Underreplication
Ontology highlight
ABSTRACT:
ORGANISM(S): Drosophila melanogaster
SUBMITTER: Igor Zhimulev
PROVIDER: E-GEOD-2551 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Publications
Genomic analysis of Drosophila chromosome underreplication reveals a link between replication control and transcriptional territories.
Belyakin Stepan N SN Christophides George K GK Alekseyenko Artyom A AA Kriventseva Evgenia V EV Belyaeva Elena S ES Nanayev Roman A RA Makunin Igor V IV Kafatos Fotis C FC Zhimulev Igor F IF
Proceedings of the National Academy of Sciences of the United States of America 20050531 23
In Drosophila polytene chromosomes, most late-replicating regions remain underreplicated. A loss-of-function mutant of the suppressor of underreplication [Su(UR)] gene suppresses underreplication (UR), whereas extra copies of this gene enhance the level and number of regions showing UR. By combining DNA microarray analysis with manipulation of the number of Su(UR) gene copies, we achieved genomic-scale molecular identification of 1,036 genes that are arranged in clusters located in 52 UR chromos ...[more]
Similar Datasets
Project description:Sumoylation is generally considered a repressive mark for many transcription factors. However, the in vivo importance of sumoylation for any given substrate remains unclear and is questionable because the extent of sumoylation appears exceedingly low for most substrates. Here, we permanently eliminated SF-1/NR5A1 sumoylation in mice (Sf-1K119R,K194R or 2KR) and found that Sf-12KR/2KR mice failed to phenocopy a simple gain of SF-1 function or show elevated levels of well-established SF-1 target genes. Instead, mutant mice exhibited marked endocrine abnormalities and changes in cell fate that reflected an inappropriate activation of hedgehog signaling. In an immortalized embryonic cell line, the highly SUMO-sensitive target gene Shh is ectopically activated by direct recruitment of unsumoylatable SF-1 to non-canonical DNA binding sites. We propose that sumoylation greatly expands the functional capacity of transcription factors such as SF-1, and is leveraged during development to achieve cell type-specific gene expression in multi-cellular organisms. Adult and embryonic gene expression in adrenals and testes from SF-1 wild type and 2KR homozygous mice are compared using MEEBO microarrays.
2011-08-14 | E-GEOD-30078 | biostudies-arrayexpress
Project description:We have designed a zebrafish genomic microarray to identify DNA-protein interactions in the proximal promoter regions of over 11,000 zebrafish genes. Using these microarrays, together with chromatin immunoprecipitation with an antibody directed against tri-methylated lysine 4 of Histone H3, we demonstrate the feasibility of this method in zebrafish. This approach will allow investigators to determine the genomic binding locations of DNA interacting proteins during development and expedite the assembly of the genetic networks that regulate embryogenesis. Genomic array design Microarrays were designed as described below and manufactured by Agilent Technologies (www.agilent.com). Further information on design can be found at http://jura.wi.mit.edu/bioc/gbell/zfish_chip/. Selection of transcription start sites and identification of promoter sequences We interrogated 5 databases: Ensembl, VEGA, Refseq, ZGC full length clones and a database provided by Dr. Leonard Zon (Harvard Medical School, Boston, USA) in order to assemble an extensive list of zebrafish transcripts. The Zon lab database is a hand-curated database of zebrafish genes that have homologues in other species. We included all transcripts that appeared in the manually annotated databases (VEGA, Zon) and in the ZGC full length database. We also identified genes present in any 2 of the 5 databases and included those not already selected. The transcripts were mapped to the zebrafish genome (Zv4, June 2004) obtained from UCSC Bioinformatics (http://genome.ucsc.edu) and the transcription start site (TSS) for each transcript was determined. Transcripts with TSSs within 500bp were clustered into a transcriptional unit (TU) and promoter regions were identified relative to the most upstream TSS. This resulted in the identification of 13,413 TUs and corresponding promoter regions. Each promoter region was extracted and masked for repetitive sequence by RepeatMasker. If the promoter region contained a gap the upstream sequence was also masked. Information on the transcriptional units that were included in the final design can be found at http://jura.wi.mit.edu/bioc/gbell/zfish_chip/. Selection of oligonucleotides 60-mer oligonucleotide probes representing the region between 1.5kb upstream and 0.5kb downstream of the annotated TSS of each transcriptional unit were then designed. Although transcription factors and other DNA binding proteins are known to regulate genes from distances of greater than -1.5kb or + 0.5kb, much information can be gained from regions close to the TSS [45], and the H3K4Me3 mark studied in this paper is found at the most 5â end of a gene, close to the TSS. Selection of 60-mers for the microarrays was essentially as described in [14] using the Zv4 build of the zebrafish genome and a locally customized version of ArrayOligoSelector. 