Evidence map›Paper›PMID 24312527›Full record

ArticlePloS one2013

Calculation of evolutionary correlation between individual genes and full-length genome: a method useful for choosing phylogenetic markers for molecular epidemiology.

Shuai Wang, Xuenong Luo, Wei Wei, Yadong Zheng, Yongxi Dou, Xuepeng Cai

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.8field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Shuai WangState Key Laboratory of Veterinary Etiological Biology, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu, China.
Xuenong Luo
Wei Wei
Yadong Zheng
Yongxi Dou
Xuepeng Cai
Chinese Academy of Agricultural Sciences · CNLanzhou Veterinary Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individual genes or regions are still commonly used to estimate the phylogenetic relationships among viral isolates. The genomic regions that can faithfully provide assessments consistent with those predicted with full-length genome sequences would be preferable to serve as good candidates of the phylogenetic markers for molecular epidemiological studies of many viruses. Here we employed a statistical method to evaluate the evolutionary relationships between individual viral genes and full-length genomes without tree construction as a way to determine which gene can match the genome well in phylogenetic analyses. This method was performed by calculation of linear correlations between the genetic distance matrices of aligned individual gene sequences and aligned genome sequences. We applied this method to the phylogenetic analyses of porcine circovirus 2 (PCV2), measles virus (MV), hepatitis E virus (HEV) and Japanese encephalitis virus (JEV). Phylogenetic trees were constructed for comparisons and the possible factors affecting the method accuracy were also discussed in the calculations. The results revealed that this method could produce results consistent with those of previous studies about the proper consensus sequences that could be successfully used as phylogenetic markers. And our results also suggested that these evolutionary correlations could provide useful information for identifying genes that could be used effectively to infer the genetic relationships.

Indexed as

Genetic MarkersGenome, ViralHumansMolecular EpidemiologySequence AlignmentVirus DiseasesVirusesGenetic Markers

Identifiers

PMID24312527
PMCPMC3849185
OpenAlexW2060124223

What OpenQuestion holds

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LicenceCC BY
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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.