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Search Results: 1 - 10 of 404888 matches for " Lars M. Steinmetz "
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Genome-wide survey of post-meiotic segregation during yeast recombination
Eugenio Mancera, Richard Bourgon, Wolfgang Huber, Lars M Steinmetz
Genome Biology , 2011, DOI: 10.1186/gb-2011-12-4-r36
Abstract: By genotyping tens of thousands of genetic markers in yeast segregants and their clonal progeny, we analyzed post-meiotic segregation at a genome-wide scale. We show that post-meiotic segregation occurs in close to 10% of recombination events. Although the overall number of markers affected in a single meiosis is small, the rate of post-meiotic segregation is more than five orders of magnitude larger than the base substitution mutation rate. Post-meiotic segregation took place with equal relative frequency in crossovers and non-crossovers, and usually at the edges of gene conversion tracts. Furthermore, post-meiotic segregation tended to occur in markers that are isolated from other heterozygosities and preferentially at polymorphism types that are relatively uncommon in the yeast species.Overall, our survey reveals the genome-wide characteristics of post-meiotic segregation. The results show that post-meiotic segregation is widespread in meiotic recombination and could be a significant determinant of allelic inheritance and allele frequencies at the population level.In sexually reproducing organisms, homologous chromosomes exchange genetic information through meiotic recombination. This process, which occurs in most eukaryotes, is an important determinant of allelic variation [1,2]. Recombination is triggered by the formation of programmed double-strand breaks (DSBs), which are typically repaired using the homologous chromosome as a template. Meiotic DSB repair often produces regions of gene conversion, which may or may not be accompanied by a reciprocal exchange of homologous chromosomal arms, thereby producing crossovers (COs) and non-crossovers (NCOs), respectively [3]. The pairing of a single strand from one homolog with the complementary strand from the other produces heteroduplex DNA with mismatches at heterozygous positions. Repair of these mismatches results in either gene conversion or restoration of the original genotype. If the mismatches are not repaire
Complex Genetic Interactions in a Quantitative Trait Locus
Himanshu Sinha,Bradly P Nicholson,Lars M Steinmetz,John H McCusker
PLOS Genetics , 2006, DOI: 10.1371/journal.pgen.0020013
Abstract: Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3′UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.
Complex genetic interactions in a quantitative trait locus.
Sinha Himanshu,Nicholson Bradly P,Steinmetz Lars M,McCusker John H
PLOS Genetics , 2006,
Abstract: Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3'UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.
Assessing Systems Properties of Yeast Mitochondria through an Interaction Map of the Organelle
Fabiana Perocchi,Lars J Jensen,Julien Gagneur,Uwe Ahting,Christian von Mering,Peer Bork,Holger Prokisch,Lars M Steinmetz
PLOS Genetics , 2006, DOI: 10.1371/journal.pgen.0020170
Abstract: Mitochondria carry out specialized functions; compartmentalized, yet integrated into the metabolic and signaling processes of the cell. Although many mitochondrial proteins have been identified, understanding their functional interrelationships has been a challenge. Here we construct a comprehensive network of the mitochondrial system. We integrated genome-wide datasets to generate an accurate and inclusive mitochondrial parts list. Together with benchmarked measures of protein interactions, a network of mitochondria was constructed in their cellular context, including extra-mitochondrial proteins. This network also integrates data from different organisms to expand the known mitochondrial biology beyond the information in the existing databases. Our network brings together annotated and predicted functions into a single framework. This enabled, for the entire system, a survey of mutant phenotypes, gene regulation, evolution, and disease susceptibility. Furthermore, we experimentally validated the localization of several candidate proteins and derived novel functional contexts for hundreds of uncharacterized proteins. Our network thus advances the understanding of the mitochondrial system in yeast and identifies properties of genes underlying human mitochondrial disorders.
