Dataset Information

Effect of mago nashi depletion on gene expression in Drosophila S2R+ cells

ABSTRACT: This study was designed to identify changes in gene expression resulting from depletion of Mago nashi (Mago), a core subunit of the exon junction complex. Drosophila S2R+ cells were treated with double-stranded RNA targeting either LacZ or Mago for 6 days. Poly(A)+ RNA was purified from each sample and sequenced using 54 bp reads on an Illumina Genome Analyzer II. Fold changes in expression were calculated for each gene as the ratio of the reads per kilobase per million reads (RPKM) for Mago relative to LacZ. In other experiments, we have shown that Mago is required for correct splicing of the MAP kinase gene and its depletion causes a large reduction in MAP kinase mRNA levels. MAP kinase is a large gene in heterochromatin. In this study, we find that heterochromatic genes are disproportionately down-regulated in Mago-depleted cells, and those with large introns are particularly likely to be affected. SRA accession number: SRP003001.1 Sequencing of poly(A)+ RNA from S2R+ cells treated with either lacZ (control) or mago (experimental) dsRNA

ORGANISM(S): Drosophila melanogaster

SUBMITTER: Jessica E Treisman Stuart Brown Zuojian Tang Jean-Yves Roignant

PROVIDER: E-GEOD-23997 | ArrayExpress | 2010-10-20

SECONDARY ACCESSION(S): GSE23997SRP003001PRJNA130291

REPOSITORIES: GEO, ArrayExpress, ENA

ACCESS DATA

Publications

Exon junction complex subunits are required to splice Drosophila MAP kinase, a large heterochromatic gene.

Roignant Jean-Yves JY Treisman Jessica E JE

Cell 20101001 2

The exon junction complex (EJC) is assembled on spliced mRNAs upstream of exon-exon junctions and can regulate their subsequent translation, localization, or degradation. We isolated mutations in Drosophila mago nashi (mago), which encodes a core EJC subunit, based on their unexpectedly specific effects on photoreceptor differentiation. Loss of Mago prevents epidermal growth factor receptor signaling, due to a large reduction in MAPK mRNA levels. MAPK expression also requires the EJC subunits Y1 ...[more]

PMID: 20946982

Similar Datasets

Project description:In order to study the effect of transcription factor knockdown, we selectively depleted mRNA products from 483 different genes that are known or predicted to encode transcription factors. We treated Drosophila S2R+ tissue culture cells with double strand RNAs designed to be specific for these loci. Following RNAi treatment, we isolated poly A+ RNA from the cells, and performed stranded high-throughput RNA-Seq analyses to determine knockdown efficiency and propagating transcriptional consequences. Overall design: We started with a curated list of transcription factors and related proteins compiled for production of a reagent library at the DRSC (http://www.flyrnai.org/supplement/TranscriptionFactorGenes.xls). We ranked genes on this list as follows - Rank 1: experimental evidence of TF activity and DNA binding, Rank 2: experimental evidence of TF activity and predicted DNA binding, Rank 3: predicted/unknown TF activity and experimental evidence of DNA binding, Rank 4: predicted/unknown TF activity and/or predicted DNA binding, Rank 5: experimental evidence of TF cofactor, Rank 6: predicted TF cofactor, Rank 7: chromatin regulation, Rank 8: little or indirect annotation, Rank 9: no evidence for any TF activity. We then excluded genes with a rank of 8 or 9. We additionally restricted the list to the subset of 483 genes with expression levels higher than signal from intergenic regions in an Drosophila S2R+ RNA-Seq study (Lee et al., 2014. PMID: 25262759). We generated a panel of double strand RNA (dsRNA) for knockdown reagents (Ramadan et al., 2007. PMID: 17853882). For 387 loci we used two different dsRNA reagents, which target different regions of the mRNAs. Only one dsRNA reagent was used for the remaining 96 loci. As a control for general effects of dsRNA treament, we used dsRNA against the E. coli LacZ gene as a sham. We performed RNAi treatments and library preparations in 96 well format, and we placed one LacZ control in each plate. On each plate, there were also wells that we used to estimate dsRNA uptake after depletion of Death-associated inhibitor of apoptosis 1 (Diap-1, or thread. Flybase ID: FBgn0260635) and ensured that cells underwent cell death. RNA-Seq libraries from wells with such high proportions of dead cells were not informative and are not part of this submission. We performed all dsRNA treatments in biological duplicate. We performed RNA-sequencing on Illumina platform after polyA+ selection of mRNA. We prepared libraries in strand-specific manner, using the Uracil-DNA glycosylase method (Parkhomchuk et al., 2009. PMID: 19620212). RNA-Seq libraries were sequenced to generate single-end, 50 bp reads.

Project description:Osteogenesis is a highly regulated developmental process and continues during the turnover and repair of mature bone. Runx2, the master regulator of osteoblastogenesis, directs a transcription program essential for bone formation through both genetic and epigenetic mechanisms. While individual Runx2 gene targets have been identified, further insights into the broad spectrum of Runx2 functions required for osteogenesis are needed. By performing genome-wide characterization of Runx2 binding at the three major stages of osteoblast differentiation: proliferation, matrix deposition and mineralization, we identified Runx2-dependent regulatory networks driving bone formation. Using chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) over the course of these stages, we discovered close to 80,000 significantly enriched regions of Runx2 binding throughout the mouse genome. These binding events exhibited distinct patterns during osteogenesis, and were associated with proximal promoters as well as a large percentage of Runx2 occupancy in non-promoter regions: upstream, introns, exons, transcription termination site (TTS) regions, and intergenic regions. These peaks were partitioned into clusters that are associated with genes in complex biological processes that support bone formation. Using Affymetrix expression profiling of differentiating osteoblasts depleted of Runx2, we identified novel Runx2 targets including Ezh2, a critical epigenetic regulator; Crabp2, a retinoic acid signaling component; Adamts4 and Tnfrsf19, two remodelers of extracellular matrix. We demonstrated by luciferase assays that these novel biological targets are regulated by Runx2 occupancy at non-promoter regions. Our data establish that Runx2 interactions with chromatin across the genome reveal novel genes, pathways and transcriptional mechanisms that contribute to the regulation of osteoblastogenesis. To identiy the genome-wide occupancy of Runx2, DNA bound by Runx2 at the prolieration, matrix deposition, and mineralization stages were recovered by Runx2 ChIP. Libraries of purified DNA were generated using Illumina SR adapters (Illumina) following manufacturer’s manual, and were selected for the inserted fragments of 200 ± 50 bp, and sequenced 36 bases on an Illumina Genome Analyzer II. Base calls and sequence reads were generated by Illumina CASAVA software (version 1.6, Illumina). Two independent biological repeats of Runx2 ChIP-Seq libraries were prepared for each time point, and two input libraries were prepared with sonicated DNA from day 9 MC3T3-E1 cells. We pooled the reads from two biological replicates for peaking calling using MACS (version 1.4.1) with a stringent p value threshold (p < 1e-10) in contrast to input control, and used these peaks for further bioinformatic analyses. Each sample deposited here contains three files: the sequence file with short reads combined from two biological replicates, a Bed file with peaks called from the pooled short reads, and a Wig file with peak signals.