Evidence map›Paper›PMID 20333212›Full record

ArticleGenome biology and evolution2009

Lateral transfer of genes and gene fragments in prokaryotes.

Cheong Xin Chan, Robert G Beiko, Aaron E Darling, Mark A Ragan

Open access · goldAbstract read
In one paragraph

Article in Genome biology and evolution, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

36 citing papers in PubMed, 92 citations in OpenAlex.

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  17. Next-generation phylogenomics.Biology direct · 2013
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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

4 authors at 1 institution in 2 countries.

Cheong Xin ChanInstitute for Molecular Bioscience and ARC Centre of Excellence in Bioinformatics, The University of Queensland, Brisbane, Queensland, Australia.
Robert G Beiko
Aaron E Darling
Mark A Ragan
University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lateral genetic transfer (LGT) involves the movement of genetic material from one lineage into another and its subsequent incorporation into the new host genome via genetic recombination. Studies in individual taxa have indicated lateral origins for stretches of DNA of greatly varying length, from a few nucleotides to chromosome size. Here we analyze 1,462 sets of single-copy, putatively orthologous genes from 144 fully sequenced prokaryote genomes, asking to what extent complete genes and fragments of genes have been transferred and recombined in LGT. Using a rigorous phylogenetic approach, we find evidence for LGT in at least 476 (32.6%) of these 1,462 gene sets: 286 (19.6%) clearly show one or more "observable recombination breakpoints" within the boundaries of the open reading frame, while a further 190 (13.0%) yield trees that are topologically incongruent with the reference tree but do not contain a recombination breakpoint within the open reading frame. We refer to these gene sets as observable recombination breakpoint positive (ORB(+)) and negative (ORB(-)) respectively. The latter are prima facie instances of lateral transfer of an entire gene or beyond. We observe little functional bias between ORB(+) and ORB(-) gene sets, but find that incorporation of entire genes is potentially more frequent in pathogens than in nonpathogens. As ORB(+) gene sets are about 50% more common than ORB(-) sets in our data, the transfer of gene fragments has been relatively frequent, and the frequency of LGT may have been systematically underestimated in phylogenetic studies.

Indexed as

comparative genomicsgenetic recombinationgenome evolutionhorizontal genetic transferlateral genetic transfer

Identifiers

PMID20333212
PMCPMC2817436
OpenAlexW2148046120

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LicenceCC BY-NC
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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.