Evidence map›Paper›PMID 24192837›Full record

ArticleG3 (Bethesda, Md.)2014

Origin and length distribution of unidirectional prokaryotic overlapping genes.

Miguel M Fonseca, D James Harris, David Posada

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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

3 authors.

Miguel M FonsecaDepartment of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain.
D James Harris
David Posada

Funding

European Research Council 203161
6 · The paper itself

Abstract

Prokaryotic unidirectional overlapping genes can be originated by disrupting and replacing of the start or stop codon of one protein-coding gene with another start or stop codon within the adjacent gene. However, the probability of disruption and replacement of a start or stop codon may differ significantly depending on the number and redundancy of the start and stop codons sets. Here, we performed a simulation study of the formation of unidirectional overlapping genes using a simple model of nucleotide change and contrasted it with empirical data. Our results suggest that overlaps originated by an elongation of the 3'-end of the upstream gene are significantly more frequent than those originated by an elongation of the 5'-end of the downstream gene. According to this, we propose a model for the creation of unidirectional overlaps that is based on the disruption probabilities of start codon and stop codon sets and on the different probabilities of phase 1 and phase 2 overlaps. Additionally, our results suggest that phase 2 overlaps are formed at higher rates than phase 1 overlaps, given the same evolutionary time. Finally, we propose that there is no need to invoke selection to explain the prevalence of long phase 1 unidirectional overlaps. Rather, the overrepresentation of long phase 1 relative to long phase 2 overlaps might occur because it is highly probable that phase 2 overlaps are retained as short overlaps by chance. Such a pattern is stronger if selection against very long overlaps is included in the model. Our model as a whole is able to explain to a large extent the empirical length distribution of unidirectional overlaps in prokaryotic genomes.

Indexed as

Genes, ArchaealGenes, BacterialArchaeaBacteriaBase CompositionCodon, InitiatorCodon, TerminatorGenes, OverlappingModels, GeneticPoint MutationCodon, InitiatorCodon, Terminatoroverlap length distributionoverlapping genesprokaryotic genomesunidirectional genes

Identifiers

PMID24192837
PMCPMC3887535

What OpenQuestion holds

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LicenceCC BY
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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.