Evidence map›Paper›PMID 29402213›Full record

ArticleBMC bioinformatics2018

xenoGI: reconstructing the history of genomic island insertions in clades of closely related bacteria.

Eliot C Bush, Anne E Clark, Carissa A DeRanek, Alexander Eng, Juliet Forman, Kevin Heath, Alexander B Lee, Daniel M Stoebel, Zunyan Wang, Matthew Wilber and 1 more

Abstract read
In one paragraph

Article in BMC bioinformatics, 2018. 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.

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  6. Microorganisms · 2020
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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

11 authors.

Eliot C BushDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA. bush@hmc.edu.ORCID 0000-0001-5476-8005
Anne E ClarkDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Carissa A DeRanekDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Alexander EngDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Juliet FormanDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Kevin HeathDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Alexander B LeeDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Daniel M StoebelDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Zunyan WangDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Matthew WilberDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.
Helen WuDepartment of Biology, Harvey Mudd College, 301 Platt Blvd., Claremont, 91711, CA, USA.

Funding

Howard Hughes Medical Institute 52007544
6 · The paper itself

Abstract

backgroundGenomic islands play an important role in microbial genome evolution, providing a mechanism for strains to adapt to new ecological conditions. A variety of computational methods, both genome-composition based and comparative, have been developed to identify them. Some of these methods are explicitly designed to work in single strains, while others make use of multiple strains. In general, existing methods do not identify islands in the context of the phylogeny in which they evolved. Even multiple strain approaches are best suited to identifying genomic islands that are present in one strain but absent in others. They do not automatically recognize islands which are shared between some strains in the clade or determine the branch on which these islands inserted within the phylogenetic tree.

resultsWe have developed a software package, xenoGI, that identifies genomic islands and maps their origin within a clade of closely related bacteria, determining which branch they inserted on. It takes as input a set of sequenced genomes and a tree specifying their phylogenetic relationships. Making heavy use of synteny information, the package builds gene families in a species-tree-aware way, and then attempts to combine into islands those families whose members are adjacent and whose most recent common ancestor is shared. The package provides a variety of text-based analysis functions, as well as the ability to export genomic islands into formats suitable for viewing in a genome browser. We demonstrate the capabilities of the package with several examples from enteric bacteria, including an examination of the evolution of the acid fitness island in the genus Escherichia. In addition we use output from simulations and a set of known genomic islands from the literature to show that xenoGI can accurately identify genomic islands and place them on a phylogenetic tree.

conclusionsxenoGI is an effective tool for studying the history of genomic island insertions in a clade of microbes. It identifies genomic islands, and determines which branch they inserted on within the phylogenetic tree for the clade. Such information is valuable because it helps us understand the adaptive path that has produced living species.

Indexed as

PhylogenySoftwareBacteriaComputer SimulationEvolution, MolecularGenome, BacterialGenomic IslandsReproducibility of ResultsTime FactorsGene familyGenomic islandHorizontal transferSynteny

Identifiers

PMID29402213
PMCPMC5799925

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LicenceCC BY
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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.