but promotes polyadenylation site selection of coding and noncoding genes. We found that Seb1 associates with 3′ end processing factors, is enriched at the 3′ end of genes, and binds RNA motifs downstream from cleavage sites. Importantly, a deficiency in Seb1 resulted in widespread changes in 3′ untranslated region (UTR) length as a consequence of increased alternative polyadenylation. Given that Seb1 levels affected the recruitment of conserved 3′ end processing factors, our findings indicate that the conserved RNA-binding protein Seb1 cotranscriptionally controls alternative polyadenylation.

Journal article

Ahrne E, Martinez-Segura A, Syed AP, Vina-Vilaseca A, Gruber AJ, Marguerat S, Schmidt Aet al., 2015, Exploiting the multiplexing capabilities of tandem mass tags for high-throughput estimation of cellular protein abundances by mass spectrometry, METHODS, Vol: 85, Pages: 100-107, ISSN: 1046-2023

Journal article

Shahrezaei V, Marguerat S, 2015, Connecting growth with gene expression: of noise and numbers., Current Opinion in Microbiology, Vol: 25, Pages: 127-135, ISSN: 1879-0364

Growth is a dynamic process whereby cells accumulate mass. Growth rates of single cells are connected to RNA and protein synthesis rates, and therefore with biomolecule numbers. Noise in gene expression depends on these numbers, and is thus linked with cellular growth. Whether these global attributes of the cell participate in gene regulation is still largely unexplored. New experimental and modelling studies suggest that systemic variations in biomolecule numbers can coordinate cellular processes, including growth itself, through global regulatory feedback that acts in addition to genetic regulatory networks. Here, we review these findings and speculate on possible implications of this less appreciated layer of gene regulation for cellular physiology and adaptation to changing environments.

Journal article

Bitton DA, Atkinson SR, Rallis C, Smith GC, Ellis DA, Chen YY, Malecki M, Codlin S, Lemay JF, Cotobal C, Bachand F, Marguerat S, Mata J, Bähler Jet al., 2015, Widespread exon skipping triggers degradation by nuclear RNA surveillance in fission yeast., Genome Research, Vol: 25, Pages: 884-896, ISSN: 1549-5469

Exon skipping is considered a principal mechanism by which eukaryotic cells expand their transcriptome and proteome repertoires, creating different splice variants with distinct cellular functions. Here we analyze RNA-seq data from 116 transcriptomes in fission yeast (Schizosaccharomyces pombe), covering multiple physiological conditions as well as transcriptional and RNA processing mutants. We applied brute-force algorithms to detect all possible exon-skipping events, which were widespread but rare compared to normal splicing events. Exon-skipping events increased in cells deficient for the nuclear exosome or the 5'-3' exonuclease Dhp1, and also at late stages of meiotic differentiation when nuclear-exosome transcripts decreased. The pervasive exon-skipping transcripts were stochastic, did not increase in specific physiological conditions, and were mostly present at less than one copy per cell, even in the absence of nuclear RNA surveillance and during late meiosis. These exon-skipping transcripts are therefore unlikely to be functional and may reflect splicing errors that are actively removed by nuclear RNA surveillance. The average splicing rate by exon skipping was ∼0.24% in wild type and ∼1.75% in nuclear exonuclease mutants. We also detected approximately 250 circular RNAs derived from single or multiple exons. These circular RNAs were rare and stochastic, although a few became stabilized during quiescence and in splicing mutants. Using an exhaustive search algorithm, we also uncovered thousands of previously unknown splice sites, indicating pervasive splicing; yet most of these splicing variants were cryptic and increased in nuclear degradation mutants. This study highlights widespread but low frequency alternative or aberrant splicing events that are targeted by nuclear RNA surveillance.

Journal article

Lovell D, Pawlowsky-Glahn V, Egozcue JJ, Marguerat S, Baehler Jet al., 2015, Proportionality: A Valid Alternative to Correlation for Relative Data, Plos Computational Biology, Vol: 11, ISSN: 1553-7358

Journal article

Clément-Ziza M, Marsellach FX, Codlin S, Papadakis MA, Reinhardt S, Rodríguez-López M, Martin S, Marguerat S, Schmidt A, Lee E, Workman CT, Bähler J, Beyer Aet al., 2014, Natural genetic variation impacts expression levels of coding, non-coding, and antisense transcripts in fission yeast., Molecular Systems Biology, Vol: 10, Pages: 764-764, ISSN: 1744-4292

Our current understanding of how natural genetic variation affects gene expression beyond well-annotated coding genes is still limited. The use of deep sequencing technologies for the study of expression quantitative trait loci (eQTLs) has the potential to close this gap. Here, we generated the first recombinant strain library for fission yeast and conducted an RNA-seq-based QTL study of the coding, non-coding, and antisense transcriptomes. We show that the frequency of distal effects (trans-eQTLs) greatly exceeds the number of local effects (cis-eQTLs) and that non-coding RNAs are as likely to be affected by eQTLs as protein-coding RNAs. We identified a genetic variation of swc5 that modifies the levels of 871 RNAs, with effects on both sense and antisense transcription, and show that this effect most likely goes through a compromised deposition of the histone variant H2A.Z. The strains, methods, and datasets generated here provide a rich resource for future studies.

