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  • This is a dataset generated by the Drosophila Regulatory Elements modENCODE Project led by Kevin P. White at the University of Chicago. It contains genome-wide binding profile of the factor H3K27me3 from D.pse_E0-4h generated by ChIP and analyzed on Illumina Genome Analyzer. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A validated dataset is comprised of three biological replicates for ChIP-chip experiments and two replicates for ChIP-seq and meet the modENCODE quality standards. The control sample is the chromatin Input used for ChIP. Factors binding profiles are generated by using specific antibodies for the protein of interest. This submission represents the ChIP-seq component of the study
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  • This is a dataset generated by the Drosophila Regulatory Elements modENCODE Project led by Kevin P. White at the University of Chicago. It contains genome-wide binding profile of the factor KW3-Trl-D2 from D.pse_E0-4h generated by ChIP and analyzed on Illumina Genome Analyzer. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A validated dataset is comprised of three biological replicates for ChIP-chip experiments and two replicates for ChIP-seq and meet the modENCODE quality standards. The control sample is the chromatin Input used for ChIP. Factors binding profiles are generated by using specific antibodies for the protein of interest. This submission represents the ChIP-seq component of the study
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  • This is a dataset generated by the Drosophila Regulatory Elements modENCODE Project led by Kevin P. White at the University of Chicago. It contains genome-wide binding profile of the factor H3K27me3 from D.pse_WPP generated by ChIP and analyzed on Illumina Genome Analyzer. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A validated dataset is comprised of three biological replicates for ChIP-chip experiments and two replicates for ChIP-seq and meet the modENCODE quality standards. The control sample is the chromatin Input used for ChIP. Factors binding profiles are generated by using specific antibodies for the protein of interest. This submission represents the ChIP-seq component of the study
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    • File Set
  • This is a dataset generated by the Drosophila Regulatory Elements modENCODE Project led by Kevin P. White at the University of Chicago. It contains genome-wide binding profile of the factor KW3-Kr-D2 from D.sim_E0-4h generated by ChIP and analyzed on Illumina Genome Analyzer. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A validated dataset is comprised of three biological replicates for ChIP-chip experiments and two replicates for ChIP-seq and meet the modENCODE quality standards. The control sample is the chromatin Input used for ChIP. Factors binding profiles are generated by using specific antibodies for the protein of interest. This submission represents the ChIP-seq component of the study
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  • This SuperSeries is composed of the following subset Series: GSE29517: ChIP-chip from Drosophila egg chambers using ORC2 antibody GSE29518: ChIP-chip from dissected Drosophila egg chambers using antibody recognizing RNAPII GSE29520: ChIP-chip from Drosophila egg chambers using antibody recognizing tetra-acetylated histone H4 GSE29526: Expression profile of 16C ovarian follicle cells Refer to individual Series
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  • LID is a histone demethylase acting on H3K4me3, a mark related to transcription and found near the transcription start sites (TSS) of the genes. We analyzed where LID is localized and the effects of LID downregulation in the distribution of H3K4me3. Analysis of LID-binding sites in wild type, and of H3K4me3-binding sites in wild type and LID RNAi wing imaginal discs.
