Control of expression noise, fitness and gene aggregation by a component of the yeast pheromone response pathway
Ontology highlight
ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
SUBMITTER: Hiten Madhani
PROVIDER: E-GEOD-17583 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Cellular processes are subject to variability, or noise, yet mechanisms that promote cell-to-cell uniformity are poorly understood. We have identified such a role for Dig1, a redundant (with Dig2) MAPK-responsive inhibitor of the S. cerevisiae mating pathway transcription factor Ste12. Cells lacking Dig1, but not Dig2, exhibited increased variability in outputs of the mating pathway. dig1∆ mutants also displayed a Ste12-dependent defect in growth in the absence of mating pheromone and a quantitative defect in the process of mating, itself. In cells expressing two reporter genes driven by the same promoter, both intrinsic/uncorrelated and extrinsic/correlated noise were found to increase. Remarkably, the extrinsic noise phenotype in cells lacking Dig1 correlates with the aggregation of target genes: we observed subnuclear foci of Ste12 specifically in dig1∆ cells and, using a newly-developed method to immunoprecipitate a single locus from crosslinked chromatin, we found that Dig1 inhibits long-range interactions between Ste12 target genes in vivo. Dig1 may shield binding surfaces on Ste12 whose unmasking leads to inappropriate gene associations and increased gene expression noise. These studies reveal how investigations of variability modulation mechanisms can yield unexpected biological insights.
2010-12-15 | GSE17583 | GEO
Project description:In this study, we mapped for the first time differences in transcription binding among individuals and elucidated the genetic basis of such variation. Whole-genome Ste12 binding profiles were determined using ChIP-Seq in pheromone-treated cells of 43 segregants of a cross between two highly diverged yeast strains, YJM789 and S288c as well as the parental lines. We identified extensive Ste12 binding variation among individuals and mapped underlying cis- and trans- acting loci responsible for such variation. We showed that the majority of TF binding variation is cis-linked and that many variations are associated with polymorphisms residing in the binding motifs of Ste12 as well as those of several known and proposed Ste12 cofactors. We also identified two trans factors, AMN1 and FLO8, that modulate Ste12 binding to promoters of more than 10 genes under α-factor treatment. Neither of these two genes was known to regulate Ste12 previously, and we suggest that they may be key mediators of gene activity and phenotypic diversity. Ste12 binding strongly correlates with gene expression for more than 200 genes indicating that binding variation is functional. Many of the variable bound genes are involved in cell wall organization and biogenesis. Overall, we identified key regulators of molecular diversity among individuals and provide novel insights into mechanisms of gene regulation. Two ChIP-Seq experiments and one Input DNA-Seq experiment for the yeast strains S96, HS959 and 43 MATa segregants were performed under alpha factor treatment conditions; an additional replicate was also performed for some of the strains. One ChIP-Seq experiment for each parental strain was performed without alpha factor treatment, and one ChIP-Seq experiment for each of the 24 deletion strains was performed under alpha factor treatment.
2010-02-18 | E-GEOD-19635 | biostudies-arrayexpress
Project description:In this study, we mapped for the first time differences in transcription binding among individuals and elucidated the genetic basis of such variation. Whole-genome Ste12 binding profiles were determined using ChIP-Seq in pheromone-treated cells of 43 segregants of a cross between two highly diverged yeast strains, YJM789 and S288c, as well as the parental lines. We identified extensive Ste12 binding variation among individuals and mapped underlying cis- and trans- acting loci responsible for such variation. We showed that the majority of TF binding variation is cis-linked and that many variations are associated with polymorphisms residing in the binding motifs of Ste12 as well as those of several known and proposed Ste12 cofactors. We also identified two trans factors, AMN1 and FLO8, that modulate Ste12 binding to promoters of more than 10 genes under α-factor treatment. Neither of these two genes was known to regulate Ste12 previously, and we suggest that they may be key mediators of gene activity and phenotypic diversity. Ste12 binding strongly correlates with gene expression for more than 200 genes, indicating that binding variation is functional. Many of the variable bound genes are involved in cell wall organization and biogenesis. Overall, we identified key regulators of molecular diversity among individuals and provide novel insights into mechanisms of gene regulation. We measured gene expression levels after 30 minutes treatment with alpha factor for 43 MATa segregants from a YJM789 X S96 cross, as well as MATa parental lines. We also measured the gene expression levels without alpha factor treatment for parental lines (S96, HS959) and SEG8 as controls.
2010-05-14 | E-GEOD-19634 | biostudies-arrayexpress
Project description:Here, we examine how six single amino acid variants in the DNA-binding domain of Ste12 – a yeast transcription factor regulating mating and invasion – alter Ste12 genome binding, motif recognition and gene expression to yield markedly different phenotypes. Using a combination of the calling card method, RNA sequencing , we find that variants with dissimilar binding and expression profiles can converge onto similar cellular behaviors.
2020-01-30 | GSE141713 | GEO
Project description:This model is from the article:
Positive roles for negative regulators in the mating response of yeast.
