Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Chromosomal clustering of genes in trithorax (trx) mutant larvae

ABSTRACT: We have performed a systematic examination of genome-wide expression profiles using microarrays to reconstruct a global picture of the trx regulatory gene network in D. melanogaster. Using computational analysis of the microarray data, we have identified 25 clusters of genes potentially regulated by trx, most of them being located in the arm L of chromosome 3. Functional analysis revealed that most clusters are enriched in structural proteins involved in cuticle formation, which are preferently expressed in salivary glands. The same organization in clusters was observed in the transcriptomes of four independent experiments, being a distinctive feature of the regulatory networks of trx and other chromatin regulators (ASH2, NURF, Pc, ASH1). We have also identified many of these clusters in D. simulans, D. yakuba, D. pseudoobscura and partially in A. gambiae. Keywords: loss of function analysis Total RNA from w1118;+;+ larvae was pooled and used as a common reference in four microarrays against w1118;+;trxE3/trxB11 total RNA coming from two different extractions to take biological differences into account. Two amplifications from w1118;+;+ and one from each w1118;+;trxE3/trxB11 replicate were performed with the Amino-Allyl Messageamp II aRNA Amplification Kit (Ambion, Inc) to obtain amplified RNA (aRNA). The two arrays from each replicate pair were hybridized with the same amplified RNA from sample and common reference but with dyes (Cy3 and Cy5 from Amersham, Inc) swapped to take dye-bias into account.

ORGANISM(S): Drosophila melanogaster

SUBMITTER: AdriÃ Punset

PROVIDER: E-GEOD-8748 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Conserved chromosomal clustering of genes governed by chromatin regulators in Drosophila.

Blanco Enrique E Pignatelli Miguel M Beltran Sergi S Punset Adrià A Pérez-Lluch Silvia S Serras Florenci F Guigó Roderic R Corominas Montserrat M

Genome biology 20080910 9

<h4>Background</h4>The trithorax group (trxG) and Polycomb group (PcG) proteins are responsible for the maintenance of stable transcriptional patterns of many developmental regulators. They bind to specific regions of DNA and direct the post-translational modifications of histones, playing a role in the dynamics of chromatin structure.<h4>Results</h4>We have performed genome-wide expression studies of trx and ash2 mutants in Drosophila melanogaster. Using computational analysis of our microarray ...[more]

PMID: 18783608

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Project description:Research on the ability of certain organisms to reconstruct missing structures of their bodies is still in its infancy, despite numerous efforts performed in multiple species. Using expression profile analyses on different timepoints that cover wound healing and regeneration processes (0, 24 and 72 hours post injury), we studied the regenerative behaviour of fragmented wing imaginal discs of D. melanogaster implanted into adult flies. First, through the comparison between cut and intact discs, we identified the effect of implantation on the regeneration process. Filtering this information, we then constructed the specific early regeneration gene signature of wing discs in which multiple transcription factors, immune response genes and members of the JNK, Notch and WNT signaling pathways seem to play an important role. We next compared the transcriptomes of discs 24 and 72 hours after fragmentation to characterize the regenerative machinery and observed a temporal decrease in the cellular metabolic processes, RNA processing and gene expression machinery, suggesting the discs normal activity was stopped on this first interval of time in response to injury and implantation offences. Based on the expression patterns, we elaborated a catalogue of genes involved in wing disc regeneration divided into four classes (wound healing, regeneration, quick response, constant response). Imaginal discs from third instar larvae were 3/4 fragmented, implanted into the abdomen of adult flies and cultured. In order to subtract the noise due to implantation, we repeated the same protocol using intact discs that were cultivated for 24h. Therefore, a total of 12 microarrays were hybridized: four microarrays (with total RNA from non cut wing discs at 0 and 24 hours) were used to assess the effect of the implantation procedure in intact wing discs and the rest (8) were used to measure changes in gene expression in the first 24 hours after disc dissection and implantation (total RNA from wing discs at 0 and 24 hours was hybridized) and during the period between 24 and 72 hours after the cut (total RNA from wing discs at 24 and 72 hours was hybridized). At least two independent total RNA extractions were carried out (using the RNeasy Protect Mini Kit from Qiagen Inc.) for each condition. The four microarrays hybridized for each pair of conditions were done in biological replicate pairs with dyes swapped to take dye bias into account. The whole set of microarrays was normalized following the same protocol, extracting in each case the list of significant genes (at least 1.5-fold change, FDR adjusted pvalue < 0.05).

