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Dataset results
123 results for “mRNA processing”
Arabidopsis thaliana circadian mRNA-seq gene expression processed tables from Romanowski et al., TPJ 2020.
<p>This dataset is an add-on for Romanowski et al., TPJ 2020 (https://doi.org/10.1111/tpj.14776) containing processed files for the circadian RNAseq data in tab delimited txt format.</p> <p><br> Here, you can the raw counts file, the normalized CPM values, and the full JTK result (without recalculated circadian phases, just the original ones). All genes with a read density > 0.05 in at least one timepoint were considered expressed. The read density is calculated as the amount of reads divided by the effective length of a gene (total reads / length). Genes rd file is also included.</p> <p>Some useful notes:<br> 1) Counts were assigned using ASpli and the AtRTDv2 annotation (34,212 genes).<br> 2) After filtering by rd we had a total of 18,503 expressed genes.<br> 3) 13,256 genes passed the QL F-tests.<br> 4) 9,127 genes were rhythmic according to JTK_cycle. </p> <p>For detailed protocols, please see Romanowski et al., TPJ 2020 (https://doi.org/10.1111/tpj.14776)</p> <p>The RNA-seq raw data supporting the conclusions of this article have been deposited in ArrayExpress (Kolesnikov et al., 2015) at EMBL-EBI (www.ebi.ac.uk/arrayexpress), under accession numbers E-MTAB-7933.</p> <p>All relevant custom r scripts are available at https://github.com/aromanowski/Circadian_rhythms_and_alternative_splicing</p>
Regulation of mature mRNA levels by RNA processing efficiency
<p>Data from the research paper "Regulation of mature mRNA levels by RNA processing efficiency" by Henfrey, C., Murphy, S., and Tellier, M.:</p> <p>-Highest expressed transcript annotation for protein-coding genes, gencode v38.</p> <p>-15 txt (BED) files for chromatin vs nucleoplasm enrichment gene sets: HeLa full gene sets, canonical protein only sets, chromatin RNA seq subsamples, mNET seq subsamples, Raji gene sets.</p> <p>-Proteomics data table</p> <p>-mRNA half-life table</p> <p>-Splicing efficiency for POINT-seq, ChrRNA-seq, NucRNA-seq table</p> <p>-Ser2-P mNET-seq readthrough index data table</p> <p>-Splicing efficiency for siLuc/siEX3 table (ChrRNA-seq, NucRNA-seq)</p> <p>-RMATs output tables for alternative splicing results (siEX3 vs siLuc)</p> <p>-Tables for TSS:TES quantifications (mNET-seq(CTD) vs log2FoldChange, chr/nuc/mnet siEX3 vs siLuc)</p>
Effect of shade and nitrogen content on Arabidopsis Col-0 and cytokinin mutants abcg14 and cypDM mRNA-seq gene expression processed tables.
<p>This dataset is an add-on for Gautrat et al., containing processed files for the mRNAseq data in tab delimited txt format.</p> <p>Here, you can obtain the raw counts file, the normalized CPM values, and the normalized logCPM values</p> <p>The RNA-seq raw data supporting the conclusions of this article have been deposited in ArrayExpress (Kolesnikov et al., 2015) at EMBL-EBI (www.ebi.ac.uk/arrayexpress), under accession numbers E-MTAB-13638.</p> <p>All relevant custom r scripts are available at https://github.com/aromanowski/shade_N_ck</p>
Datasets and Scripts: Full-length mRNA sequencing uncovers a widespread coupling between transcription and mRNA processing
<p>The multilayered control of gene expression requires tight coordination of regulatory mechanisms at the transcriptional and post-transcriptional level. In this study, we studied the interdependence of transcription, splicing and polyadenylation events on single mRNA molecules by full-length mRNA sequencing. In MCF-7 breast cancer cells and three human tissues, we found an unforeseen number of genes that demonstrate mutually inclusive or exclusive alternative transcription and mRNA processing events, which can span the entire length of mRNA molecules. Furthermore, alternative poly(A) sites that are coupled with alternative splicing events are depleted for known poly(A) signals and enriched for MBNL binding motifs, supporting a dual role of MBNL proteins in regulating splicing and polyadenylation. We predict thousands of open-reading frames from the sequence of full-length mRNAs, allowing for a more sensitive proteogenomics analysis of MCF-7 mass-spectrometry data. Our findings demonstrate that our understanding of transcriptome complexity is far from complete and provides a framework to reveal largely unresolved mechanisms that coordinate transcription and mRNA processing.</p>
Mature mRNA processing that deletes 3′ end sequences directs translational activation and embryonic development
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Processed data for Jowhar et al, "A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X"
<p>Processed data for Jowhar et al, "A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X".</p> <p>It contains the data objects to reproduce all figures of the paper.</p> <p>More info here: <strong><a href="https://github.com/calviellolab/DDX3X_GC_paper">https://github.com/calviellolab/DDX3X_GC_paper</a></strong></p>
Data from: Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast
Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.
Data from: Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast
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Elevated pre-mRNA 3' end processing activity in cancer cells renders vulnerability to inhibition of cleavage and polyadenylation [ChrRNA-seq]
GEO Series GSE218545. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
Overlapping and distinct functions of CstF64 and CstF64τ in mammalian mRNA 3’ processing
GEO Series GSE51156. Homo sapiens; synthetic construct. 5 samples. Type: Expression profiling by high throughput sequencing; Other.
The anti-cancer compound JTE-607 reveals hidden sequence specificity of the mRNA 3' processing machinery
GEO Series GSE218977. synthetic construct; Homo sapiens. 18 samples. Type: Other.
Uncovering human DCP1 is essential for mRNA decapping process and paralog-specific functions in gene regulation
GEO Series GSE230847. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
A histone H3.3 Lysine 36 Trimethylation Reader Connects Chromatin to Regulated Pre-mRNA Processing
GEO Series GSE51672. Homo sapiens. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Ultra-deep sequencing reveals pre-mRNA splicing as a sequence driven high-fidelity process
GEO Series GSE137883. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Cancer-associated snaR-A noncoding RNA interacts with core splicing machinery and disrupts processing of mRNA subpopulations II
GEO Series GSE286577. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Widespread Influence of 3′-end Structures on Mammalian mRNA Processing and Stability [CENPB-3'-end-KO]
GEO Series GSE95466. Homo sapiens. 2 samples. Type: Other; Expression profiling by high throughput sequencing.
Pathogenic CLP1 p.R140H mutation alters mRNA processing in human motor neurons (PAC-seq)
GEO Series GSE183869. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing.
Widespread Influence of 3′-end Structures on Mammalian mRNA Processing and Stability [CENPB-3'-end-library]
GEO Series GSE93424. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
Genome‐wide analysis of pre‐mRNA 3' end processing reveals a decisive role of human cleavage factor I in the regulation of 3' UTR length: A-seq
GEO Series GSE37037. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
Delayed processing of blood samples may impair the accuracy of mRNA-based biomarkers
GEO Series GSE192530. Bos taurus. 30 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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.