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355 results for “RNA modifications”
xPore: Identification of differential RNA modifications from nanopore direct RNA sequencing
<p>xPore is a Python package for identification and quantification of differential RNA modifications from direct RNA sequencing.</p> <p>The detailed usage is documented at <a href="https://xpore.readthedocs.io/en/latest/">https://xpore.readthedocs.io/en/latest</a>, while all scripts and source code are available at <a href="https://github.com/GoekeLab/xpore">https://github.com/GoekeLab/xpore</a>.</p> <p>All the preprocessed datasets used in the paper are provided here. </p> <p>Please cite our paper below when using these data.<br> Ploy N. Pratanwanich et al. "Detection of differential RNA modifications from direct RNA sequencing of human cell lines." bioRxiv (2020).</p>
xPore: Identification of differential RNA modifications from nanopore direct RNA sequencing - SGNEx data
<p>xPore is a Python package for identification and quantification of differential RNA modifications from direct RNA sequencing.</p> <p>The detailed usage is documented at <a href="https://xpore.readthedocs.io/en/latest/">https://xpore.readthedocs.io/en/latest</a>, while all scripts and source code are available at <a href="https://github.com/GoekeLab/xpore">https://github.com/GoekeLab/xpore</a>.</p> <p>All the preprocessed datasets used in the paper are provided here. </p> <p>Please cite our paper below when using these data.<br> Ploy N. Pratanwanich et al. "Detection of differential RNA modifications from direct RNA sequencing of human cell lines." bioRxiv (2020).</p>
Sequencing data of RNA editing, RNA modifications, and transcriptional units in Listeria monocytogenes
<p>Sequencing data for "RNA editing, RNA modifications, and transcriptional units in <em>Listeria monocytogenes</em>" manuscript, which is submitted to BMC genomics.</p>
RNA modification 5-methylcytosine (m5C) is associated with small RNA biogenesis in Arabidopsis thaliana
<p><strong>Small RNAs (sRNAs) are essential in regulating the development in plants and animals. While the biogenesis pathways of many sRNAs is clear, the biogenesis pathway for novel small RNAs like tRNA- and rRNA-derived fragments (tRFs and rRFs) is less so. Many diverse cellular RNAs including mRNAs, long-non-coding RNAs, tRNAs and rRNAs in plants have covalent post-transcriptional modifications and their function is only starting to be elucidated. Here, we determine if the RNA modification 5-methylcytosine (m<sup>5</sup>C) plays a role in sRNA biogenesis in <em>Arabidopsis thaliana</em>. To this effect, we Illumina-sequenced sRNAs from wild type and m5C methyltransferase mutant <em>tRNA methyltransferase 4b </em>(<em>trm4b</em>). Our bioinformatics analysis identified 158 sRNAs loci that increased in abundance and two sRNA loci that decreased in abundance in the <em>trm4b</em> compared to the wild type control. Comparison with RNA bisulphite sequencing data confirmed that most of the top differentially abundant sRNAs have m<sup>5</sup>C sites. In summary, our results suggest that m<sup>5</sup>C RNA modifications is associated with sRNA biogenesis in <em>Arabidopsis thaliana</em>.</strong></p>
De novo nanopore sequencing overrepresents RNA modification landscape
<p>RNA modifications are critical to the functional diversity and regulatory complexity of the transcriptome. With increasing frequency, direct nanopore RNA sequencing is applied to identify RNA modifications de novo. Here, we directly compare the MS2 phage genome RNA modification profiles determined using nanopore to orthogonal LC-MS/MS assays. The results reveal very different views of the modification landscape, suggesting caution when calling new RNA modifications using nanopore alone.</p>
RNA modification detection using direct RNA sequencing and nanoDoc2
<p><strong>The core of nanoDoc2 includes a machine-learning algorithm in which a 6-mer segmented raw current signal is compared by Deep-One-Class classification using a Wavenet-based neural network. As an output, an RNA modification is detected by a statistical score in each candidate position. Herein, we describe the detailed instructions on how to use nanoDoc2 for signal segmentation, train/test the neural network and finally predict RNA modifications present in nanopore direct RNA sequence data.</strong></p>
