Alpha Factor arrest cell cycle synchronization time-course microarray in Glucose
Ontology highlight
ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
SUBMITTER: Umut Eser
PROVIDER: E-GEOD-29893 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Lack of G1 cyclin arrest cln1,2,3-delta MET3pr-CLN2 cells Cell cycle syncronization time-course microarray in Glucose. Time-course experiment. Samples are hybridized onto the first timepoint.
2011-06-11 | E-GEOD-29800 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE29800: Lack of G1 cyclin arrest cell cycle synchronization time-course microarray in Glucose GSE29892: Alpha Factor arrest cell cycle synchronization time-course microarray in Galactose GSE29893: Alpha Factor arrest cell cycle synchronization time-course microarray in Glucose Refer to individual Series
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Project description:Alpha Factor arrest cell cycle syncronization time-course microarray in Galactose. Time course from 0 to 40 minute. Time-course experiment. Samples are hybridized onto the first timepoint.
2011-06-11 | E-GEOD-29892 | biostudies-arrayexpress
Project description:This study was part of a larger study on the zebra finch genome (Warren et al 2010. Nature). Here we present a summary of the specific experiment on singing-regulated gene expression. To evaluate the genomic landscape of learned vocal communication, we profiled gene expression in the zebra finch song nucleus, Area X, with custom Agilent oligoarrays for up to seven hours following initiation of singing. We developed algorithms to identify singing-regulated transcripts related to time spent singing, and discovered over 800 transcripts in Area X that are significantly regulated by singing. These included known increases of the egr1 and c-fos transcription factors, and a decrease in the FoxP2 transcription factor, a gene associated with spoken language development. We clusted the singing-regulated genes in Area X into 20 temporal dynamic expression patterns, which include rapidly up-regulated and transient, rapidly up-regulated and sustained, slowly up-regulated and sustained, a late upregulated response, and equally diverse clusters of down-regulated patterns. Using promotor motif search algorithms, we found significant over-representation of transcription factor binding sites in the promoters of genes within specific clusters. These binding sites included those of transcription factors known to be activated by neural activity and plasticity, such as CREB, SRF, AP-1, NFKB1, CFOS, EGR1, and MEF2. Gene expression in Area X was measured before singing (0) or after singing for 0.5, 1, 2, 3, 4, 5, 6, and 7hours. Six independent experiments were performed at each of the 9 timepoints.
2010-05-15 | E-GEOD-19900 | biostudies-arrayexpress
Project description:Studies of transcriptional networks in multi-cellular organisms usually focus on isolated cells and typically assume that the discovered gene networks represent those present in connected cells within a complex organ like the brain. However, similar cell types connected in diverse anatomical networks could differentially influence transcriptional networks. Here, we used laser capture microdissection, expression arrays, genome mapping, and computational inference to explore behaviorally regulated gene networks in the brains of awake, behaving songbirds producing a skilled motor behavior, singing. We found that at baseline, in the absence of singing, a large proportion of genes (17%, >3000) are differentially expressed in the different brain regions of the neural circuit that controls singing. These genes predominantly code for cell communication and connectivity proteins, and non-coding RNAs. Remarkably, the act of singing was associated with differential regulation of ~10% of the coding and non-coding genome. However, less than 1% of genes were singing-regulated in most brain regions and these were largely immediate early genes (IEGs), which peaked early, including the inducible transcription factors EGR1 and FOS. The remaining vast majority of behaviorally regulated gene expression was specific to one or a subset of brain regions, which peaked later. Promoters of the baseline, common, and diverse singing regulated gene clusters were enriched for different combinations of post-translationally activated transcription factors, like CREB, SRF, MEF2, MZF, and the IEG transcription factors. The results suggest that diverse cell-to-cell interactions and differential combinatorial binding of a small group of transcription factors may influence regional diversity of gene networks in seemingly similar cell types. Thus, in highly integrated neural circuits of intact behaving animals, transcriptional network diversity appears to be the rule, rather than the exception. Gene expression in Area X, HVC, LMAN, and Ra was measured before singing (0) or after singing for 0.5, 1, 2, 3, 4, 5, 6, and 7hours. Four-Six independent experiments were performed at each of the 9 timepoints.
