Evidence map›Paper›PMID 40561183›Full record

ArticlePLoS genetics2025

Defining the high-translational readthrough stop codon context.

Daniela Smoljanow, Dennis Lebeda, Julia Hofhuis, Sven Thoms

Abstract read
In one paragraph

Article in PLoS genetics, 2025. 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. RNAViruses · 2026
    Review
  3. 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

4 authors.

Daniela SmoljanowDepartment for Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany.ORCID https://orcid.org/0009-0001-6388-3205
Dennis LebedaDepartment for Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany.
Julia HofhuisDepartment for Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany.ORCID https://orcid.org/0000-0003-2774-1661
Sven ThomsDepartment for Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany.ORCID https://orcid.org/0000-0003-3018-6363

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Translational termination is not entirely efficient and competes with elongation, which might result in translational readthrough (TR). TR occurs when a near-cognate tRNA binds to a stop codon, (mis)interpreting it as a sense codon and producing a C-terminal extension of the protein. This process is influenced by the stop codon itself and the surrounding nucleotide sequence, known as the stop codon context (SCC). To investigate the role of these cis-acting elements beyond the high-TR motif UGA CUA G, this study examines specific positions within the SCC, both upstream and downstream of the motif, that contribute to variations in basal and aminoglycoside-induced TR. In particular, we identified a surprisingly large influence of the upstream nucleotide positions -9 and -8 (relative to the stop codon) and positions +11 and +12 on readthrough levels, revealing a complex interplay between nucleotides in the expanded SCC with effects turning out to be non-linear and, furthermore, not transferable to evolutionarily non-adapted SCCs. These findings support our understanding of translational termination and may benefit the development of pharmacological therapy for diseases caused by premature stop codon mutations.

Indexed as

Codon, TerminatorPeptide Chain Termination, TranslationalProtein BiosynthesisAminoglycosidesCodon, NonsenseHumansRNA, TransferAminoglycosidesCodon, NonsenseCodon, TerminatorRNA, Transfer

Identifiers

PMID40561183
PMCPMC12233894

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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.