Project description:Histone modifications affect DNA-templated processes ranging from transcription to genomic replication. In this study, we examine the cell cycle dynamics of the trimethylated form of histone H3 lysine 4 (H3K4me3), a mark of active chromatin that is viewed as â??long-livedâ?? [1], and that is involved in memory during cell state inheritance in metazoans [2]. We synchronized yeast using two different protocols, then followed H3K4me3 patterns as yeast passed through subsequent cell cycles. While most H3K4me3 patterns were conserved from one generation to the next, we found that methylation patterns induced by alpha factor or high temperature were erased within one cell cycle, during S phase. Early-replicating regions were erased before late-replicating regions, implicating replication in H3K4me3 loss. However, incomplete H3K4me3 erasure occurred at the majority of loci even when replication was prevented, suggesting that most erasure results from an active process. Indeed, deletion of the demethylase Jhd2 slowed erasure at most loci. Together, these results indicate overlapping roles for passive dilution and active enzymatic demethylation in erasing ancestral histone methylation states in yeast. References: [1] Ng HH, Robert F, Young RA, Struhl K (2003) Targeted recruitment of Set1 histone methylase by elongating Pol II provides a localized mark and memory of recent transcriptional activity. Mol Cell 11: 709-719. [2] Ringrose L, Paro R (2004) Epigenetic regulation of cellular memory by the Polycomb and Trithorax group proteins. Annu Rev Genet 38: 413-443. The overall design of the experiment consists of two cell cycle experiments, each consisting of the following subsets: gene expression, ChIP with anti-H3K4Me3 antibody, and ChIP input. The experiments are as follows: CCA - BY4741 bar1- cells synchronized by alpha factor arrest; CCTS - BY4741 cdc28(ts) cells synchronized by arrest at non-permissive temperature. The individual time courses are enumerated as follows: CCA gene expression (array title "Synchronized cells, xxx min, cell cycle CCA"), 18 arrays; CCA ChIP for anti-H3K4Me3 (array title "H3K4Me3 ChIP cell cycle CCA, xxx min"), 17 arrays, 1 replicate; CCA ChIP input (array title "ChIP Input cell cycle CCA, xxx min"), 18 arrays, 1 replicate; CCTS gene expression (appears in a different dataset as biological replicate "I"; array title "Synchronized cells, xxx min, biological replicate I"), 18 arrays; CCTS ChIP for anti-H3K4Me3 (array title "H3K4Me3 cell cycle CCTS, xxx min"), 2 technical replicates, 18 arrays per replicate; CCTS ChIP input (array title "ChIP Input cell cycle CCTS, xxx min"), 2 technical replicates, 18 arrays per replicate. Gene expression arrays were run against a reference of unsynchronized cells, ChIP-chip anti-H3K4Me3 samples were run against an IP (of the same epitope) of unsynchronized cells, and ChIP input samples were run against either a pool of all the time points in the time course (CCTS) or against sonicated DNA isolated from unsynchronized cells (CCA). Four additional experiments have been performed. They are referred to as series X in the title. Series 1: anti H3K4me3 CHIP time course of BY4741 bar1 delete cells (wt) synchronized with alpha factor and released in the cell cycle, 9 arrays, 1 replicate. Series 2: anti H3K4me3 CHIP time course of BY4741 bar1 jhd2 delete cells (jhd2 delete) synchronized with alpha factor and released in the cell cycle, 7 arrays, 1 replicate. Series 3: anti H3K4me3 CHIP time course of CYM36 cells (cdc7ts) synchronized with alpha factor and released in the cell cycle at the permissive 24C or at the restrictive 37C temperature, 22 arrays, 2 replicates. Series 4: anti H3K4me3 CHIP time course of BY4741 bar1 delete cells (wt) grown in galactose and synchronized with alpha factor and either released in the cell cycle in glucose media or alpha factor arrested and switched to glucose media, 6 arrays, 1 replicate.