Molecular dynamics simulations of RNA Pol I closed complex in WT and with modifications to DNA base pairs -27 and -28
<p><span>The starting structure for the modelling was cryo-EM based structure of <em>S. cerevisiae</em> pre-initiation complex, showing Pol I, RRN3 and CF bound on a rDNA promoter at 2.90 Å resolution. This structure (‘RNA Polymerase I closed conformation 2’; accession code: 6RQL) was downloaded from the PDB database and prepared using the Protein Preparation Workflow of Maestro with default settings. This included filling in missing sidechains, optimizing hydrogen bonds and protonation using PROPKA at pH 7.4, deleting water molecules >5Å from the heteroatoms and a short energy minimization using OPLS4 force field</span><span>. The initial structures for the complexes with DNA mutations were constructed from this pre-processed structure by manually mutating the base pairs at position -28 or -27 of the rDNA promoter from C</span><span>·</span><span>G to A</span><span>·</span><span>T (</span><span>tDNA·ntDNA)</span><span> and from A</span><span>·</span><span>T to C</span><span>·</span><span>G, respectively. </span><span></span><span>MD simulations (3*80 ns/system) were conducted with Desmond using default parameters from Schrödinger Suite version 2024-1 on the CSC (IT Center for Science, Finland) supercomputer Puhti. </span></p>
HG002 DNA (PacBio and ONT) and UHRR RNA (ONT) base modification data for minimod
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PCB126 exposure revealed alterations in m6A RNA modifications in transcripts associated with AHR activation
<p>Chemical modifications of proteins, DNA and RNA moieties play critical roles in regulating gene expression. Emerging evidence suggests the RNA modifications (epitranscriptomics) have substantive roles in basic biological processes. One of the most common modifications in mRNA and noncoding RNAs is <i>N</i><sup>6</sup>-methyladenosine (m6A). In a subset of mRNAs, m<sup>6</sup>A sites are preferentially enriched near stop codons, in 3′ UTRs, and within exons, suggesting an important role in the regulation of mRNA processing and function including alternative splicing and gene expression. Very little is known about the effect of environmental chemical exposure on m6A modifications. As many of the commonly occurring environmental contaminants alter gene expression profiles and have detrimental effects on physiological processes, it is important to understand the effects of exposure on this important layer of gene regulation. Hence, the objective of this study was to characterize the acute effects of developmental exposure to PCB126, an environmentally relevant dioxin-like PCB, on m6A methylation patterns. We exposed zebrafish embryos to PCB126 for 6 hours starting from 72 hours post-fertilization and profiled m6A RNA using methylated RNA immunoprecipitation followed by sequencing (MeRIP-seq). Our analysis revealed 117 and 217 m6A peaks in the DMSO and PCB126 samples (FDR 5%), respectively. The majority of the peaks were preferentially located around the 3'UTR and stop codons. Statistical analysis revealed 15 m6A marked transcripts to be differentially methylated by PCB126 exposure. These include transcripts that are known to be activated by AHR agonists (e.g., <i>ahrra</i>, <i>tiparp</i>, <i>nfe2l2b) as well as others that are important for normal development (vgf, cebpd, sned1). These results suggest that</i> environmental chemicals such as dioxin-like PCBs could affect developmental gene expression patterns by altering m6A levels. Further studies are necessary to understand the functional consequences of exposure-associated alterations in m6A levels.</p>
Oxford Nanopore Direct RNA Sequencing datasets for detecting rRNA modifications in the Brassica oleracea mitoribosome
