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46 results for “protein isoform”
Enhanced Protein Isoform Characterization Through Long-Read Proteogenomics - Workflow Results
<pre> </pre> <p>The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g. PacBio, Oxford Nanopore) provides full-length transcript sequencing, which can be used to predict full-length proteins. Here, we describe a long-read proteogenomics approach for integrating matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data in protein inference to enable detection of protein isoforms that are intractable to MS detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis.</p> <p>Companion Repositories:</p> <ol> <li><a href="https://doi.org/10.5281/zenodo.5920817">Long-Read-Proteogenomics Workflow GitHub Repository Release</a></li> <li><a href="https://doi.org/10.5281/zenodo.5920847">Long-Read-Proteogenomics Analysis GitHub Repository Release</a></li> </ol> <p>Companion Datasets</p> <ol> <li><a href="https://zenodo.org/deposit/5703754">Long-Read-Proteogenomics Workflow Sample and Reference Data</a></li> <li><a href="https://doi.org/10.5281/zenodo.5234651">TEST Data for Long-Read-Proteogenomics Workflow GitHub Actions</a></li> </ol> <p>This Repository contains the complete output from the execution of the <a href="https://doi.org/10.5281/zenodo.5920817">Long-Read-Proteogenomics Workflow</a>, using the input from <a href="https://zenodo.org/deposit/5703754">Jurkat Samples and Reference Data</a>. </p> <p>The file <em>jurkat.flnc.bam </em>was 6.5 GB had to be split into 13 separate files and for use should be rejoined -- here are the steps that were used to split the file up. </p> <p>1. Convert <em>jurkat.flnc.bam</em> (binary format) to sam file (text format) without header: <em>samtools view jurkat.flnc.bam > jurkat.flnc.sam</em></p> <p>2. Capture the header: <em>samtools view -H jurkat.flnc.bam > jurkat.flnc.header.sam</em></p> <p>3. Split <em>jurkat.flnc.sam</em> into smaller files (aim to get final size under 2GB): <em>split -l 400000 jurkat.flnc.sam jurkat.flnc.chunk.</em></p> <p>4. Convert each of these files back to bam for uploading: <em>samtools view -b jurkat.flnc.chunk.a* -o jurkat.flnc.chunk.a*.bam (*=a,b,c,d,e,f,g,h,i,j,k,l,m)</em></p> <p>After downloading, reverse this process including using the header file which is found in the LRPG-Manuscript-Results-results-results-jurkat-isoseq3-companion-files.tar.gz file></p> <p>1. Convert the bam files back to sam files: <em>samtools view jurkat.flnc.chunk.a*.bam > jurkat.flnc.chunk.a*.sam (*=a,b,c,d,e,f,g,h,i,j,k,l,m)</em></p> <p>2. Combine the header together with the sam files: <em>cat jurkat.flnc.chunk.a*sam > jurkcat.flnc.sam (</em>verified the same number of lines of the sam files is identical to the number of lines of the original without header: 4,956,761. Header file is 13 lines.</p> <p>3. Convert to bam files if desired: <em>samtools view -b jurkat.flnc.sam -o jurkat.flnc.bam</em></p> <p>4. Rehead with the header file: <em>samtools reheader -P -i jurkat.flnc.header.sam jurkat.flnc.bam</em></p>
Underlying data for IsoAligner: dynamic mapping of amino acidpositions across protein isoforms
<p>The human isoform library (list_of_gene_objects_25th_july_final.txt) for the IsoAligner webtool is generated from these resources.</p>
Long read proteogenomics to characterize protein isoform diversity in human umbilical vein endothelial cells (HUVECs)
<p>Endothelial cells (ECs) comprise the lumenal lining of all blood vessels and are critical for the functioning of the cardiovascular system and their phenotypes can be modulated by protein isoforms. To characterize the isoform landscape within EC, we applied a long read proteogenomics approach to analyze human umbilical vein endothelial cells (HUVECs). Transcripts delineated from PacBio sequencing serve as the basis for a sample-specific protein database used for downstream MS analysis to infer protein isoform expression. We detected 53,836 transcript isoforms from 10,426 genes, with 22,195 of those transcripts being novel. Furthermore, the predominant isoform in HUVECs does not correspond with the accepted “reference isoform” 25% of the time, with vascular pathway-related genes among this group. We found 2,597 protein isoforms supported through unique peptides, with an additional 2,280 isoforms nominated upon incorporation of long-read transcript evidence. We characterized a novel alternative acceptor for endothelial-related gene <em>CDH5</em>, suggesting potential changes in its associated signaling pathways. Finally, we identified novel protein isoforms arising from a diversity of splicing mechanisms supported by uniquely mapped novel peptides. Our results represent a high resolution atlas of known and novel isoforms of potential relevance to endothelial phenotypes and function.</p>
TEST DATA for Enhanced protein isoform characterization through long-read proteogenomics
<p>Test data for The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g. PacBio, Oxford Nanopore) provides full-length transcript sequencing, which can be used to predict full-length proteins. Here, we describe a long-read proteogenomics approach for integrating matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data in protein inference to enable detection of protein isoforms that are intractable to MS detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis.</p> <p>Companion Repositories:</p> <ol> <li><a href="https://doi.org/10.5281/zenodo.5920817">Long-Read-Proteogenomics Workflow GitHub Repository Release</a></li> <li><a href="https://doi.org/10.5281/zenodo.5920847">Long-Read-Proteogenomics Analysis GitHub Repository Release</a></li> </ol> <p>Companion Datasets</p> <ol> <li><a href="https://zenodo.org/deposit/5703754">Jurkat Samples and Reference Data</a></li> <li><a href="http://10.5281/zenodo.5920920">Long-Read-Proteogenomics Workflow Results using Jurkat Sample data</a></li> </ol> <p>This Repository contains the test data, specifically:</p> <p><a href="https://doi.org/10.5281/zenodo.5234651">TEST Data for Long-Read-Proteogenomics Workflow GitHub Actions</a></p>