Houser JR, Ford E, Nagiec MJ, Errede B, Elston TC. Mol Syst Biol
2012 June 5;8:586 22669614
,
Abstract:
All cells must detect and respond to changes in their environment, often through changes in gene expression. The yeast pheromone pathway has been extensively characterized, and is an ideal system for studying transcriptional regulation. Here we combine computational and experimental approaches to study transcriptional regulation mediated by Ste12, the key transcription factor in the pheromone response. Our mathematical model is able to explain multiple counterintuitive experimental results and led to several novel findings. First, we found that the transcriptional repressors Dig1 and Dig2 positively affect transcription by stabilizing Ste12. This stabilization through protein-protein interactions creates a large pool of Ste12 that is rapidly activated following pheromone stimulation. Second, we found that protein degradation follows saturating kinetics, explaining the long half-life of Ste12 in mutants expressing elevated amounts of Ste12. Finally, our model reveals a novel mechanism for robust perfect adaptation through protein-protein interactions that enhance complex stability. This mechanism allows the transcriptional response to act on a shorter time scale than upstream pathway activity.
2005-01-01 | MODEL1204040000 | BioModels
Project description:A fundamental problem in biology is the molecular basis for divergence among related organisms. We have investigated the level of divergence of transcription factor binding sites for two key factors that regulate developmental processes in the budding yeasts. The genomic binding locations for the Ste12 and Tec1 transcription factors in S. cerevisiae, S. mikatae and S. bayanus were mapped by chromatin immunoprecipitation combined with microarrays (chIP chip)1, 2 and compared to one another. While there was a large core network which was conserved in all three species, there were many instances of binding events whose relative levels differ significantly quantitatively in one species relative to another and as well as species-specific binding events. One interesting class of genes were identified that were bound only in S. mikatae and S. bayanus; many of these genes are targets of Ste12 in haploid strains of S. cerevisiae, suggesting that S. cerevisiae has uniquely acquired the ability to differentially regulate these genes in haploid and diploid cells in these species. To extend these studies, the transcriptional network for the Ste12 homologue (Cph1) in Candida albicans was also mapped and compared to the Saccharomyces species. Again, there were several genes bound by Cph1 which are involved in mating in S. cerevisiae, suggesting that the precise delineation between many mating and pseudohyphal targets by Ste12 may be specific to S. cerevisiae. Overall our results demonstrate that transcription binding sites differ faster than gene content indicating that gene regulation at the level of transcription factor binding is likely to be a major mode of evolutionary divergence between related species. We expect that this divergence is essential for the distinct ecological niches inhabited by these organisms. Keywords: chIP-chip ChIP-chip was performed on Ste12 and Tec1 from S. cerevisiae, S. mikatae and S. bayanus in addition to Cph1 from S. cerevisiae. Three biological replicates were performed for each factor in each species with one replicate representing a dye swap.
2007-09-06 | E-GEOD-5421 | biostudies-arrayexpress
Project description:Genetically identical cells exhibit large variability (noise) in gene expression, with important consequences for cellular function. Although the amount of noise decreases with and is thus partly determined by the mean expression level, the extent to which different promoter sequences can deviate away from this trend is not known. Here, we study how different noise levels are encoded by the promoter sequence using massively parallel noise measurements of thousands of synthetically designed promoters. We find that the noise levels of promoters with similar mean expression levels can vary over more than one order of magnitude, with nucleosome-disfavoring sequences resulting in lower noise and more transcription factor binding sites resulting in higher noise. We devised a computational model that can accurately predict the mean-independent component of the noise from DNA sequence alone. Our model suggests that the effect of promoters on noise is partly mediated by the combination of non-specific DNA binding and one-dimensional sliding along the DNA that occurs when transcription factors search for their target sites. Overall, our results demonstrate that small changes in the DNA sequence of promoters can allow tuning of noise levels in a manner that is largely predictable and partly decoupled from effects on the mean expression levels. These insights may assist in designing promoters with desired noise levels. Expression measurements of a collection of synthetic promoters collection that was published in Sharon et al. Nature Biotechnology 2012(doi: 10.1038/nbt.2205). Two replicates of the promoter library integrated into a plasmid in yeast were measured in SC-Glu-URA medium. The promoter library was measured as described in Sharon et. al.(Sharon et al. 2012), except for the differences below. Briefly, a large collection of synthetic promoter reporter gene strains was generated by a pooled ligation of 6500 fully designed DNA oligos (obtained by synthesis on a microarray(LeProust et al. 2010) by Agilent Technologies, Santa Clara, California). The oligos were ligated upstream to a yellow fluorescent protein (YFP) gene with a short (100 bp) core promoter sequence taken from HIS3 gene promoter and into a low copy plasmid which also contains a TEF2 promoter deriving red fluorescent protein (mCherry). The resulting plasmids were then transformation into yeast (S. cerevisiae). Next, the pool of cells was grown in amino acid starvation condition (SCD without amino acid except Histidine), and sorted according to their YFP expression level into 32 expression bins (mCherry was used for gating one plasmid copy cells and for normalization). The DNA of the promoters in each bin were then amplified and sent to multiplexed parallel sequencing. Each sequencing result was mapped to a specific promoter and expression bin, resulting in a distribution of cells that contain each promoter across all expression bins. The following differences were applied relative to the description in Sharon et. al.(Sharon et al. 2012). The medium used both for growing the cells and for their sorting was SC-Glu-URA (synthetic complete media with 2% glucose and without uracil) medium without amino acids, except for Histidine. In order to achieve expression distributions with high resolution that would allow good assessment of expression noise, the library cells were sorted into 32 bins according to their ratio of YFP and mCherry expression level, thereby normalizing for extrinsic noise effects. Each of the two extreme expression bins contained 2% of the library cells and each of the remaining 30 bins contained 3.2%. We collected a total of 10,000,000 cells. As previously described, the mapping of cells to bins involves parallel sequencing of the amplified promoter regions. For this purpose, Illumina Hi-Seq 2000 was used to obtain >30,000,000 mapped reads. The two replicates were separately generated from the ssDNA oligo library and separately measured as described above.
