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Bayesian Coalescent Analysis Reveals a High Rate of Molecular Evolution in GB Virus C

Overview of attention for article published in Journal of Molecular Evolution, March 2008
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Title
Bayesian Coalescent Analysis Reveals a High Rate of Molecular Evolution in GB Virus C
Published in
Journal of Molecular Evolution, March 2008
DOI 10.1007/s00239-008-9087-3
Pubmed ID
Authors

Camila M. Romano, Paolo M. de A. Zanotto, Edward C. Holmes

Abstract

GB virus C/hepatitis G (GBV-C) is an RNA virus of the family Flaviviridae. Despite replicating with an RNA-dependent RNA polymerase, some previous estimates of rates of evolutionary change in GBV-C suggest that it fixes mutations at the anomalously low rate of approximately 10(-7) nucleotide substitution per site, per year. However, these estimates were largely based on the assumption that GBV-C and its close relative GBV-A (New World monkey GB viruses) codiverged with their primate hosts over millions of years. Herein, we estimated the substitution rate of GBV-C using the largest set of dated GBV-C isolates compiled to date and a Bayesian coalescent approach that utilizes the year of sampling and so is independent of the assumption of codivergence. This revealed a rate of evolutionary change approximately four orders of magnitude higher than that estimated previously, in the range of 10(-2) to 10(-3) sub/site/year, and hence in line with those previously determined for RNA viruses in general and the Flaviviridae in particular. In addition, we tested the assumption of host-virus codivergence in GBV-A by performing a reconciliation analysis of host and virus phylogenies. Strikingly, we found no statistical evidence for host-virus codivergence in GBV-A, indicating that substitution rates in the GB viruses should not be estimated from host divergence times.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Chile 1 3%
Unknown 27 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 34%
Student > Ph. D. Student 5 17%
Lecturer > Senior Lecturer 2 7%
Student > Doctoral Student 1 3%
Student > Bachelor 1 3%
Other 6 21%
Unknown 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 52%
Biochemistry, Genetics and Molecular Biology 4 14%
Immunology and Microbiology 1 3%
Medicine and Dentistry 1 3%
Engineering 1 3%
Other 0 0%
Unknown 7 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 March 2014.
All research outputs
#7,453,350
of 22,786,087 outputs
Outputs from Journal of Molecular Evolution
#450
of 1,438 outputs
Outputs of similar age
#28,385
of 79,880 outputs
Outputs of similar age from Journal of Molecular Evolution
#4
of 10 outputs
Altmetric has tracked 22,786,087 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,438 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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