Evidence map›Paper›PMID 28178267›Full record

ArticlePLoS computational biology2017

A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons.

Yen-Fu Chen, Hsiu-Chuan Lin, Kai-Neng Chuang, Chih-Hsu Lin, Hsueh-Chi S Yen, Chen-Hsiang Yeang

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Yen-Fu ChenInstitute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
Hsiu-Chuan LinInstitute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
Kai-Neng ChuangInstitute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
Chih-Hsu LinInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.ORCID 0000-0003-4034-8960
Hsueh-Chi S YenInstitute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
Chen-Hsiang YeangGenome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei, Taiwan.ORCID 0000-0002-9224-5800
National Taiwan University · TWInstitute of Molecular Biology, Academia Sinica · TWInstitute of Statistical Science, Academia Sinica · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ambiguity in genetic codes exists in cases where certain stop codons are alternatively used to encode non-canonical amino acids. In selenoprotein transcripts, the UGA codon may either represent a translation termination signal or a selenocysteine (Sec) codon. Translating UGA to Sec requires selenium and specialized Sec incorporation machinery such as the interaction between the SECIS element and SBP2 protein, but how these factors quantitatively affect alternative assignments of UGA has not been fully investigated. We developed a model simulating the UGA decoding process. Our model is based on the following assumptions: (1) charged Sec-specific tRNAs (Sec-tRNASec) and release factors compete for a UGA site, (2) Sec-tRNASec abundance is limited by the concentrations of selenium and Sec-specific tRNA (tRNASec) precursors, and (3) all synthesis reactions follow first-order kinetics. We demonstrated that this model captured two prominent characteristics observed from experimental data. First, UGA to Sec decoding increases with elevated selenium availability, but saturates under high selenium supply. Second, the efficiency of Sec incorporation is reduced with increasing selenoprotein synthesis. We measured the expressions of four selenoprotein constructs and estimated their model parameters. Their inferred Sec incorporation efficiencies did not correlate well with their SECIS-SBP2 binding affinities, suggesting the existence of additional factors determining the hierarchy of selenoprotein synthesis under selenium deficiency. This model provides a framework to systematically study the interplay of factors affecting the dual definitions of a genetic codon.

Indexed as

Models, GeneticCodon, InitiatorCodon, TerminatorComputer SimulationProtein BiosynthesisProteinsSelenocysteineSelenoproteinsSequence Analysis, RNACodon, InitiatorCodon, TerminatorProteinsSelenocysteineSelenoproteins

Identifiers

PMID28178267
PMCPMC5323020
OpenAlexW2587237058

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.