Evidence map›Paper›PMID 39703423›Full record

ArticleNAR genomics and bioinformatics2024

Cell- and tissue-specific glycosylation pathways informed by single-cell transcriptomics.

Panagiotis Chrysinas, Shriramprasad Venkatesan, Isaac Ang, Vishnu Ghosh, Changyou Chen, Sriram Neelamegham, Rudiyanto Gunawan

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Unraveling the Glycosylation Machinery ofInternational journal of molecular sciences · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Panagiotis ChrysinasDepartment of Chemical and Biological Engineering, University at Buffalo-SUNY, 308 Furnas Hall, Buffalo, NY 14260, USA.
Shriramprasad VenkatesanDepartment of Chemical and Biological Engineering, University at Buffalo-SUNY, 308 Furnas Hall, Buffalo, NY 14260, USA.
Isaac AngDepartment of Computer Science, University of Illinois Urbana-Champaign, 201 North Goodwin Avenue, Urbana, IL 61801, USA.
Vishnu GhoshDepartment of Chemical and Biological Engineering, University at Buffalo-SUNY, 308 Furnas Hall, Buffalo, NY 14260, USA.
Changyou ChenDepartment of Computer Science and Engineering, University at Buffalo-SUNY, 338 Davis Hall, Buffalo, NY 14260, USA.
Sriram NeelameghamDepartment of Chemical and Biological Engineering, University at Buffalo-SUNY, 308 Furnas Hall, Buffalo, NY 14260, USA.ORCID https://orcid.org/0000-0002-1371-8500
Rudiyanto GunawanDepartment of Chemical and Biological Engineering, University at Buffalo-SUNY, 308 Furnas Hall, Buffalo, NY 14260, USA.ORCID https://orcid.org/0000-0002-6480-7976

Funding

Project 3: Role of Glycosaminoglycans in HematopoiesisP01HL151333 · NHLBI · VERSITI WISCONSIN, INC. · PI HOFFMEISTER, KARIN MARIA · 2021 to 2025
$12.3M
Systems Biology of GlycosylationR01HL103411 · NHLBI · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI NEELAMEGHAM, SRIRAM · 2011 to 2025
$7.1M
NHLBI NIH HHS P01 HL151333NHLBI NIH HHS R01 HL103411
6 · The paper itself

Abstract

While single-cell studies have made significant impacts in various subfields of biology, they lag in the Glycosciences. To address this gap, we analyzed single-cell glycogene expressions in the Tabula Sapiens dataset of human tissues and cell types using a recent glycosylation-specific gene ontology (GlycoEnzOnto). At the median sequencing (count) depth, ∼40-50 out of 400 glycogenes were detected in individual cells. Upon increasing the sequencing depth, the number of detectable glycogenes saturates at ∼200 glycogenes, suggesting that the average human cell expresses about half of the glycogene repertoire. Hierarchies in glycogene and glycopathway expressions emerged from our analysis: nucleotide-sugar synthesis and transport exhibited the highest gene expressions, followed by genes for core enzymes, glycan modification and extensions, and finally terminal modifications. Interestingly, the same cell types showed variable glycopathway expressions based on their organ or tissue origin, suggesting nuanced cell- and tissue-specific glycosylation patterns. Probing deeper into the transcription factors (TFs) of glycogenes, we identified distinct groupings of TFs controlling different aspects of glycosylation: core biosynthesis, terminal modifications, etc. We present webtools to explore the interconnections across glycogenes, glycopathways and TFs regulating glycosylation in human cell/tissue types. Overall, the study presents an overview of glycosylation across multiple human organ systems.

Identifiers

PMID39703423
PMCPMC11655298

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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.