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  • Loss of Lsd1 in Drosophila in specific cells of the Drosophila ovary results in increased BMP signaling outside the cap cell niche and an expanded germline stem cell (GSC) phenotype. To better characterize the function of Lsd1 in different cell populations within the ovary, we performed Chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq). This analysis shows that Lsd1 associates with a surprisingly limited number of sites in escort cells and fewer, and often, different sites in cap cells. These findings indicate that Lsd1 displays highly selective binding in specific cellular contexts. Examination of epitope tagged Lsd1 transgenes in specific cell populations within the Drosophila ovary
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  • This SuperSeries is composed of the following subset Series: GSE36735: Distribution of Drosophila insulator protein BEAF-32 in Wing imaginal tissue (Wildtype) [ChIP-seq] GSE36736: Genome wide transcriptional profiling of BEAF-32 in wing imaginal tissues of wildtype and mutants [expresion array] Refer to individual Series
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  • JAK/STAT pathway plays important roles in controlling Drosophila intestinal homeostasis and regulating the ISC proliferation and differentiation. However,the downstream targets of its transcription factor-STAT92E remain largely unknown.To further identify the regualtory mechanisms of the JAK/STAT pathway in controlling intestinal homeostasis,we performed the ChIP-Seq assay with mouse raised STAT92E antibody using JAK/STAT signaling highly activated adult intestines.Through the ChIP assay, we have identified over 1000 significant peaks (p<0.01) around the putative targets.The well-characterized JAK/STAT downstream targets including Domeless,Socs36E,STAT92E and chinmo were identified in our ChIP assay,indicating that our experiment is workable to identify novel JAK/STAT downstream targets in adult intestines.This work will provide insights into our understanding of regulatory mechanisms of JAK/STAT signaling during Drosophila intestinal development. Identify the ChIP peaks of STAT92E antibody using JAK/STAT signaling highly actived Drosophila adult intestines, compared with input libaray as the control
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  • Transcription factors and their number of target genes in the D. melanogaster ChIP-chip gold standard network and in the predicted networks for six Drosophila species at the 10% recall level (in brackets for each TF the number of true positive predictions). The bottom two rows are the total number of interactions in each network and the overall precision (percentage of true positives) of the predicted networks.... We collected gene expression data for 3,610 genes in six Drosophila species measured at 9–13 time points during early embryonic development with 3–8 replicates per time point (200 samples in total) . To obtain a global view on the similarities and differences between samples, we performed multi-dimensional scaling using Sammon’s nonlinear mapping criterion on the 3,610-dimensional sample vectors (cf. Methods and Figure fig:sammona). The first (horizontal) axis of variation corresponded to developmental time, with samples ordered along this dimension according to increasing developmental time points, while the second (vertical) axis of variation corresponded to evolutionary distance, with samples ordered along this dimension according to species. By expanding these two axes of variation into principal components, we found that the “developmental” dimension explained 34% of the total variation in the data, while the “evolutionary” dimension explained 11% (cf. Methods). This result confirms that variations in gene expression levels across Drosophila species at the same developmental time point are not greater than variations across time points within the same species. In this study we were interested whether this additional layer of inter-species expression variation can be harnessed in the reconstruction of gene regulatory networks.... To quantitatively compare different methods across different gold standard networks we considered the area under the recall–precision curve (AUC) and the precision at 10% recall (PREC10) as performance measures and converted them to P -values by comparison to AUCs and PREC10s of networks generated by randomly assigning ranks to all possible edges in the corresponding gold standard network (cf. Methods and Figure fig:rec-prec-aggr for the recall vs. precision curves). While the AUC assesses the overall performance of a predicted network, PREC10 measures the quality of the top-ranked predictions, a property that may be of greater practical relevance. This analysis showed that no predicted network performs best for either measure across all gold standards (Figure fig:scorea-f). The single-species virilis networks performed best for 5 out of 12 AUC and PREC10 scores, albeit not for the ChIP-seq network measured in its own species. This overall good performance is consistent with virilis having the highest number of measured time points in the data (Supplementary Table tab:data). D. melanogaster also had more data points available than the other four species, but its time series were less complete (Supplementary Table tab:data). Among the integrative methods, the centroid and union methods both performed best for 5 out of 12 AUC and PREC10 scores (Figure fig:scorea-f). Both also