60-mers were chosen so that promoter regions contained approximately one probe every 250bp with a maximum distance between probes for each promoter region set at 600bp. In cases where only one probe could be designed for a particular TU these were not included in the final design. This process yielded 80,839 probes for 11,171 promoter regions We also incorporated several sets of control probes, both positive and negative. On each array there are 1090 probes designed against âgene desertâ regions, which are genomic regions that are unlikely to be bound by transcriptional regulators, and 270 probes designed against Arabidopsis thaliana genes, which are not present in the zebrafish genome (by BLAST). In addition, because our main motivation for making these microarrays is to identify mesodermally-regulated genes we included 7 genes expressed in mesoderm during gastrulation as positive controls (wnt11, flh, vent, msgn1, myod, fgf8, pcdh8). Probes designed against these promoters, which flank from 3-4kb around each TSS, are arrayed 2-4 times on each slide. Since these genes are expressed at gastrula stages to varying degrees, they also serve as a positive controls in this study. Finally there are 2256 controls added by Agilent and a variable number of blank spots. These probes were divided between two microarray slides each with 44,290 features. We refer to these two microarray slides as the âproximal promoter setâ. A proximal promoter set based on these designs as well as an expanded set of 9 slides which contain regions from â9kb to + 3kb relative to the TSS, are available by contacting Agilent (www.agilent.com) or by downloading the design files from http://jura.wi.mit.edu/bioc/gbell/zfish_chip/ for self-manufacture.
2010-07-01 | E-GEOD-4863 | biostudies-arrayexpress
Project description:The proteasome can regulate transcription through proteolytic processing of transcription factors and via gene locus binding, but few targets of proteasomal regulation have been identified. Using genome-wide location analysis and transcriptional profiling in Saccharomyces cerevisiae, we have established which genes are bound and regulated by the proteasome, and by Spt23 and Mga2, transcription factors activated by the proteasome. We observed proteasome association with gene sets that are highly transcribed, controlled by the mating-type loci, and involved in lipid metabolism. At ribosomal protein genes, proteasome and RNA polymerase II binding was enriched in a proteasome mutant, indicating a role for the proteasome in dissociating elongation complexes. The genomic occupancies of Spt23 and Mga2 overlapped significantly with the genes bound by the proteasome. Finally, the proteasome acts in two distinct ways, one dependent and one independent of Spt23/Mga2 cleavage, providing evidence for cooperative gene regulation by the proteasome and its substrates. Keywords: ChIP-chip; genetic modification transcriptional profiling Six genomic localization analysis (GLA, ChIP2) experiments are represented by 18 samples. Six transcriptional profiling experiments (prof) are also represented. Experiments were generally done in triplicate, with fluors swapped on the third replicate.
2006-02-28 | E-GEOD-4272 | biostudies-arrayexpress
Project description:The existence of two separate lineages of Escherichia coli O157:H7 has previously been reported, and research indicates that one of these lineages (lineage I) might be more pathogenic towards human hosts. We have previously shown that the more pathogenic lineage expresses higher levels of Shiga toxin 2 (Stx2) than the non-pathogenic lineage II. To evaluate why lineage 2 isolates do not express appreciable levels of toxin, two lineage 2 isolates (FRIK966 and FRIK2000) were chosen as representatives of lineage 2 and whole genome microarrays were performed using Agilent microarrays using the E. coli O157:H7 EDL933 lineage I clinical type isolate as a reference. Microarray results were utilized to evaluate what genes and pathways might be missing or differentially expressed. Quantitative RT-PCR was utilized to validate the microarray data. Based upon the transcriptome of Escherichia coli O157:H7 EDL933 an oligonucleotide microarray, made up of 60 mers was designed. A total of 4873 genes in an 8 x 15K Agilent microarray design. Designed using a custom script, specifications for gene specific oligos were based upon various design characteristics such as temperature of melting, 3’ location, specificity, lack of repeat nucleotides, etc. (Charbonnier et al., 2005). Arrays were manufactured using Agilent Sure-print technology. Each array consisted of duplicate elements for each gene randomly distributed with Agilent control elements included. All procedures were performed according to respective manufacturer protocols. Lineage I and lineage II strains were grown overnight as described, a total of 10e7 cells were washed twice in fresh media, normalized based upon optical density, inoculated into fresh media, incubated at 37oC shaking 120 x g for 3 hours and then suspended in RNAprotect bacteria reagent (Qiagen Inc., Valencia, CA.). Total RNA was extracted using RNeasy Bacteria Mini Kit (Qiagen Inc., Valencia, CA.) and trace amounts of DNA were removed using RNase-Free DNase Set (Qiagen Inc., Valencia, CA.). RNA was quantified using Nanodrop system (NanoDrop Technologies, Wilmington, DE) and quality confirmed by electrophoresis on a Bio-rad Experion system (BioRad XXX). For each sample, 10 ug of RNA were labeled with either CyDye3-dCTP or CyDye5-dCTP (Perkin Elmer) using the LabelStar kit (Qiagen Inc., Valencia, CA.) and Random nonamers (Integrated DNA Technologies ). Labeled cDNA were hybridized to the microarray using Agilent Hi-RPM hybridization solution in an Agilent Hybridization chamber (Agilent.). A total of 8 arrays, each with duplicate elements for each gene, alternating dye swap for each replicate (4 biological replicates), were analyzed to obtain genes that were consistently and differentially regulated in comparison to EDL933, while limiting false discover rate (FDR) below a stringent 5% (Benjamini and Hochberg, 1995).