High-resolution transcription atlas of the mitotic cell cycle in budding yeast
Marina V Granovskaia, Lars J Jensen, Matthew E Ritchie, Joern Toedling, Ye Ning, Peer Bork, Wolfgang Huber, Lars M Steinmetz
Genome Biology , 2010, DOI: 10.1186/gb-2010-11-3-r24
Abstract: We discovered 523 antisense transcripts, of which 80 cycle or are located opposite periodically expressed mRNAs, 135 unannotated intergenic non-coding RNAs, of which 11 cycle, and 109 cell-cycle-regulated protein-coding genes that had not previously been shown to cycle. We detected periodic expression coupling of sense and antisense transcript pairs, including antisense transcripts opposite of key cell-cycle regulators, like FAR1 and TAF2.Our dataset presents the most comprehensive resource to date on gene expression during the budding yeast cell cycle. It reveals periodic expression of both protein-coding and non-coding RNA and profiles the expression of non-annotated RNAs throughout the cell cycle for the first time. This data enables hypothesis-driven mechanistic studies concerning the functions of non-coding RNAs.Genome-wide transcriptome analyses in humans [1-5], mouse [6], Drosophila melanogaster [7,8], Arabidopsis thaliana [9], and fission and budding yeast [10-12] have provided evidence for widespread expression of non-coding RNAs (ncRNAs) from intergenic as well as protein-coding regions (for example, antisense or intron-derived transcripts). ncRNAs have been implicated in regulation of chromatin structure, DNA methylation, transcription, translation, as well as RNA silencing and stability [2,13-15].Extensive transcription of intergenic regions and the antisense strands of hundreds of annotated protein-coding genes occurs in budding yeast, despite it lacking vestiges of the protein machinery required for microRNA or small interfering RNA processing [11,16-18]. It is not clear to what extent these RNAs are functional [19], but several have been shown to regulate transcription, acting through either transcriptional interference or epigenetic modifications. Examples of transcriptional interference are SRG1, a ncRNA transcribed in cis across the promoter of SER3 [20,21], and the antisense transcript of IME4 [22], whereas the antisense transcripts of PHO5 [23],
Temporal Expression Profiling Identifies Pathways Mediating Effect of Causal Variant on Phenotype
Saumya Gupta?,Aparna Radhakrishnan?,Pandu Raharja-Liu?,Gen Lin?,Lars M. Steinmetz,Julien Gagneur?,Himanshu Sinha
PLOS Genetics , 2015, DOI: 10.1371/journal.pgen.1005195
Abstract: Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants’ effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage of analyzing allele-specific transcriptional dynamics of mediating genes. Applications in higher eukaryotes can be valuable for inferring causal molecular pathways underlying complex dynamic processes, such as development, physiology and disease progression.
Genotype-Environment Interactions Reveal Causal Pathways That Mediate Genetic Effects on Phenotype
Julien Gagneur equal contributor,Oliver Stegle equal contributor,Chenchen Zhu,Petra Jakob,Manu M. Tekkedil,Raeka S. Aiyar,Ann-Kathrin Schuon,Dana Pe'er,Lars M. Steinmetz
PLOS Genetics , 2013, DOI: 10.1371/journal.pgen.1003803
Abstract: Unraveling the molecular processes that lead from genotype to phenotype is crucial for the understanding and effective treatment of genetic diseases. Knowledge of the causative genetic defect most often does not enable treatment; therefore, causal intermediates between genotype and phenotype constitute valuable candidates for molecular intervention points that can be therapeutically targeted. Mapping genetic determinants of gene expression levels (also known as expression quantitative trait loci or eQTL studies) is frequently used for this purpose, yet distinguishing causation from correlation remains a significant challenge. Here, we address this challenge using extensive, multi-environment gene expression and fitness profiling of hundreds of genetically diverse yeast strains, in order to identify truly causal intermediate genes that condition fitness in a given environment. Using functional genomics assays, we show that the predictive power of eQTL studies for inferring causal intermediate genes is poor unless performed across multiple environments. Surprisingly, although the effects of genotype on fitness depended strongly on environment, causal intermediates could be most reliably predicted from genetic effects on expression present in all environments. Our results indicate a mechanism explaining this apparent paradox, whereby immediate molecular consequences of genetic variation are shared across environments, and environment-dependent phenotypic effects result from downstream integration of environmental signals. We developed a statistical model to predict causal intermediates that leverages this insight, yielding over 400 transcripts, for the majority of which we experimentally validated their role in conditioning fitness. Our findings have implications for the design and analysis of clinical omics studies aimed at discovering personalized targets for molecular intervention, suggesting that inferring causation in a single cellular context can benefit from molecular profiling in multiple contexts.
