Transcriptomics data of 11 species of yeast identically grown in rich media and oxidative stress conditions

Objective: The objective of this experiment was to identify transcripts in baker’s yeast (Saccharomyces cerevisiae) that could have originated from previously non-coding genomic regions, or de novo. We generated this data to be able to compare the transcriptomes of different species of Ascomycota. Data description: We generated high-depth RNA sequencing data for 11 species of yeast: Saccharomyces cerevisiae, Saccharomyces paradoxus, Saccharomyces mikatae, Saccharomyces kudriavzevii, Saccharomyces bayanus, Naumovia castelii, Kluyveromyces lactis, Lachancea waltii, Lachancea thermotolerans, Lachancea kluyveri, and Schizosaccharomyces pombe. Using RNA-Seq from yeast grown in rich and oxidative conditions we created genome-guided de novo assemblies of the transcriptomes for each species. We included synthetic spike-in transcripts in each sample to determine the lower limit of detection of the sequencing platform as well as the reliability of our de novo transcriptome assembly pipeline. We subsequently compared the de novo transcripts assemblies to the reference gene annotations and generated assemblies that comprised both annotated and novel transcripts.The work was funded by the following grants: (1) BFU2015-65235-P Ministerio de Economía e Innovación (Spanish Government)-FEDER (EU). (2) BFU2015-68351-P Ministerio de Economía e Innovación (Spanish Government)-FEDER (EU). (3) MDM-2014-0370 “Maria de Maeztu” Programme for Units of Excellence in R&D (Spanish Government). (4) 2017SGR1054 Agència de Gestió d’Ajuts Universitaris i de Recerca Generalitat de Catalunya. (5) 2017SGR01020 Agència de Gestió d’Ajuts Universitaris i de Recerca Generalitat de Catalunya. (6) Predoctoral fellowship (FI, Generalitat de Catalunya) to WRB. Grants 1, 3 and 4 were used to cover lab expenses and to obtain the RNA samples from yeast cultures. Grants 2 and 5 were used for RNA sequencing. Grant 6 covered the salary of WRB. These funding bodies had no role in the design of the study, collection of the data, analysis of the results, or writing of the manuscript

Synchronized replication of genes encoding the same protein complex in fast-proliferating cells

DNA replication perturbs the dosage balance among genes; at mid-S phase, early-replicating genes have doubled their copies while late-replicating ones have not. Dosage imbalance among genes, especially within members of a protein complex, is toxic to cells. However, the molecular mechanisms that cells use to deal with such imbalance remain not fully understood. Here, we validate at the genomic scale that the dosage between early- and late-replicating genes is imbalanced in HeLa cells. We propose the synchronized replication hypothesis that genes sensitive to stoichiometric relationships will be replicated simultaneously to maintain stoichiometry. In support of this hypothesis, we observe that genes encoding the same protein complex have similar replication timing but mainly in fast-proliferating cells such as embryonic stem cells and cancer cells. We find that the synchronized replication observed in cancer cells, but not in slow-proliferating differentiated cells, is due to convergent evolution during tumorigenesis that restores synchronized replication timing within protein complexes. Taken together, our study reveals that the demand for dosage balance during S phase plays an important role in the optimization of the replication-timing program; this selection is relaxed during differentiation as the cell cycle prolongs and is restored during tumorigenesis as the cell cycle shortens

Single cell functional genomics reveals the importance of mitochondria in cell-to-cell phenotypic variation

Mutations frequently have outcomes that differ across individuals, even when these individuals are genetically identical and share a common environment. Moreover, individual microbial and mammalian cells can vary substantially in their proliferation rates, stress tolerance, and drug resistance, with important implications for the treatment of infections and cancer. To investigate the causes of cell-to-cell variation in proliferation, we used a high-throughput automated microscopy assay to quantify the impact of deleting >1500 genes in yeast. Mutations affecting mitochondria were particularly variable in their outcome. In both mutant and wild-type cells mitochondrial membrane potential - but not amount - varied substantially across individual cells and predicted cell-to-cell variation in proliferation, mutation outcome, stress tolerance, and resistance to a clinically used anti-fungal drug. These results suggest an important role for cell-to-cell variation in the state of an organelle in single cell phenotypic variation.Work in the lab of BL was supported by a European Research Council Consolidator grant (616434), the Spanish Ministry of Economy and Competitiveness (BFU2017-89488-P and SEV-2012–0208), the AXA Research Fund, the Bettencourt Schueller Foundation, Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR SGR 1322), the EMBL Partnership, and the Generalitat/CERCA program. Work in the lab of LBC was supported by MINECO (BFU2015-68351-P) and AGAUR (2014 SGR 0974) and the Unidad de Excelencia Maria de Maeztu (MDM-2014–0370)