2009-08-31 | E-GEOD-17070 | biostudies-arrayexpress
Project description:Summer mortality of the Pacific oyster Crassostrea gigas is the result of a complex interaction between oysters, their environment and pathogens. Heredity appears to be a major factor determining the sensitivity of oysters to summer mortality, allowing resistant (R) and susceptible (S) lines to be produced. We conducted genome-wide expression profiling of R and S gonads during the 3-month period preceding a summer mortality event using a 9K cDNA microarray that we designed. This transcriptional analysis provides new indications to define markers for Quantitative Trait Loci searches and functional studies, and evaluates the potential role of each gene in the resistance to summer mortality For microarray analysis, R and S oysters were sampled four times (dates 1 to 4: May 9, May 25, June 6, and June 20, respectively). On each date, 3 replicates of 8 oysters were sampled from each line (R and S) and the gonads prepared for total RNA extraction. Furthermore, the entire tissues of 10 wild oysters were collected, pooled and homogenized to constitute a single total RNA sample for use as a reference in all slide hybridizations and RT-PCR analysis. For microarray hybridizations, 5µg of total RNA were directly labeled by reverse transcription and then purified using the Direct ShipShot Labeling kit (Promega). This reaction was performed for each of the 24 gonad samples, with Cy5 (red) incorporation. The reference sample was Cy3-labeled (green) in 24 separate tubes following the same protocol. The 24 Cy3-labeled cDNAs were next pooled, and then divided once more into 24 samples to obtain a homogeneous reference. Equimolar amounts of cDNA samples and cDNA reference labeled with Cy5 and Cy3, respectively, were SpeedVac evaporated and mixed into a single pool with the hybridization buffer (ChipHyb™ hybridization buffer, Ventana Discovery, Tucson, AZ, USA). They were then co-hybridized on the same microarray slide, in a Ventana hybridization station (Ventana Discovery, Tucson, AZ, USA). The data submitted here correspond to the mean of the three replicates for each line and each date, representing 8 samples : gonad_resistant_date1 gonad_sensitive_date1 gonad_resistant_date2 gonad_sensitive_date2 gonad_resistant_date3 gonad_sensitive_date3 gonad_resistant_date4 gonad_sensitive_date4
2009-08-15 | E-GEOD-16448 | biostudies-arrayexpress
Project description:all data from control and diabetic
2010-06-05 | E-GEOD-2068 | biostudies-arrayexpress
Project description:Background: The mosquito Anopheles gambiae is a major vector of human malaria. Increasing evidence indicates that blood cells (hemocytes) comprise an essential arm of the mosquito innate immune response against both bacteria and malaria parasites. To further characterize the role of hemocytes in mosquito immunity, we undertook the first genome-wide transcriptomic analyses of adult female An. gambiae hemocytes following infection by two species of bacteria and a malaria parasite. Results: We identified 4047 genes expressed in hemocytes, using An. gambiae genome-wide microarrays. While 279 transcripts were significantly enriched in hemocytes relative to whole adult female mosquitoes, 959 transcripts exhibited immune challenge-related regulation. The global transcriptomic responses of hemocytes to challenge with different species of bacteria and/or different stages of malaria parasite infection revealed discrete, minimally overlapping, pathogen-specific signatures of infection-responsive gene expression; 105 of these represented putative immunity-related genes including anti-Plasmodium factors. Of particular interest was the specific co-regulation of various members of the Imd and JNK immune signaling pathways during malaria parasite invasion of the mosquito midgut epithelium. Conclusion: Our genome-wide transcriptomic analysis of adult mosquito