Nucleosome positioning study of Arabidopsis er/erl1/erl2 mutant using MNase-seq approach
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PROVIDER: PRJEB21571 | ENA |
REPOSITORIES: ENA
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Project description:We utilized MNase-seq to profile nucleosome positions in wild type (Ax2) and ChdC null cells both in growing cells and a partially developed state (loose-mound) to study changes in nucleosome positioning and occupancy during development and the impact the deletion of ChdC an ATP-dependent chromatin remodeller has on nucleosome positioning and occupancy. As a control for MNase sequence bias we also digested naked DNA with MNase.
2017-02-26 | GSE70122 | GEO
Project description:The members of ERECTA family (ERf) leucine-rich receptor like kinases (ERECTA, ERECTA-LIKE1, ERECTA-LIKE2) are involved in various developmental processes and hormonal regulation. In this experiment we showed that inactivation of all three ER's causes wide range of transcriptional changes affecting developmental, hormonal and metabolic processes. Based on our genome-wide nucleosome occupancy and positioning data and other experiments we concluded that ERf's kinases are involved in chromatin organization through modulation their plasticity. This work was supported by the National Science Centre (Poland) Grants UMO-2011/01/B/NZ1/00053 to T.J.S.
2023-04-01 | E-MTAB-5830 | biostudies-arrayexpress
Project description:MNase-Seq and ChIP-Seq have evolved as popular techniques to study chromatin and histone modification. Although many tools have been developed to identify enriched regions, software tools for nucleosome positioning are still limited. We introduce a flexible and powerful open-source R package, PING 2.0, for nucleosome positioning using MNase-Seq data or MNase- or sonicated- ChIP-Seq data combined with either single-end or paired-end sequencing. PING uses a model-based approach, which enables nucleosome predictions even in the presence of low read counts. We illustrate PING using two paired-end datasets from Saccharomyces cerevisiae and compare its performance to nucleR and ChIPseqR.
2013-07-11 | GSE47073 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE40910: Genome-wide nucleosome positioning during embryonic stem cell development [MNase-Seq] GSE40948: Genome-wide nucleosome positioning during embryonic stem cell development [RNA-Seq] GSE40951: Genome-wide nucleosome positioning during embryonic stem cell development [ChIP-Seq] Refer to individual Series
2012-10-21 | E-GEOD-40896 | biostudies-arrayexpress
Project description:Purpose: The goal of this study is to evaluate potentially direct targets of altered chromatin remodeller SWI/SNF on nucleosome positioning at gene promoters by means of MNase-sequencing from synchronised L1-staged swsn‑1 single mutant, swsn‑1; snfc‑5 double mutants, swsn‑1; snfc‑5; ubr‑5 triple mutants compared to wild-type animals to achieve genome-wide nucleosome coverage profiles. Methods: In vivo MNAse-seq profiles of WT (N2), swsn-1-/- (MH2354, SX3714), swsn-1-/-; snfc-5-/- (SX3622, SX3715), swsn-1-/-; snfc-5-/-; ubr-5-/- (SX3627) C. elegans L1s were generated by deep sequencing, in duplicate, using Illumina NextSeq 2000. The sequence reads that passed quality filters were mapped to C. elegans (ce11) genome using bowtie2 aligner v.2.2.9. The resulting bam files were converted to bigwig tracks using deeptools bamCoverage. Results: Using an optimized data analysis workflow, we mapped about 50 million sequence reads per sample to the C elegans genome (build ce11). MNase-Seq data was further analysed locus-by-locus for nucleosome positioning around transcription start site of ubiquitous genes in the mutants relative to wild-type coverage. Swsn-1 single mutants showed strongly reduced +1 nucleosome coverage in compare to the wild-type animals. The +1-nucleosome coverage in both the swsn-1; snfc-5 double and swsn-1; snfc-5; ubr-5 triple suppressor mutants was higher than in swsn-1 single mutants. We also established that the subsets of ubiquitously up and downregulated SWI/SNF-dependent genes have a higher nucleosome coverage in wild-type animals when compared to all ubiquitous genes in wild-type animals.
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2010-05-29 | E-GEOD-21821 | biostudies-arrayexpress
Project description:MNase-Seq and ChIP-Seq have evolved as popular techniques to study chromatin and histone modification. Although many tools have been developed to identify enriched regions, software tools for nucleosome positioning are still limited. We introduce a flexible and powerful open-source R package, PING 2.0, for nucleosome positioning using MNase-Seq data or MNase- or sonicated- ChIP-Seq data combined with either single-end or paired-end sequencing. PING uses a model-based approach, which enables nucleosome predictions even in the presence of low read counts. We illustrate PING using two paired-end datasets from Saccharomyces cerevisiae and compare its performance to nucleR and ChIPseqR. Identification of nucleosomes from two different mononucleosomes data. A yeast strain (W303 background) with the HTZ1 gene expressed a fusion with a myc epitope was used to map total and Htz1-containign nucleosome by MNase-ChIP-Seq. Cells were grown to mid-log phase and monomucleosomes were generated using MNase treatment of isolated nuclei. Especially for the sample of SC0017_61YDGAAXX_8_TCATTC, the Htz1-containing nucleosomes were enriched by immunoprecipitation using an anti-Myc antibody (3E10). DNA from both total nucleosomes and Htz1-enriched nucleosomes were purified and sequenced on an Illumina GA IIx using the by paired-end protocol.
2013-07-11 | E-GEOD-47073 | biostudies-arrayexpress
Project description:E-ChRPs: Engineered Chromatin Remodeling Proteins for Precise Nucleosome Positioning [MNase-Seq]
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Project description:Genome-wide maps of nucleosome positioning in mouse ES cells with control shRNA and on Smarcad1 KD. MNase-seq data for human colo829 cells are also included.
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Project description:We have employed MNase-Seq technology to determine the nucleosome positioning across the Ly49-expressing RMA cell line. This information was compared to the default nucleosome landscape of these cells as predicted by NuPop computations to identify transcription factor binding site regions that significantly deviate from our predictions, potentially indicating an interfering role for nucleosome binding at these sites. We report that expressed Ly49 genes significantly deviate in their nucleosome coverage at AML-1a sites when compared to other, non-expressed Ly49 genes within the same sample. This information has implications for our understanding of NK cell biology, and also presents the Ly49 family as a convenient model system for discovering how various genetic and epigenetic elements impact expression state, since Ly49 genes are stochastically expressed within a given population, but have similar transcription factor requirements. It is our hope that other work on the epigenetic control of gene expression can benefit from this model system.
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