Project description:Significant insight about biological networks arises from the study of network motifs âoverly abundant network subgraphs, but such wiring patterns do not specify when and how potential routes within a cellular network are used. To address this limitation, we introduce activity motifs, which capture patterns in the dynamic use of a network. Using this framework to analyze transcription in Saccharomyces cerevisiae metabolism, we find that cells use different timing activity motifs to optimize transcription timing in response to changing conditions: forward activation to produce metabolic compounds efficiently, backward shutoff to rapidly stop production of a detrimental product and synchronized activation for co-production of metabolites required for the same reaction Measuring protein abundance over a time course reveals that mRNA timing motifs also occur at the protein level. Timing motifs significantly overlap with binding activity motifs, where genes in a linear chain have ordered binding affinity to a transcription factor, suggesting a mechanism for ordered transcription. Finely timed transcriptional regulation is therefore abundant in yeast metabolism, optimizing the organism's adaptation to new environmental conditions. We generated a set of 13 time courses by measuring gene expression after a metabolic change. Yeast strain KCN118 (MATalpha ade2) was grown at 28 Â°C in 400 ml of synthetic complete media with 2% dextrose (SCD) to an OD600 of 0.6. Synthetic complete was prepared using the standard recipe, except 75 uM inositol was included. At OD600 of 0.6, 100 ml of cells were collected by centrifugation and frozen as a reference sample, and the remaining cells were rapidly collected by filtration, washed with distilled water and resuspended in 300 ml of one of the following media: SCE (SC + 2% ethanol), SCG (SC + 2% galactose), SM1 (SCD lacking amino acids A, R, N, C, Q, G, K, P, S, F and T), SM2 (SCD lacking amino acids L, I, V, W, H and M), S0 (SCD lacking all amino acids), S0G (no amino acids, 2% galactose) or S0E (no amino acids, 2% ethanol). The data appears in Figures 2 and 4 of the manuscript, as it relates to the global analysis of all the arrays used in the dataset. All time courses consist of the following time points (in min): 15, 30, 60, 120, 240, and were hybridized against the t = 0 time point of cells grown in SCD. Each time course was performed as one single biological replicate and one technological replicate, except where noted below. Specifically, the 13 time courses break down into the following groups: Media key: SCD (synthetic complete, not including inositol) SCE (SC + 2% ethanol) SCG (SC + 2% galactose) SM1 (SCD lacking amino acids A, R, N, C, Q, G, K, P, S, F and T) SM2 (SCD lacking amino acids L, I, V, W, H and M) S0 (SCD lacking all amino acids) S0G (no amino acids, 2% galactose) S0E (no amino acids, 2% ethanol). ino = inositol aa = all amino acids supplemented The following group descriptions are the media as described above, followed by the description as indicated in the long title of the individual arrays: 1. S0 (5 arrays) = SD 2. SCD (6 arrays, t = 240 min has 2 tech replicates) = SD+aa 3. SM2 (5 arrays) = SD+aa:ARNCQGKPSDEFTY+ino 4. SM1 + ino (5 arrays) = SD+aa:LIVWHM+ino 5. S0 + ino (6 arrays, t = 240 min has 2 tech replicates) = SD+ino 6. S0E (5 arrays) = SEtOH 7. S0E + aa (7 arrays, t = 240 min and 60 min each have 2 tech replicates) = SEtOH+aa 8. S0E + aa + ino (5 arrays) = SEtOH+aa+ino 9. S0E + ino (8 arrays, t = 240 min, 15 min and 30 min each have 2 tech replicates) = SEtOH+ino 10. S0G (5 arrays) = Sgal 11. S0G + aa (5 arrays) = Sgal+aa 12. S0G + aa + ino (5 arrays) = Sgal+aa+ino 13. S0G + ino (6 arrays, t = 60 min has 2 tech replicates) = Sgal+ino

Dataset Information

Chromosomal clustering of genes in trithorax (trx) mutant larvae

Publications

Conserved chromosomal clustering of genes governed by chromatin regulators in Drosophila.

Similar Datasets

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