Promoter architecture determines cotranslational regulation of mRNA

Information that regulates gene expression is encoded throughout each gene but if different regulatory regions can be understood in isolation, or if they interact, is unknown. Here we measure mRNA levels for 10,000 open reading frames (ORFs) transcribed from either an inducible or constitutive promoter. We find that the strength of cotranslational regulation on mRNA levels is determined by promoter architecture. By using a novel computational genetic screen of 6402 RNA-seq experiments, we identify the RNA helicase Dbp2 as the mechanism by which cotranslational regulation is reduced specifically for inducible promoters. Finally, we find that for constitutive genes, but not inducible genes, most of the information encoding regulation of mRNA levels in response to changes in growth rate is encoded in the ORF and not in the promoter. Thus, the ORF sequence is a major regulator of gene expression, and a nonlinear interaction between promoters and ORFs determines mRNA levels.L.B.C. was supported by Ministerio de Economía y Competitividad (MINECO) (BFU2015-68351-P), AGAUR (2014SGR0974), and the Unidad de Excelencia María de Maeztu, funded by the MINECO (MDM-2014-0370)

Coevolution trumps pleiotropy: carbon assimilation traits are independent of metabolic network structure in budding yeast

Phenotypic traits may be gained and lost together because of pleiotropy, the involvement of common genes and networks, or because of simultaneous selection for multiple traits across environments (multiple-trait coevolution). However, the extent to which network pleiotropy versus environmental coevolution shapes shared responses has not been addressed. To test these alternatives, we took advantage of the fact that the genus Saccharomyces has variation in habitat usage and diversity in the carbon sources that a given strain can metabolize. We examined patterns of gain and loss in carbon utilization traits across 488 strains of Saccharomyces to investigate whether the structure of metabolic pathways or selection pressure from common environments may have caused carbon utilization traits to be gained and lost together. While most carbon sources were gained and lost independently of each other, we found four clusters that exhibit non-random patterns of gain and loss across strains. Contrary to the network pleiotropy hypothesis, we did not find that these patterns are explained by the structure of metabolic pathways or shared enzymes. Consistent with the hypothesis that common environments shape suites of phenotypes, we found that the environment a strain was isolated from partially predicts the carbon sources it can assimilate.This work was supported by startup funds from Stony Brook University to JR

Promoter architecture determines cotranslational regulation of mRNA

Information that regulates gene expression is encoded throughout each gene but if different regulatory regions can be understood in isolation, or if they interact, is unknown. Here we measure mRNA levels for 10,000 open reading frames (ORFs) transcribed from either an inducible or constitutive promoter. We find that the strength of cotranslational regulation on mRNA levels is determined by promoter architecture. By using a novel computational genetic screen of 6402 RNA-seq experiments, we identify the RNA helicase Dbp2 as the mechanism by which cotranslational regulation is reduced specifically for inducible promoters. Finally, we find that for constitutive genes, but not inducible genes, most of the information encoding regulation of mRNA levels in response to changes in growth rate is encoded in the ORF and not in the promoter. Thus, the ORF sequence is a major regulator of gene expression, and a nonlinear interaction between promoters and ORFs determines mRNA levels.L.B.C. was supported by Ministerio de Economía y Competitividad (MINECO) (BFU2015-68351-P), AGAUR (2014SGR0974), and the Unidad de Excelencia María de Maeztu, funded by the MINECO (MDM-2014-0370)

A conserved expression signature predicts growth rate and reveals cell & lineage-specific differences

Isogenic cells cultured together show heterogeneity in their proliferation rate. To determine the differences between fast and slow-proliferating cells, we developed a method to sort cells by proliferation rate, and performed RNA-seq on slow and fast proliferating subpopulations of pluripotent mouse embryonic stem cells (mESCs) and mouse fibroblasts. We found that slowly proliferating mESCs have a more naïve pluripotent character. We identified an evolutionarily conserved proliferation-correlated transcriptomic signature that is common to all eukaryotes: fast cells have higher expression of genes for protein synthesis and protein degradation. This signature accurately predicted growth rate in yeast and cancer cells, and identified lineage-specific proliferation dynamics during development, using C. elegans scRNA-seq data. In contrast, sorting by mitochondria membrane potential revealed a highly cell-type specific mitochondria-state related transcriptome. mESCs with hyperpolarized mitochondria are fast proliferating, while the opposite is true for fibroblasts. The mitochondrial electron transport chain inhibitor antimycin affected slow and fast subpopulations differently. While a major transcriptional-signature associated with cell-to-cell heterogeneity in proliferation is conserved, the metabolic and energetic dependency of cell proliferation is cell-type specific.This work has been funded by the Spanish Ministry of Science, Innovation and Universities (BFU2014-55275-P and BFU2017-88407-P to B.P. and BFU2015-68351-P to L.B.C.), the AXA Research Fund and the Agencia de Gestio d’Ajuts Universitaris i de Recerca (AGAUR, 2017 SGR 346 to B.P. and 2014 SGR 0974 & 2017 SGR 1054 to L.B.C.), the National Natural Science Foundation of China (31950410537 to L.B.C.). We would like to thank the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, to the ‘Centro de Excelencia Severo Ochoa’, and the Unidad de Excelencia María de Maeztu, funded by the MINECO (MDM-2014-0370). We also acknowledge the support of the CERCA Programme of the Generalitat de Catalunya. L.B.C. was supported by funding from Peking University and from the Peking-Tsinghua Center for Life Sciences, and from the Research Fund for International Young Scientists (National Natural Science Foundation of China