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Project description:Time course experiment to study the expression profile of cln3-delta bck2-delta G1 arrested yeast cells upon overexpression of CLN3
2010-06-14 | E-TABM-764 | biostudies-arrayexpress
Project description:In budding yeast, this signaling pathway— the high-osmolarity glycerol (HOG) response —culminates in dual phosphorylation and nuclear translocation of the MAPK, Hog1 (ortholog of mammalian p38/SAPK). Induction of at least 50 genes requires nuclear Hog1, implying that transcriptional up-regulation is necessary to cope with hyperosmotic stress. Contrary to this expectation, we found that cells lacking the karyopherin (Nmd5) required for Hog1 nuclear import or in which Hog1 was permanently anchored at the plasma membrane(HOG1-CCAAX) (or both) withstood hyperosmotic challenge by three different solutes (1 M sorbitol, KCl or NaCl). In cells where activated Hog1 is excluded from the nucleus, there was little change in transcriptional program after exposure to hyperosmotic shock (comparable to hog1∆ cells), as judged by examining several diagnostic mRNAs and by global transcript measurements using microarrays. Systematic genetic analysis ruled out the need for any transcription factor known to be influenced by Hog1 (Hot1, Msn2, Msn4, Sko1 and Smp1). Keywords: Time course of stress response gene expression array The transcriptomes' of HOG1-GFP, hog1del, and HOG1-CCAAX strains before and after 60 min hyperosmotic shock with 1M sorbitol at 25C were compared. Three biological replicates were done, with the first biological replicate done in technical triplicate, and the final two biological replicates beind done in technical duplicate by in slide duplication of features. Several supplementary files attached to the Series are summarized below: GSE8703 B1, B2, B3 Tscombined_matrix files show the averages of the technical replicates for each biological replicate. GSE8703 B1, B2, B3 norm_to_0_matrix files show the fold change over the time course (log2 time 60 - log2 time 0) for each of the three strains in each biological replicate. GSE8703 Figure_S6 shows the 30 genes with the most significant difference between the HOG1-GFP strain and the hog1del strain as determined by SAM. Genes were identified as: >3 fold induction in HOG1-GFP over 60 minute hyperosmotic shock and <3 fold induction in hog1del over 60 minute hyperosmotic shock.
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Project description:We examined global RNA expression in S. cerevisiae wild type cells and ime2D cells (lacking the IME2 gene) that were induced to enter meiosis. These data have provided evidence that the Ime2 protein kinase is required for normal transcription of many genes that contain cell cycle box promoter elements. Cells populations were induced to enter meiosis synchronously and gene expression was analyzed at 0, 2, 4, and 6 hours. Two independent experiments were performed.
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Project description:Quantifying interactions in DNA microarrays is of central importance for a better understanding of their functioning. Hybridization thermodynamics for nucleic acid strands in aqueous solution can be described by the so-called nearest-neighbor model, which estimates the hybridization free energy of a given sequence as a sum of dinucleotide terms. Compared with its solution counterparts, hybridization in DNA microarrays may be hindered due to the presence of a solid surface and of a high density of DNA strands. We present here a study aimed at the determination of hybridization free energies in DNA microarrays. Experiments are performed on custom Agilent slides. The solution contains a single oligonucleotide. The microarray contains spots with a perfect matching complementary sequence and other spots with one or two mismatches: in total 1006 different probe spots, each replicated 15 times per microarray. The free energy parameters are directly fitted from microarray data. The experiments demonstrate a clear correlation between hybridization free energies in the microarray and in solution. The experiments are fully consistent with the Langmuir model at low intensities, but show a clear deviation at intermediate (non-saturating) intensities. These results provide new interesting insights for the quantification of molecular interactions in DNA microarrays. Keywords: experiment to assess technical aspects of hybridization in microarrays The study consists of four experiments. Each experiments consists of one slide with eight identical microarrays which were hybridized with an identical solution but at a different concentration. Per experiment a single target sequence in solution was used for hybridization: target1 to target4 (Table 1 main manuscript or description of samples below). Each target oligo was bought in duplicate, referred to as oligos a and b. In experiment 1 and 2 a fragmentation step (f) was applied. More details can be found in the main manuscript especially Table 3.
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