Evidence map›Paper›PMID 20230630›Full record

ArticleBMC bioinformatics2010

Missing genes in the annotation of prokaryotic genomes.

Andrew S Warren, Jeremy Archuleta, Wu-Chun Feng, João Carlos Setubal

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

58 citing papers in PubMed, 118 citations in OpenAlex.

  1. Bacteriocin distribution patterns inApplied and environmental microbiology · 2024
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  4. StORF-Reporter: finding genes between genes.Nucleic acids research · 2023
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  5. Challenges in prokaryote pangenomics.Microbial genomics · 2023
    Review
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  13. Evolution ofPeerJ · 2022
    Article
  14. Article
  15. Understanding small ORF diversity through a comprehensive transcription feature classification.DNA research : an international journal for rapid publication of reports on genes and genomes · 2021
    Review
  16. Article
  17. PeerJ · 2021
    Article
  18. Article
  19. Article
  20. 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 at 1 institution in 1 country.

Andrew S WarrenVirginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA. anwarren@vt.edu
Jeremy Archuleta
Wu-Chun Feng
João Carlos Setubal
Virginia Tech · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein-coding gene detection in prokaryotic genomes is considered a much simpler problem than in intron-containing eukaryotic genomes. However there have been reports that prokaryotic gene finder programs have problems with small genes (either over-predicting or under-predicting). Therefore the question arises as to whether current genome annotations have systematically missing, small genes.

resultsWe have developed a high-performance computing methodology to investigate this problem. In this methodology we compare all ORFs larger than or equal to 33 aa from all fully-sequenced prokaryotic replicons. Based on that comparison, and using conservative criteria requiring a minimum taxonomic diversity between conserved ORFs in different genomes, we have discovered 1,153 candidate genes that are missing from current genome annotations. These missing genes are similar only to each other and do not have any strong similarity to gene sequences in public databases, with the implication that these ORFs belong to missing gene families. We also uncovered 38,895 intergenic ORFs, readily identified as putative genes by similarity to currently annotated genes (we call these absent annotations). The vast majority of the missing genes found are small (less than 100 aa). A comparison of select examples with GeneMark, EasyGene and Glimmer predictions yields evidence that some of these genes are escaping detection by these programs.

conclusionsProkaryotic gene finders and prokaryotic genome annotations require improvement for accurate prediction of small genes. The number of missing gene families found is likely a lower bound on the actual number, due to the conservative criteria used to determine whether an ORF corresponds to a real gene.

Indexed as

Genes, BacterialGenome, BacterialDatabases, GeneticGenomicsOpen Reading FramesProkaryotic Cells

Identifiers

PMID20230630
PMCPMC3098052
OpenAlexW2090327616

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.