Genetic Modifiers of Chromatin Acetylation Antagonize the Reprogramming of Epi-Polymorphisms
Anne-Laure Abraham equal contributor,Muniyandi Nagarajan equal contributor,Jean-Baptiste Veyrieras,Hélène Bottin,Lars M. Steinmetz,Ga?l Yvert
PLOS Genetics , 2012, DOI: 10.1371/journal.pgen.1002958
Abstract: Natural populations are known to differ not only in DNA but also in their chromatin-associated epigenetic marks. When such inter-individual epigenomic differences (or “epi-polymorphisms”) are observed, their stability is usually not known: they may or may not be reprogrammed over time or upon environmental changes. In addition, their origin may be purely epigenetic, or they may result from regulatory variation encoded in the DNA. Studying epi-polymorphisms requires, therefore, an assessment of their nature and stability. Here we estimate the stability of yeast epi-polymorphisms of chromatin acetylation, and we provide a genome-by-epigenome map of their genetic control. A transient epi-drug treatment was able to reprogram acetylation variation at more than one thousand nucleosomes, whereas a similar amount of variation persisted, distinguishing “labile” from “persistent” epi-polymorphisms. Hundreds of genetic loci underlied acetylation variation at 2,418 nucleosomes either locally (in cis) or distantly (in trans), and this genetic control overlapped only partially with the genetic control of gene expression. Trans-acting regulators were not necessarily associated with genes coding for chromatin modifying enzymes. Strikingly, “labile” and “persistent” epi-polymorphisms were associated with poor and strong genetic control, respectively, showing that genetic modifiers contribute to persistence. These results estimate the amount of natural epigenomic variation that can be lost after transient environmental exposures, and they reveal the complex genetic architecture of the DNA–encoded determinism of chromatin epi-polymorphisms. Our observations provide a basis for the development of population epigenetics.
The Role of Ctk1 Kinase in Termination of Small Non-Coding RNAs
Tineke L. Lenstra, Agnieszka Tudek, Sandra Clauder, Zhenyu Xu, Spyridon T. Pachis, Dik van Leenen, Patrick Kemmeren, Lars M. Steinmetz, Domenico Libri, Frank C. P. Holstege
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0080495
Abstract: Transcription termination in Saccharomyces cerevisiae can be performed by at least two distinct pathways and is influenced by the phosphorylation status of the carboxy-terminal domain (CTD) of RNA polymerase II (Pol II). Late termination of mRNAs is performed by the CPF/CF complex, the recruitment of which is dependent on CTD-Ser2 phosphorylation (Ser2P). Early termination of shorter cryptic unstable transcripts (CUTs) and small nucleolar/nuclear RNAs (sno/snRNAs) is performed by the Nrd1-Nab3-Sen1 (NNS) complex that binds phosphorylated CTD-Ser5 (Ser5P) via the CTD-interacting domain (CID) of Nrd1p. In this study, mutants of the different termination pathways were compared by genome-wide expression analysis. Surprisingly, the expression changes observed upon loss of the CTD-Ser2 kinase Ctk1p are more similar to those derived from alterations in the Ser5P-dependent NNS pathway, than from loss of CTD-Ser2P binding factors. Tiling array analysis of ctk1Δ cells reveals readthrough at snoRNAs, at many cryptic unstable transcripts (CUTs) and stable uncharacterized transcripts (SUTs), but only at some mRNAs. Despite the suggested predominant role in termination of mRNAs, we observed that a CTK1 deletion or a Pol II CTD mutant lacking all Ser2 positions does not result in a global mRNA termination defect. Rather, termination defects in these strains are widely observed at NNS-dependent genes. These results indicate that Ctk1p and Ser2 CTD phosphorylation have a wide impact in termination of small non-coding RNAs but only affect a subset of mRNA coding genes.
Loss of the Yeast SR Protein Npl3 Alters Gene Expression Due to Transcription Readthrough
Rebecca K. Holmes?,Alex C. Tuck?,Chenchen Zhu?,Hywel R. Dunn-Davies?,Grzegorz Kudla?,Sandra Clauder-Munster?,Sander Granneman?,Lars M. Steinmetz,Christine Guthrie?,David Tollervey
PLOS Genetics , 2015, DOI: 10.1371/journal.pgen.1005735
Abstract: Yeast Npl3 is a highly abundant, nuclear-cytoplasmic shuttling, RNA-binding protein, related to metazoan SR proteins. Reported functions of Npl3 include transcription elongation, splicing and RNA 3’ end processing. We used UV crosslinking and analysis of cDNA (CRAC) to map precise RNA binding sites, and strand-specific tiling arrays to look at the effects of loss of Npl3 on all transcripts across the genome. We found that Npl3 binds diverse RNA species, both coding and non-coding, at sites indicative of roles in both early pre-mRNA processing and 3’ end formation. Tiling arrays and RNAPII mapping data revealed 3’ extended RNAPII-transcribed RNAs in the absence of Npl3, suggesting that defects in pre-mRNA packaging events result in termination readthrough. Transcription readthrough was widespread and frequently resulted in down-regulation of neighboring genes. We conclude that the absence of Npl3 results in widespread 3' extension of transcripts with pervasive effects on gene expression.
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