2014-07-12 | E-GEOD-55346 | biostudies-arrayexpress
Project description:We used an unbiased approach to identify differences in gene expression that may account for the high degree of interindividual variability in inflammatory responses to LPS in the normal human population. We measured LPS-induced cytokine production ex vivo in whole blood from 102 healthy human subjects and identified individuals who consistently showed either very high or very low responses to LPS. Comparison of gene expression profiles between the lpshigh and lpslow individuals revealed 80 genes that were differentially expressed in the presence of LPS and 21 genes that were differentially expressed in the absence of LPS (p < 0.005, ANOVA). Expression of a subset of these genes was confirmed using real-time RT-PCR. These data illustrate a novel approach to the identification of factors that determine interindividual variability in innate immune inflammatory responses. Experiment Overall Design: Six whole blood samples (three high and three low responders to LPS) were selected from a cohort of 102 healthy individuals, exposed to media or LPS for 4 hours. RNA was isolated and hybridized with an Affymetrix array.
2007-09-07 | E-GEOD-3491 | biostudies-arrayexpress
Project description:A fundamental problem in biology is the molecular basis for divergence among related organisms. We have investigated the level of divergence of transcription factor binding sites for two key factors that regulate developmental processes in the budding yeasts. The genomic binding locations for the Ste12 and Tec1 transcription factors in S. cerevisiae, S. mikatae and S. bayanus were mapped by chromatin immunoprecipitation combined with microarrays (chIP chip)1, 2 and compared to one another. While there was a large core network which was conserved in all three species, there were many instances of binding events whose relative levels differ significantly quantitatively in one species relative to another and as well as species-specific binding events. One interesting class of genes were identified that were bound only in S. mikatae and S. bayanus; many of these genes are targets of Ste12 in haploid strains of S. cerevisiae, suggesting that S. cerevisiae has uniquely acquired the ability to differentially regulate these genes in haploid and diploid cells in these species. To extend these studies, the transcriptional network for the Ste12 homologue (Cph1) in Candida albicans was also mapped and compared to the Saccharomyces species. Again, there were several genes bound by Cph1 which are involved in mating in S. cerevisiae, suggesting that the precise delineation between many mating and pseudohyphal targets by Ste12 may be specific to S. cerevisiae. Overall our results demonstrate that transcription binding sites differ faster than gene content indicating that gene regulation at the level of transcription factor binding is likely to be a major mode of evolutionary divergence between related species. We expect that this divergence is essential for the distinct ecological niches inhabited by these organisms. Keywords: chIP-chip
2007-09-06 | GSE5421 | GEO
Project description:Yeast chromosome III contains the mating type loci that provide a paradigm for long-range interactions between distant loci. Yeast switch mating type by gene conversion between the MAT locus and either of two silent loci (HML or HMR) on opposite ends of the chromosome. This long-range process is mating type-specific so that MATa cells choose HML as template, while MATα cells use HMR. The Recombination Enhancer (RE), located on the left arm regulates this process. One long-standing hypothesis is that switching is guided by mating type-specific, and possibly RE-dependent three-dimensional folding of chromosome III. Here we used Hi-C, 5C, and live cell imaging to characterize the conformation of chromosome III in both mating types in non-switching strains. We discovered a mating type-specific difference in the folding of the left arm: in MATa cells the left arm is located closely to the centromere-proximal portion of the chromosome as well as to MAT, whereas it is more extended away in MATα cells. Deletion analysis showed that a 1 kb subregion within the RE, which is not necessary during switching, abolished mating type-dependent chromosome folding. In this mutant the conformation of chromosome III is the same in both mating types, but distinct from the wild type MATa or MATα conformations, indicating that the RE induces conformational changes in both mating types. The RE is therefore a composite element with one subregion essential for selecting the appropriate donor during switching, and a separate region involved in modulating chromosome conformation prior to switching. This submission contain 2 biological replicates of Hi-C experiments done in MATa and MATalpha cells in Saccharamycese cerevisiae. It also contains 3 biological replicates of 13 5C experiments in various mutants in MATa and MATalpha cells.
2015-11-20 | E-GEOD-73890 | biostudies-arrayexpress