hemocytes reveals pathogen-specific signatures of gene regulation and identifies several novel candidate genes for future functional studies. In order to identify hemocyte-specific and immune-responsive transcripts, we first compared transcripts expressed in hemocytes from one day old sugar-fed mosquitoes to transcripts detected in whole mosquitoes of the same age and feeding status. This resulted in identification of the hemocyte-enriched transcriptome. We then compared hemocytes from 1 day old mosquitoes, 1 hour after immune challenge with heat-killed Escherichia coli or Micrococcus luteus, to control female mosquitoes injected with sterile PBS to determine the bacteria challenge responsive transcriptomes. We used heat-killed bacteria in these assays, because our primary interest was in identifying the bacterial responsive transcriptome and to avoid the potentially confounding effects of altered gene expression due to the lethal effects of a systemic infection associated with injection of living bacteria. Lastly, we compared hemocytes from mosquitoes at 24 hours and 19 days after ingestion of a blood meal infected with Plasmodium berghei to mosquitoes of the same age fed a non-infected blood meal to determine the ookinete and sporozoite infection responsive transcriptomes, respectively. This design resulted in a total of five experimental treatments. The following samples are not included in this submission: Hemo E coli vs. hemo unchallenged A Hemo E coli vs. hemo unchallenged B Hemo m luteus vs. hemo unchallenged A Hemo m luteus vs. hemo unchallenged B
2011-10-31 | E-GEOD-33269 | biostudies-arrayexpress
Project description:We used cDNA microarray technology to compare the genome-wide expression profiles of a wild type strain (BY4700) (E02, E04, E06) or the isogenic strain deleted of GLN3 and GAT1 genes (E01, E03, E05) grown in YNB medium with glutamine as nitrogen source (M.Gln) against the wild type strain grown in M.Gln after addition of rapamacyn (20 min) (E01, E02), or M.proline (M.Pro) (E03, E04) or after a two hours shift from M.Gln to M.Pro (E05, E06), all growth conditions known to modify the expression of genes involved in nitrogen utilization. These microarrays allowed to identify the set of genes that were up or down-regulated in response to the quality of the nitrogen source. To evaluate whether the majority of genes responding to the nitrogen source were dependent on Gln3 and Gat1, we compared the expression profiles of the wild type strain and of the isogenic strain deleted of GLN3 and GAT1 genes (03167b: ura3, gln3â, gat1â), when both strains were grown on M.Gln + rapamycin (E07), or M.Pro (E08) or after a shift from M.Gln to M.Pro (E09). We also used an independent means of identifying Gln3-Gat1 regulated genes by comparing the expression profiles in wild type and ure2â (4709âURE2) strains on M.Gln medium (E10). The hybridization signal was measured using a GSM418 laser scanner. Image analysis for each array was processed using the GenePix Pro 4.0 (Axon Instruments, Inc.) software package, which measures fluorescence intensity pairs for each gene. Following image acquisition, a visual inspection of the individual spots on each microarray (size, signal-to-noise ratio, background level, and spot uniformity) completed the flagging (present/not present, good/bad) of the data. To maximize sensitivity two scans were made, one at high laser power and high PMT (Photo Multiplier Tube) gain to detect the faintest spots, and a second one using low laser power and a PMT gain avoiding saturation. The values for spots presenting ⥠5% saturation in the first scan were calculated based on an extrapolation after linear regression analysis of the intensities from both scans. These data were then imported in the GeneSpring 7.1 (Silicon Genetics) software package, applying a per spot per chip intensity-dependent (Lowess) normalization for further analysis.