Large-scale mapping of gene regulatory logic reveals context-dependent repression by transcriptional activators

Transcription factors (TFs) are key mediators that propagate extracellular and intracellular signals through to changes in gene expression profiles. However, the rules by which promoters decode the amount of active TF into target gene expression are not well understood. To determine the mapping between promoter DNA sequence, TF concentration, and gene expression output, we have conducted in budding yeast a large-scale measurement of the activity of thousands of designed promoters at six different levels of TF. We observe that maximum promoter activity is determined by TF concentration and not by the number of binding sites. Surprisingly, the addition of an activator site often reduces expression. A thermodynamic model that incorporates competition between neighboring binding sites for a local pool of TF molecules explains this behavior and accurately predicts both absolute expression and the amount by which addition of a site increases or reduces expression. Taken together, our findings support a model in which neighboring binding sites interact competitively when TF is limiting but otherwise act additively.This work was supported by the Spanish Ministerio de Economía y Competitividad and FEDER through project BFU2015-68351-P to L.B.C. and by grant 2014SGR0974 from the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) to L.B.C. This work was supported by grants from the European Research Council (ERC) and the US National Institutes of Health (NIH) to E.S. D.vD. was supported by Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) Rubicon fellowship 825.14.016

Promoter activity buffering reduces the fitness cost of misregulation

Organisms regulate gene expression through changes in the activity of transcription factors (TFs). In yeast, the response of genes to changes in TF activity is generally assumed to be encoded in the promoter. To directly test this assumption, we chose 42 genes and, for each, replaced the promoter with a synthetic inducible promoter and measured how protein expression changes as a function of TF activity. Most genes exhibited gene-specific TF dose-response curves not due to differences in mRNA stability, translation, or protein stability. Instead, most genes have an intrinsic ability to buffer the effects of promoter activity. This can be encoded in the open reading frame and the 3' end of genes and can be implemented by both autoregulatory feedback and by titration of limiting trans regulators. We show experimentally and computationally that, when misexpression of a gene is deleterious, this buffering insulates cells from fitness defects due to misregulationL.B.C. was supported by Ministerio de Economía y Competitividad (MINECO) and the Fondo Europeo de Desarrollo Regional (FEDER) (BFU2015-68351-P), AGAUR (2014SGR0974 and 2017SGR1054), and the Unidad de Excelencia María de Maeztu, funded by MINECO (MDM-2014-0370). We would like to thank the UPF/CRG Flow Cytometry core

Extensive post-transcriptional buffering of gene expression in the response to severe oxidative stress in baker's yeast

Cells responds to diverse stimuli by changing the levels of specific effector proteins. These changes are usually examined using high throughput RNA sequencing data (RNA-Seq); transcriptional regulation is generally assumed to directly influence protein abundances. However, the correlation between RNA-Seq and proteomics data is in general quite limited owing to differences in protein stability and translational regulation. Here we perform RNA-Seq, ribosome profiling and proteomics analyses in baker's yeast cells grown in rich media and oxidative stress conditions to examine gene expression regulation at various levels. With the exception of a small set of genes involved in the maintenance of the redox state, which are regulated at the transcriptional level, modulation of protein expression is largely driven by changes in the relative ribosome density across conditions. The majority of shifts in mRNA abundance are compensated by changes in the opposite direction in the number of translating ribosomes and are predicted to result in no net change at the protein level. We also identify a subset of mRNAs which is likely to undergo specific translational repression during stress and which includes cell cycle control genes. The study suggests that post-transcriptional buffering of gene expression may be more common than previously anticipated.The work was funded by grants BFU2015–65235-P, BFU2015-68351-P and BFU2016-80039-R, from Ministerio de Economía e Innovación (Spanish Government) - FEDER (EU), and from grant PT17/0009/0014 from Instituto de Salud Carlos III – FEDER. We also received funding from the “Maria de Maeztu” Programme for Units of Excellence in R&D (MDM-2014-0370) and from Agència de Gestió d’Ajuts Universitaris i de Recerca Generalitat de Catalunya (AGAUR), grant number 2014SGR1121, 2014SGR0974, 2017SGR01020 and, predoctoral fellowship (FI) to W.B. We also acknowledge support from the EU Erasmus Programme to T.T