Evidence map›Paper›PMID 20459719›Full record

ArticleBMC genomics2010

In silico identification of the sea squirt selenoproteome.

Liang Jiang, Qiong Liu, Jiazuan Ni

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.9field-weighted citation impact, top 11% of its field
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

15 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Article
  3. The algal selenoproteomes.BMC genomics · 2020
    Article
  4. Bioinformatics of Selenoproteins.Antioxidants & redox signaling · 2020
    Review
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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

3 authors at 2 institutions in 1 country.

Liang JiangChangchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, PR China.
Qiong Liu
Jiazuan Ni
Chinese Academy of Sciences · CNShenzhen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputational methods for identifying selenoproteins have been developed rapidly in recent years. However, it is still difficult to identify the open reading frame (ORF) of eukaryotic selenoprotein gene, because the TGA codon for a selenocysteine (Sec) residue in the active centre of selenoprotein is traditionally a terminal signal of protein translation. Although the identification of selenoproteins from genomes through bioinformatics methods has been conducted in bacteria, unicellular eukaryotes, insects and several vertebrates, only a few results have been reported on the ancient chordate selenoproteins.

resultsA gene assembly algorithm SelGenAmic has been constructed and presented in this study for identifying selenoprotein genes from eukaryotic genomes. A method based on this algorithm was developed to build an optimal TGA-containing-ORF for each TGA in a genome, followed by protein similarity analysis through conserved sequence alignments to screen out selenoprotein genes form these ORFs. This method improved the sensitivity of detecting selenoproteins from a genome due to the design that all TGAs in the genome were investigated for its possibility of decoding as a Sec residue. Using this method, eighteen selenoprotein genes were identified from the genome of Ciona intestinalis, leading to its member of selenoproteome up to 19. Among them a selenoprotein W gene was found to have two SECIS elements in the 3'-untranslated region. Additionally, the disulfide bond formation protein A (DsbA) was firstly identified as a selenoprotein in the ancient chordates of Ciona intestinalis, Ciona savignyi and Branchiostoma floridae, while selenoprotein DsbAs had only been found in bacteria and green algae before.

conclusionThe method based on SelGenAmic algorithm is capable of identifying eukaryotic selenoprotein genes from their genomes. Application of this method to Ciona intestinalis proves its successes in finding Sec-decoding TGA from large-scale eukaryotic genome sequences, which fills the gap in our knowledge on the ancient chordate selenoproteins.

Indexed as

AlgorithmsAnimalsProteomeSelenoproteinsUrochordataProteomeSelenoproteins

Identifiers

PMID20459719
PMCPMC2874816
OpenAlexW2008417944

What OpenQuestion holds

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LicenceCC BY
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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.