Evidence map›Paper›PMID 42011786›Full record

ArticleNucleic acids research2026

Multimodal profiling reveals cell type-specific pseudouridine modification and density-dependent translational regulation.

Caroline A McCormick, Michele Meseonznik, Yuchen Qiu, Oleksandra Fanari, Priyanka Goyal, Mitchell Thomas, Mina Shokoufandeh, Yifang Liu, Dylan Bloch, Cole Greenfield and 4 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. NanoCortex: A Unified Agentic System for Nanopore Sequencing Analysis.bioRxiv : the preprint server for biology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Caroline A McCormickDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.ORCID 0009-0000-0670-6707
Michele MeseonznikDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Yuchen QiuDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Oleksandra FanariDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Priyanka GoyalDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Mitchell ThomasDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Mina ShokoufandehDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Yifang LiuDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Dylan BlochDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Cole GreenfieldDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Isabel N KlinkDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Miten JainDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.ORCID 0000-0002-4571-3982
Meni WanunuDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.
Sara H RouhanifardDept. of Bioengineering, Northeastern University, Boston, MA, 02115, United States.ORCID 0000-0002-6991-4877

Funding

Synthetic mRNA Control Set for Nanopore-Based Pseudouridine Modification Profiling in Human TranscriptomesR01HG012856 · NHGRI · NORTHEASTERN UNIVERSITY · PI Sara Hakim Rouhanifard · 2023 to 2026
$3.4M
Single-cell direct RNA sequencing using electrical zero-mode waveguides and engineered reverse transcriptasesR01HG011087 · NHGRI · NORTHEASTERN UNIVERSITY · PI WANUNU, MENI · 2020 to 2023
$3.0M
NIH HHS R01HG011087NIH HHS R01HG012856Technology Development Coordinating Center at Jackson Laboratories U24HG011735
6 · The paper itself

Abstract

Pseudouridine (psi) is one of the most abundant mRNA modifications, yet its impact on translation is unclear, in part because existing modification maps are inconsistent, curated comparisons across cell types are lacking, and paired analyses with translation are limited. Using direct RNA nanopore sequencing coupled with our Mod-p ID analytical framework, we mapped psi at single-nucleotide resolution across six immortalized human cell lines. Nanopore sequencing provided single-molecule resolution, enabling quantification of relative modification occupancy and detection of co-occurring modifications. Integrating these psi maps with matched proteomic and ribosome profiling datasets revealed that conserved psi sites installed by the psi synthase TRUB1 are associated with increased protein production. TRUB1 knockout experiments demonstrated a motif-specific reduction in protein abundance, providing direct causal evidence that pseudouridylation enhances protein output. In contrast, transcripts bearing clustered psi sites exhibited reduced protein abundance despite elevated translation efficiency. Controlled in vitro translation experiments confirmed that increasing pseudouridine density within a physiologically relevant range directly reduces protein output, demonstrating a density-dependent effect of pseudouridylation on translation. Together, these findings establish a mechanistic framework in which single-site pseudouridylation enhances protein production, whereas hypermodification impairs translational throughput, revealing pseudouridine density and enzyme specificity as key determinants of proteome output across human cell types.

Indexed as

Protein BiosynthesisPseudouridineCell LineHEK293 CellsHumansProteomicsRibosome ProfilingRibosomesRNA, MessengerRNA Processing, Post-TranscriptionalPseudouridineRNA, Messenger

Identifiers

PMID42011786
PMCPMC13096809

What OpenQuestion holds

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LicenceCC BY-NC
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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.