Evidence map›Paper›PMID 39012054›Full record

ArticleJournal of the American Society for Mass Spectrometry2024

IS-PRM-Based Peptide Targeting Informed by Long-Read Sequencing for Alternative Proteome Detection.

Jennifer A Korchak, Erin D Jeffery, Saikat Bandyopadhyay, Ben T Jordan, Micah D Lehe, Emily F Watts, Aidan Fenix, Mathias Wilhelm, Gloria M Sheynkman

Abstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Long-read RNA sequencing: A transformative technology for exploring transcriptome complexity in human diseases.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  4. Enhanced Sample Multiplexing-Based Targeted Proteomics with Intelligent Data Acquisition.Journal of the American Society for Mass Spectrometry · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Jennifer A KorchakDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia 22903, United States.ORCID 0000-0002-2679-721X
Erin D JefferyDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia 22903, United States.ORCID 0000-0001-9511-7719
Saikat BandyopadhyayDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia 22903, United States.
Ben T JordanCancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States.
Micah D LeheDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia 22903, United States.
Emily F WattsDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia 22903, United States.
Aidan FenixDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington 98195, United States.
Mathias WilhelmComputational Mass Spectrometry, Technical University of Munich (TUM), D-85354 Freising, Germany.ORCID 0000-0002-9224-3258
Gloria M SheynkmanDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia 22903, United States.ORCID 0000-0002-4223-9947

Funding

BASIC CARDIOVASCULAR RESEARCH TRAINING GRANTT32HL007284 · NHLBI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Brant E Isakson, Gary K Owens · 1985 to 2026
$19.6M
Uncovering the functional diversification mechanisms of transcription factor isoforms involved in stem cell differentiationR35GM142647 · NIGMS · UNIVERSITY OF VIRGINIA · PI SHEYNKMAN, GLORIA · 2021 to 2025
$2.1M
NHLBI NIH HHS T32 HL007284NIGMS NIH HHS R35 GM142647
6 · The paper itself

Abstract

Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of predefined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (lrRNA-seq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNaseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This lrRNA-seq-informed Tomahto targeted approach is a new modality for generating protein-level evidence of alternative isoforms─a critical first step in designing functional studies and eventually clinical assays.

Indexed as

Alternative SplicingPeptidesProtein IsoformsProteomeCell LineHumansProteogenomicsSequence Analysis, RNATandem Mass SpectrometryPeptidesProtein IsoformsProteome

Identifiers

PMID39012054
PMCPMC11544703

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.