<p>Oxford Nanopore Direct RNA Sequencing (DRS) was applied for the detection of rRNA modifications in the <em>Brassica oleracea</em> mitoribosome. A comparison between native rRNA transcripts and in vitro transcribed (IVT) rRNA transcripts that were devoid of any modification indicated systematic base-calling errors and/or variations in current intensities that led to the prediction of the modified nucleotides (Begik et al., 2018).</p> <p>For Nanopore (DRS) library preparation, custom reverse transcription adapters (RTAs) containing Deeplexicon multiplexing barcodes (BC1, BC2 or BC3) were designed for sequence-specific ligation to the 3’-ends of <em>B. oleracea</em> mitochondrial rRNAs.</p> <p>Basecalling and demultiplexing of ONT direct RNA sequencing data were performed by Guppy and Deeplexicon, respectively.</p> <p>For the analysis and visualization of current intensities, a full description is available in the associated publication.</p> <p>The <strong>Eventalign_18S.R</strong> Rscript was used to make the nanopore <strong>18S </strong>signal analysis</p> <p>The <strong>Eventalign_26S.R</strong> Rscript was used to make the nanopore <strong>26S </strong>signal analysis</p> <p>The raw data for the scripts are in the following folders:</p> <p>- For 26S: 26S_Native.barcode01 and 26S_IVT.barcode03<br>- For 18S: 18S_Native.barcode01 and 18S_IVT.barcode02</p> <p>These folders contain the read alignment files output from minimap2 (in .bam format) and the eventalign files generated by the f5c software (in tsv format).</p> <p>The FASTA folder contains the mitochondrial 18S and 26S rRNA gene reference sequence in fasta format</p>
Roles of m5C RNA modification patterns in biochemical recurrence and tumor microenvironment characterization of prostate cancer
<p>The datasets included in the manuscript 'Roles of m5C RNA modification patterns in biochemical recurrence and tumor microenvironment characterization of prostate cancer'</p>
RNA-seq Data for Bacteroides fragilis Toxin Suppresses METTL3-Mediated m6A Modification in Macrophage to Promote Inflammatory Bowel Disease
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De novo nanopore sequencing overrepresents RNA modification landscape, part 2
<p>RNA modifications are critical to the functional diversity and regulatory complexity of the transcriptome. With increasing frequency, direct nanopore RNA sequencing is applied to identify RNA modifications de novo. Here, we directly compare the MS2 phage genome RNA modification profiles determined using nanopore to orthogonal LC-MS/MS assays. The results reveal very different views of the modification landscape, suggesting caution when calling new RNA modifications using nanopore alone.</p>
De novo nanopore sequencing overrepresents RNA modification landscape, part 3
<p>RNA modifications are critical to the functional diversity and regulatory complexity of the transcriptome. With increasing frequency, direct nanopore RNA sequencing is applied to identify RNA modifications de novo. Here, we directly compare the MS2 phage genome RNA modification profiles determined using nanopore to orthogonal LC-MS/MS assays. The results reveal very different views of the modification landscape, suggesting caution when calling new RNA modifications using nanopore alone.</p>
PCB126 exposure revealed alterations in m6A RNA modifications in transcripts associated with AHR activation
Open the record for dataset details and reuse information.
RNA modification detection using direct RNA sequencing and nanoDoc2_2
<p>RNA modification detection using direct RNA sequencing and nanoDoc2_2</p>
FUS modulates the level of ribosomal RNA modifications by regulating a subset of snoRNA expression [HydraPsiSeq]
GEO Series GSE202524. Homo sapiens. 20 samples. Type: Other.
Mdm2 enhances stemness-promoting chromatin modifications through the Polycomb Repressor Complex 2 in a p53-Independent Manner [RNA-Seq]
GEO Series GSE73176. Mus musculus. 7 samples. Type: Expression profiling by high throughput sequencing.
5-methylcytosine modification profiling of messenger RNA in breast cancer brain metastasis
GEO Series GSE246721. Homo sapiens. 12 samples. Type: Other.
An Improved SNAP-ADAR Tool Enables Efficient RNA Base Editing to Interfere with Post-translational Protein Modification
GEO Series GSE264114. Homo sapiens. 26 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.