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

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 ph...

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Autores principales: Shuai Wang, Xuenong Luo, Wei Wei, Yadong Zheng, Yongxi Dou, Xuepeng Cai
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2013
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Acceso en línea:https://doaj.org/article/5690f12a8de44a658b0bed7d14582dc0
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Sumario: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.