had higher average AUC score than the best single-species network, but only the centroid method had higher average PREC10 score than the best single-species network (Figure fig:scoreg). The most important result however is the fact that the single-species network for the species were the gold standard network was measured never has the highest single-species AUC and only twice has the highest PREC10. In contrast, the centroid method always performs as good, and in most cases better, than the single-species network for the reference species (Figure fig:scorea-f). We conclude that the centroid method is the most robust network integration method achieving consistently high AUC and PREC10 scores, at least on this dataset.... Embryonic developmental time-course expression data in 6 Drosophila species (D. melanogaster (“amel”), D. ananassae (“ana”), D. persimilis (“per”), D. pseudoobscura (“pse”), D. simulans (“sim”) and D. virilis (“vir”)) was obtained from (ArrayExpress accession code E-MTAB-404). The data consists of 10 (amel), 13 (vir) or 9 (ana, per, pse, sim) developmental time points with several replicates per time point resulting in a total of 56 (amel), 36 (vir) or 27 (ana, per, pse, sim) arrays per species (Supplementary Table tab:data). The downloaded data was processed by averaging absolute expression levels over all reporters for a gene followed by taking the log 2 transform.... a. Number of interactions found in one to six species in the inferred gene regulatory networks at 10% recall level (red dots) and in 100 randomized networks with the same in- and out-degree distribution as the inferred networks (boxplots). b. Percentage of all predicted interactions (yellow) and of all true positive predictions (blue) in one to six species c. Precision of interactions found in one to six species. d. Recall of ChIP-seq gold standard interactions conserved in one to three species (green; data for BCD, KR, HB) and one to four species (red; data for TWI). e. Phylogenetic tree between six Drosophila species reconstructed from the inferred interactions at 10% recall level, with the total number of interactions in each species shown in brackets. The tree correctly splits the species in 3 groups – melanogaster (top), obscura (middle), virilis (bottom). Each branch, (numbered 1–9) represents a inferred network state transition. At each network state transition, the number of interactions inferred to be gained (red) or lost (blue) as well as the bootstrap value for each branch (in brackets) is indicated.... Although the gold standard network reconstructed from ChIP-chip data was in D. melanogaster, perhaps surprisingly the D. melanogaster predicted network did not perform better overall than the networks predicted for the other species (Figure fig:sammonb). To get confidence in this observation, we downloaded ChIP-sequencing data for three TFs (BCD, KR, HB) in three Drosophila species (melanogaster, pseudoobscura and virilis) and one TF (TWI) in four species (melanogaster, simulans, ananassae and pseudoobscura) , and created ChIP-seq gold standard networks for five species (cf. Methods). The recall-precision curves generated from the D. melanogaster ChIP-seq gold standard network (Supplementary Figure fig:rec-prec-singleb) were in good agreement with the ChIP-chip data, demonstrating again that the D. melanogaster predicted network performed no better than other Drosophila species. We also calculated recall-precision curves using the D. ananassae, D. pseudobscura, D. simulans and D. virilis ChIP-seq gold standard networks. Again, the regulatory network in that species did not perform better compared to the other species (Supplementary Figure fig:rec-prec-singlec–f).... Performance scores with respect to the gold standard ChIP-chip network for 14 TFs in D. melanogaster (a) and the ChIP-seq networks for D. melanogaster (b, 4 TFs), D. ananassae (c, 1 TF), D. pseudoobscura (d, 4 TFs), D. simulans (e, 1 TF), D. virilis (f, 4 TFs), and their averages over all gold standard networks (g). In each panel, the left, resp. right, figure shows - log 10 P A U C , resp. - log 10 P P R E C 10 for the six single-species predicted networks (green) and the five prediction aggregation methods (red). The dashed lines indicate the performance level of the single-species network for the gold standard species (a–f) or of the best performing single-species network (g). Values with a ∗ in panel a indicate numerical underflow values truncated to the smallest non-zero P -value ( 10 -324 ).... Recall vs. precision curves for predicted regulatory networks for five multi-species meta-analysis methods. The gold standard networks were the ChIP-chip network for 14 TFs in D. melanogaster (a) and the ChIP-seq networks for D. melanogaster (b, 4 TFs), D. ananassae (c, 1 TF), D. pseudoobscura (d, 4 TFs), D. simulans (e, 1 TF) and D. virilis (f, 4 TFs). The numbers in each legend are the area under the curve for each method.... Recall vs. precision curves for predicted regulatory networks in six Drosophila species. The gold standard networks were the ChIP-chip network for 14 TFs in D. melanogaster (a) and the ChIP-seq networks for D. melanogaster (b, 4 TFs), D. ananassae (c, 1 TF), D. pseudoobscura (d, 4 TFs), D. simulans (e, 1 TF) and D. virilis (f, 4 TFs). In panel a, the numbers in the legend are the area under the curve for each species. In panel b–f, the curve for the reference species is in red while the other species are in black.
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