Evidence map›Paper›PMID 31881830›Full record

ArticleBMC bioinformatics2019

Rearrangement analysis of multiple bacterial genomes.

Mehwish Noureen, Ipputa Tada, Takeshi Kawashima, Masanori Arita

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Global diversity of integrating conjugative elements (ICEs) inbioRxiv : the preprint server for biology · 2025
    Article
  4. Article
  5. Article
  6. Microbial genomics · 2024
    Article
  7. Generalizations of the genomic rank distance to indels.Bioinformatics (Oxford, England) · 2023
    Article
  8. Article
  9. Article
  10. 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.

Mehwish NoureenNational Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan.
Ipputa TadaNational Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan.
Takeshi KawashimaNational Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan.
Masanori AritaNational Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan. arita@nig.ac.jp.ORCID http://orcid.org/0000-0001-6706-0487

Funding

Japan Society for the Promotion of Science 17K19248National Bioscience Database Center Togo DB project
6 · The paper itself

Abstract

backgroundGenomes are subjected to rearrangements that change the orientation and ordering of genes during evolution. The most common rearrangements that occur in uni-chromosomal genomes are inversions (or reversals) to adapt to the changing environment. Since genome rearrangements are rarer than point mutations, gene order with sequence data can facilitate more robust phylogenetic reconstruction. Helicobacter pylori is a good model because of its unique evolution in niche environment.

resultsWe have developed a method to identify genome rearrangements by comparing almost-conserved genes among closely related strains. Orthologous gene clusters, rather than the gene sequences, are used to align the gene order so that comparison of large number of genomes becomes easier. Comparison of 72 Helicobacter pylori strains revealed shared as well as strain-specific reversals, some of which were found in different geographical locations.

conclusionDegree of genome rearrangements increases with time. Therefore, gene orders can be used to study the evolutionary relationship among species and strains. Multiple genome comparison helps to identify the strain-specific as well as shared reversals. Identification of the time course of rearrangements can provide insights into evolutionary events.

Indexed as

Genome, BacterialChromosome InversionGene OrderGene RearrangementMultigene FamilyPhylogenyGene orderGenome rearrangementsHelicobacter pyloriReversals

Identifiers

PMID31881830
PMCPMC6933940

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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.