Journal article

Lemay J-F, Larochelle M, Marguerat S, Atkinson S, Baehler J, Bachand Fet al., 2014, The RNA exosome promotes transcription termination of backtracked RNA polymerase II, NATURE STRUCTURAL & MOLECULAR BIOLOGY, Vol: 21, Pages: 919-926, ISSN: 1545-9993

Journal article

Bitton DA, Rallis C, Jeffares DC, Smith GC, Chen YYC, Codlin S, Marguerat S, Baehler Jet al., 2014, LaSSO, a strategy for genome-wide mapping of intronic lariats and branch points using RNA-seq, GENOME RESEARCH, Vol: 24, Pages: 1169-1179, ISSN: 1088-9051

Journal article

Marguerat S, Lawler K, Brazma A, Baehler Jet al., 2014, Contributions of transcription and mRNA decay to gene expression dynamics of fission yeast in response to oxidative stress, RNA Biology, Vol: 11, Pages: 702-714, ISSN: 1547-6286

The cooperation of transcriptional and post-transcriptional levels of control to shape gene regulation is only partially understood. Here we show that a combination of two simple and non-invasive genomic techniques, coupled with kinetic mathematical modeling, affords insight into the intricate dynamics of RNA regulation in response to oxidative stress in the fission yeast Schizosaccharomyces pombe. This study reveals a dominant role of transcriptional regulation in response to stress, but also points to the first minutes after stress induction as a critical time when the coordinated control of mRNA turnover can support the control of transcription for rapid gene regulation. In addition, we uncover specialized gene expression strategies associated with distinct functional gene groups, such as simultaneous transcriptional repression and mRNA destabilization for genes encoding ribosomal proteins, delayed mRNA destabilization with varying contribution of transcription for ribosome biogenesis genes, dominant roles of mRNA stabilization for genes functioning in protein degradation, and adjustment of both transcription and mRNA turnover during the adaptation to stress. We also show that genes regulated independently of the bZIP transcription factor Atf1p are predominantly controlled by mRNA turnover, and identify putative cis-regulatory sequences that are associated with different gene expression strategies during the stress response. This study highlights the intricate and multi-faceted interplay between transcription and RNA turnover during the dynamic regulatory response to stress.

Journal article

Blaikley EJ, Tinline-Purvis H, Kasparek TR, Marguerat S, Sarkar S, Hulme L, Hussey S, Wee BY, Deegan RS, Walker CA, Pai CC, Bähler J, Nakagawa T, Humphrey TCet al., 2014, The DNA damage checkpoint pathway promotes extensive resection and nucleotide synthesis to facilitate homologous recombination repair and genome stability in fission yeast., Nucleic Acids Research, Vol: 42, Pages: 5644-5656, ISSN: 1362-4962

DNA double-strand breaks (DSBs) can cause chromosomal rearrangements and extensive loss of heterozygosity (LOH), hallmarks of cancer cells. Yet, how such events are normally suppressed is unclear. Here we identify roles for the DNA damage checkpoint pathway in facilitating homologous recombination (HR) repair and suppressing extensive LOH and chromosomal rearrangements in response to a DSB. Accordingly, deletion of Rad3(ATR), Rad26ATRIP, Crb2(53BP1) or Cdc25 overexpression leads to reduced HR and increased break-induced chromosome loss and rearrangements. We find the DNA damage checkpoint pathway facilitates HR, in part, by promoting break-induced Cdt2-dependent nucleotide synthesis. We also identify additional roles for Rad17, the 9-1-1 complex and Chk1 activation in facilitating break-induced extensive resection and chromosome loss, thereby suppressing extensive LOH. Loss of Rad17 or the 9-1-1 complex results in a striking increase in break-induced isochromosome formation and very low levels of chromosome loss, suggesting the 9-1-1 complex acts as a nuclease processivity factor to facilitate extensive resection. Further, our data suggest redundant roles for Rad3ATR and Exo1 in facilitating extensive resection. We propose that the DNA damage checkpoint pathway coordinates resection and nucleotide synthesis, thereby promoting efficient HR repair and genome stability.

Journal article

Schlackow M, Marguerat S, Proudfoot NJ, Baehler J, Erban R, Gullerova Met al., 2013, Genome-wide analysis of poly(A) site selection in Schizosaccharomyces pombe, RNA, Vol: 19, Pages: 1617-1631, ISSN: 1355-8382

Journal article

DeGennaro CM, Alver BH, Marguerat S, Stepanova E, Davis CP, Baehler J, Park PJ, Winston Fet al., 2013, Spt6 Regulates Intragenic and Antisense Transcription, Nucleosome Positioning, and Histone Modifications Genome-Wide in Fission Yeast, MOLECULAR AND CELLULAR BIOLOGY, Vol: 33, Pages: 4779-4792, ISSN: 0270-7306

Journal article

Marguerat S, Baehler J, 2012, Coordinating cell size, TRENDS IN GENETICS, Vol: 28, Pages: 560-565, ISSN: 0168-9525

Journal article

Marguerat S, Schmidt A, Codlin S, Chen W, Aebersold R, Baehler Jet al., 2012, Quantitative Analysis of Fission Yeast Transcriptomes and Proteomes in Proliferating and Quiescent Cells, CELL, Vol: 151, Pages: 671-683, ISSN: 0092-8674

Journal article

Atkinson SR, Marguerat S, Baehler J, 2012, Exploring long non-coding RNAs through sequencing, SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY, Vol: 23, Pages: 200-205, ISSN: 1084-9521

Journal article

Lemieux C, Marguerat S, Lafontaine J, Barbezier N, Bahler J, Bachand Fet al., 2011, A Pre-mRNA Degradation Pathway that Selectively Targets Intron-Containing Genes Requires the Nuclear Poly(A)-Binding Protein, MOLECULAR CELL, Vol: 44, Pages: 108-119, ISSN: 1097-2765

Journal article

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00794920&limit=30&person=true