Evidence map›Paper›PMID 32299351›Full record

ArticleBMC genomics2020

Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria.

Tomasz Pawliszak, Meghan Chua, Carson K Leung, Olivier Tremblay-Savard

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

0 citing papers in PubMed, 24 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Tomasz PawliszakDepartment of Computer Science, University of Manitoba, Winnipeg, Canada.
Meghan ChuaDepartment of Computer Science, University of Manitoba, Winnipeg, Canada.
Carson K LeungDepartment of Computer Science, University of Manitoba, Winnipeg, Canada.
Olivier Tremblay-SavardDepartment of Computer Science, University of Manitoba, Winnipeg, Canada. tremblao@cs.umanitoba.ca.
University of Manitoba · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn bacterial genomes, rRNA and tRNA genes are often organized into operons, i.e. segments of closely located genes that share a single promoter and are transcribed as a single unit. Analyzing how these genes and operons evolve can help us understand what are the most common evolutionary events affecting them and give us a better picture of ancestral codon usage and protein synthesis.

resultsWe introduce BOPAL, a new approach for the inference of evolutionary histories of rRNA and tRNA genes in bacteria, which is based on the identification of orthologous operons. Since operons can move around in the genome but are rarely transformed (e.g. rarely broken into different parts), this approach allows for a better inference of orthologous genes in genomes that have been affected by many rearrangements, which in turn helps with the inference of more realistic evolutionary scenarios and ancestors.

conclusionsFrom our comparisons of BOPAL with other gene order alignment programs using simulated data, we have found that BOPAL infers evolutionary events and ancestral gene orders more accurately than other methods based on alignments. An analysis of 12 Bacillus genomes also showed that BOPAL performs just as well as other programs at building ancestral histories in a minimal amount of events.

Indexed as

AlgorithmsBacillusBacteriaDatabases, GeneticEvolution, MolecularGene DuplicationGene OrderGenome, BacterialGenomicsModels, GeneticOperonPhylogenyResearch DesignRNA, RibosomalRNA, TransferSequence DeletionRNA, RibosomalRNA, TransferAncestral gene ordersEvolutionary historiesGlobal alignmentsOperonsPhylogenyrRNA and tRNA genes

Identifiers

PMID32299351
PMCPMC7160887
OpenAlexW3016609671

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.