Dateset of in silico investigations on protein_protein Interaction of GST isoforms with ASK1 and JNK1
<p>Please refer to the description of the files document for details on the files in the zip folder.</p> <p>The dataset contains molecular dynamics simulation files, and other in silico investigation output files used to describe the protein-protein interactions of seven GST isoforms with that of MAPK8 (JNK1) and MAP3K5 (ASK1). </p>
Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity
<p>This Zenodo repository contains data used for running <a href="https://github.com/sheynkman-lab/biosurfer_analysis" target="_blank" rel="noopener">Biosurfer_analysis</a>, a tool to surf the biological network, from genome to transcriptome to proteome and back to gain insights into human disease biology.<br><br>Repository content:</p> <ol> <li><strong>biosurfer_gencode_toy_data.zip:</strong> is a small subset of the GENCODE version 38 files (GTF, transcript FASTA, and protein FASTA) for the purpose of trial run and testing Biosurfer scripts.<br><br></li> <li><strong>biosurfer_gencode_toy_output.zip: </strong>Biosurfer generated output files for the toy data. <br><br></li> <li><strong>biosurfer_gencode_v42_data.zip: </strong>contains GENCODE version 42 (basic) files (GTF, transcript FASTA, and protein FASTA).<br><br></li> <li><strong>biosurfer_gencode_v42_output.zip: </strong>Biosurfer generated output files for GENCODE 42 input files.<br><br></li> <li><strong>biosurfer_wtc11_data.zip: </strong>contains karyotypically normal human stem cell line data (WTC11) file (GTF, transcript FASTA, and protein FASTA).<br><strong><br></strong></li> <li><strong>biosurfer_wtc11_output.zip: </strong>Biosurfer generated output files for WTC11 files.<br><br></li> <li><strong>APPRIS analysis.zip: </strong>Intermediate files (CSV) detailing the APPRIS isoforms information utilized in the associated manuscript.</li> <li><strong>biosurfer_mouse.zip: </strong>contains GENCODE Mouse version M35 (basic) files (GTF, transcript FASTA, and protein FASTA).</li> <li><strong>biosurfer_mouse_output.zip: </strong>Biosurfer generated output files for GENCODE M35 input files.</li> </ol>
Isolation of Vitamin D Binding Protein Isoforms From Human Volunteers
ClinicalTrials.gov study NCT02258035. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Domain scanning results for a selected set of high-quality-annotation protein isoforms produced by human transcription factor genes
Open the record for dataset details and reuse information.
Data from: Strain specific differences in rates of Photosystem II repair in picocyanobacteria correlate to differences in FtsH protein levels and isoform expression patterns
Open the record for dataset details and reuse information.
Cell type specific profiling of alternative translation identifies novel protein isoforms in the mouse brain
GEO Series GSE115483. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
Allele-selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-coding and Noncoding RNAs, and RNA Isoforms
GEO Series GSE66135. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing; Genome variation profiling by high throughput sequencing.
Translation initiation site profiling reveals widespread synthesis of non-AUG-initiated protein isoforms in yeast
GEO Series GSE150375. Saccharomyces cerevisiae. 11 samples. Type: Expression profiling by high throughput sequencing.
Tunable protein synthesis by transcript isoforms in human cells (Transcript Isoforms in Polysomes sequencing: TrIP-seq)
GEO Series GSE69352. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
CRISPR/Cas9 screening of RNA binding proteins (RBPs) that regulate RUNX1 isoform production
GEO Series GSE145968. Homo sapiens. 11 samples. Type: Expression profiling by high throughput sequencing.
Cytosolic splice isoform of Hsp70 nucleotide exchange factor Fes1 is required for the degradation of misfolded proteins in yeast
GEO Series GSE78136. Saccharomyces cerevisiae. 18 samples. Type: Expression profiling by high throughput sequencing.
cTag-PAPERCLIP Reveals Alternative Polyadenylation Promotes Cell-Type Specific Protein Diversity and Shifts Araf Isoforms with Microglia Activation
GEO Series GSE94054. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing; Other.
Long read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors in disease
GEO Series GSE224588. Homo sapiens. 11 samples. Type: Expression profiling by high throughput sequencing.
Ribosome rescue factor PELOTA modulates translation start site choice and protein isoform levels of transcription factor C/EBPα [CRISPRi]
GEO Series GSE226435. Homo sapiens. 16 samples. Type: Other.
MeCP2-E1 isoform is a dynamically expressed, weakly DNA-bound protein with different protein and DNA interactions compared to MeCP2-E2
GEO Series GSE130277. Mus musculus. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
RNA sequencing of transcriptomes in human brain regions: protein-coding and non-coding RNAs, isoforms and alleles
GEO Series GSE68559. Homo sapiens. 98 samples. Type: Expression profiling by high throughput sequencing; Genome variation profiling by high throughput sequencing; Non-coding RNA 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.