2010-07-01 | E-GEOD-2891 | biostudies-arrayexpress
Project description:This series represents the effects of OVA, tg-IL-13, and direct effects of IL-13 on airway epithelial cells. Experiment Design: Type of experiment: comparison of three related murine models of asthma, 1) Ova model, 2) tg-IL-13 model, 3) IL-13/Epi model. Two control groups were used: PBS challenged mice to control for the effects of OVA and tg-IL-13+ and STAT6-/- mice as controls for tg-IL-13 and IL-13/Epi mice. Measurements were made in each model in two types of tissue samples, whole lung and tracheal perfusate. Experimental factors: Allergen vs sham challenge, natural STAT6 expression vs transgenic expression and no expression. The number of hybridizations performed in the experiment: 50 (25 whole lung and 25 tracheal perfusate). The type of reference used for the hybridizations, if any: Pooled reference from lung (whole lung or tracheal perfusate) from untreated wildtype mice. Hybridization design: two-color hybridizations with reference design. Each individual sample was hybridized to a separate array. Quality control steps taken: 5 experimental replicates per group. RNA integrity assessed by Agilent Bioanalyzer. Arrays with low signals, high background, or high spatial variation rejected and corresponding samples reanalyzed. URL of any supplemental websites or database accession numbers:GEO (http://www.ncbi.nlm.nih.gov/geo, accession number GSE1438). ********** Samples used, extract preparation and labeling: The origin of the biological sample: homogenized whole lung from mouse and perfusate of mouse trachea. Manipulation of biological samples and protocols used: Whole lungs mechanically homogenized in 7.0 ml Trizol reagent (Invitrogen) for total RNA collection. Tracheas perfused with lysis buffer (Qiagen Rneasy kit) for total RNA collection. Protocol for preparing the hybridization extract and labeling: Preparation of aminoallyl-UTP labeled whole lung cDNA was performed as described [1]. Total RNA from tracheal perfusate (1.0 - 1.5 g per sample) was amplified and labeled with aminoallyl-dUTP using the MessageAmp aRNA kit (Ambion). Labeled cRNAs were coupled to Cy3 or Cy5 dyes (CyScribe, Amersham Biosciences) and purified as described [1]. Labeling protocol(s): Coupled to Cy3 or Cy5.External controls (spikes): none. ********** Hybridization procedures and parameters: Hybridizations were performed as described [1] except Ambion SlideHyb Glass Array Hybridization Buffer #1 (neat concentration) was used as hybridization buffer and hybridizations were carried out for 40 h at 55 °C. Following hybridization, arrays were washed in 1X SSC with 0.03% SDS (wash 1), 0.2X SSC (wash 2), and 0.05X SSC (wash 3) for five minutes for each wash. ********** Measurement data and specifications: Arrays were scanned using an Axon Genepix 4000B scanner and GenePix Pro Analysis 5.0 software; laser power 100%, 10 micron resolution, PMT optimized for each array. Data from GPR files are available from GEO (http://www.ncbi.nlm.nih.gov/geo, accession number GSE1438).The âprint-tip loessâ normalization was used to correct for within-array dye and spatial effects and single channel quantile normalization was used to facilitate comparison between arrays. No background subtraction was performed. We used functions in the library marrayNorm of the R / Bioconductor package to perform these normalizations. After normalization we determined the log2 ratio of experimental sample intensity to reference sample intensity for each probe on each array. ********** Array Design: General array design Array design name: UCSF 10Mm Mouse v.2 Oligo Array (GEO GPL1089) and UCSF Gladstone 18K Mouse v.2 Oligo Array (GPL1196) Platform type: spotted oligonucleotides (70mers) Surface and coating specification: aminosilane coated glass slides Physical dimensions of array support (e.g. of slide): 25 x 75 x 1.0 mm Number of features on the array: GPL1089: 19152, GPL1196: 18240 (including empty and duplicate features) For production protocol, see http://www.microarrays.org/pdfs/PrintingArrays.pdf Feature information is available from GEO (GSE1438). Reporters: synthetic single stranded oligonucleotides. Sequence and annotation information available from GEO (GPL1089 and GPL1196) Method of reporter preparation: synthesized by Operon. The spotting protocols used, including the array substrate, the spotting buffer, and any post-printing processing, including cross-linking: see http://www.microarrays.org/pdfs/PrintingArrays.pdfAny additional treatment performed prior to hybridization: none. ********** Reference: 1. Barczak A, Rodriguez MW, Hanspers K, Koth LL, Tai YC, et al. (2003) Spotted long oligonucleotide arrays for human gene expression analysis. Genome Res 13: 1775-1785. Keywords = IL-13 Keywords = Epithelial Keywords = differential gene expression Keywords = microarray
2010-06-10 | E-GEOD-1438 | biostudies-arrayexpress
Project description:Functional liability conferred by gene expression profile can be a possible basis for diseases phenotype. By comparing gene expression profiles in splenic T cells from NOD, C57BL/6 mice and their congenic strains with altered MHCs (NOD.H2^h4 , B6.NOD/Idd1,5/), we identified that the NOD splenic T cells have a strain dependent, tissue specific unique gene expression profile that can be but not necessarily be modulated by alternation of MHC. The NOD splenic T cells gene expression profile indicated a deregulated stress response system, especially heat shock protein family. We demonstrated that NOD splenic T cells have apoptosis defect in vivo and in vitro. Therefore, the gene expression profile may confer liability upon NOD splenic T cells to make them more susceptible to apoptosis, which can be a critical factor to lead to NOD lymphopenia. As recently described, compensatory homeostatic proliferation, driven by lymphopenia, generates autoimmunity in the NOD mouse.
2010-06-10 | E-GEOD-2524 | biostudies-arrayexpress