Evidence map›Paper›PMID 40750788›Full record

ArticleNature communications2025

Development and application of GlycanDIA workflow for glycomic analysis.

Yixuan Xie, Xingyu Liu, Li Yi, Shunyang Wang, Zongtao Lin, Chenfeng Zhao, Siyu Chen, Faith M Robison, Benson M George, Carlito B Lebrilla and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
  2. Glycan Sequencing, A Brief Primer.Glycoscience & therapy · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. O-glycosylation contributes to mammalian glycoRNA biogenesis.bioRxiv : the preprint server for biology · 2024
    Article
  17. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Yixuan XieState Key Laboratory of Genetic Engineering, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China. xieyixuan@ipm-gba.org.cn.
Xingyu LiuDepartment of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID http://orcid.org/0000-0003-0008-7815
Li YiState Key Laboratory of Genetic Engineering, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0002-2872-2569
Shunyang WangDepartment of Chemistry, University of California, Davis, Davis, California, USA.
Zongtao LinDepartment of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID http://orcid.org/0000-0002-6017-338X
Chenfeng ZhaoDepartment of Computer Science & Engineering, Washington University, St. Louis, Missouri, USA.
Siyu ChenDepartment of Chemistry, University of California, Davis, Davis, California, USA.ORCID http://orcid.org/0009-0003-9584-6905
Faith M RobisonDepartment of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA.
Benson M GeorgeStem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts, USA.
Carlito B LebrillaDepartment of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID http://orcid.org/0000-0001-7190-5323
Ryan A FlynnStem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts, USA. ryan.flynn@childrens.harvard.edu.ORCID http://orcid.org/0000-0001-5013-0442
Benjamin A GarciaDepartment of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA. bagarcia@wustl.edu.ORCID http://orcid.org/0000-0003-3596-4750

Funding

Research Education ComponentP30AG066444 · NIA · WASHINGTON UNIVERSITY · PI Susan Lynn Stark · 2020 to 2026
$28.7M
Shared Resources Core 2: Quantitative Proteomics CoreP01CA196539 · NCI · ROCKEFELLER UNIVERSITY · PI YOUNG, MICHAEL WARREN · 2015 to 2024
$17.6M
The incorporation of human milk oligosaccharides in brain glycoconjugatesR01GM049077 · NIGMS · UNIVERSITY OF CALIFORNIA DAVIS · PI LEBRILLA, CARLITO B · 1999 to 2024
$6.3M
Viral modulation of epitranscriptomic mechanismsR01AI118891 · NIAID · WASHINGTON UNIVERSITY · PI GARCIA, BENJAMIN A, WEITZMAN, MATTHEW D. · 2015 to 2025
$5.4M
Comprehensive Characterization of Glycosylation Alterations in Alzheimer’s DiseaseR01AG062240 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI JIN, LEE-WAY, LEBRILLA, CARLITO B · 2018 to 2022
$3.3M
Quantitative mass spectrometry for comprehending epigenetic mechanisms in a new underlying neurological developmental disorderR01HD106051 · NICHD · WASHINGTON UNIVERSITY · PI Benjamin A Garcia · 2022 to 2026
$2.6M
Mechanisms and functions of cell surface glycoRNAsR35GM151157 · NIGMS · BOSTON CHILDREN'S HOSPITAL · PI Ryan Alexander Flynn · 2023 to 2026
$1.8M
Development and Application of Chemical Biology Approaches for Understanding Protein ArginylationR01HL177113 · NHLBI · WASHINGTON UNIVERSITY · PI Benjamin A Garcia, Zongtao Lin · 2025 to 2026
$1.2M
NCI NIH HHS P01 CA196539NHLBI NIH HHS R01 HL177113NIAID NIH HHS R01 AI118891NIA NIH HHS P30 AG066444NIA NIH HHS R01 AG062240NICHD NIH HHS R01 HD106051NIGMS NIH HHS R01 GM049077NIGMS NIH HHS R35 GM151157U.S. Department of Health & Human Services | National Institutes of Health (NIH) AI118891U.S. Department of Health & Human Services | National Institutes of Health (NIH) CA196539U.S. Department of Health & Human Services | National Institutes of Health (NIH) HD106051
6 · The paper itself

Abstract

Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Herein, we report a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and precision. The GlycanDIA workflow combines higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and precision in quantification compared to conventional glycomic methods. To facilitate its use, we also develop a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification from DIA data. Our results demonstrate that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity and precision, we perform experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we find that RNA-glycans have different abundant forms as compared to protein-glycans and there are also tissue-specific differences, suggesting their distinct functions in biological processes.

Indexed as

GlycomicsPolysaccharidesAnimalsGlycosylationHumansMiceMilk, HumanOligosaccharidesTandem Mass SpectrometryWorkflowOligosaccharidesPolysaccharides

Identifiers

PMID40750788
PMCPMC12317082

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.