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Analysis of codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) and its relation to evolution

Overview of attention for article published in BMC Genomics, August 2016
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Title
Analysis of codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) and its relation to evolution
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-3021-7
Pubmed ID
Authors

Yongchao Zhao, Hao Zheng, Anying Xu, Donghua Yan, Zijian Jiang, Qi Qi, Jingchen Sun

Abstract

Analysis of codon usage bias is an extremely versatile method using in furthering understanding of the genetic and evolutionary paths of species. Codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) has remained largely unexplored at present. Hence, the codon usage bias of NPV envelope glycoprotein was analyzed here to reveal the genetic and evolutionary relationships between different viral species in baculovirus genus. A total of 9236 codons from 18 different species of NPV of the baculovirus genera were used to perform this analysis. Glycoprotein of NPV exhibits weaker codon usage bias. Neutrality plot analysis and correlation analysis of effective number of codons (ENC) values indicate that natural selection is the main factor influencing codon usage bias, and that the impact of mutation pressure is relatively smaller. Another cluster analysis shows that the kinship or evolutionary relationships of these viral species can be divided into two broad categories despite all of these 18 species are from the same baculovirus genus. There are many elements that can affect codon bias, such as the composition of amino acids, mutation pressure, natural selection, gene expression level, and etc. In the meantime, cluster analysis also illustrates that codon usage bias of virus envelope glycoprotein can serve as an effective means of evolutionary classification in baculovirus genus.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 19%
Student > Doctoral Student 4 15%
Researcher 4 15%
Student > Master 3 11%
Other 2 7%
Other 2 7%
Unknown 7 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 30%
Agricultural and Biological Sciences 8 30%
Nursing and Health Professions 1 4%
Neuroscience 1 4%
Chemistry 1 4%
Other 0 0%
Unknown 8 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 26 August 2016.
All research outputs
#18,467,727
of 22,883,326 outputs
Outputs from BMC Genomics
#8,197
of 10,668 outputs
Outputs of similar age
#261,456
of 341,481 outputs
Outputs of similar age from BMC Genomics
#210
of 273 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 273 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.