Diversifying selection in human papillomavirus type 16 lineages based on complete genome analyses - PubMed (original) (raw)

Diversifying selection in human papillomavirus type 16 lineages based on complete genome analyses

Zigui Chen et al. J Virol. 2005 Jun.

Abstract

Human papillomavirus type 16 (HPV16) is the primary etiological agent of cervical cancer, the second most common cancer in women worldwide. Complete genomes of 12 isolates representing the major lineages of HPV16 were cloned and sequenced from cervicovaginal cells. The sequence variations within the open reading frames (ORFs) and noncoding regions were identified and compared with the HPV16R reference sequence. This whole-genome approach gives us unprecedented precision in detailing sequence-level changes that are under selection on a whole-viral-genome scale. Of 7,908 base pair nucleotide positions, 313 (4.0%) were variable. Within the 2,452 amino acids (aa) comprising 8 ORFs, 243 (9.9%) amino acid positions were variable. In order to investigate the molecular evolution of HPV16 variants, maximum likelihood models of codon substitution were used to identify lineages and amino acid sites under selective pressure. Five codon sites in the E5 (aa 48, 65) and E6 (aa 10, 14, 83) ORFs were demonstrated to be under diversifying selective pressure. The E5 ORF had the overall highest nonsynonymous/synonymous substitution rate (omega) ratio (M3 = 0.7965). The E2 gene had the next-highest omega ratio (M3 = 0.5611); however, no specific codons were under positive selection. These data indicate that the E6 and E5 ORFs are evolving under positive Darwinian selection and have done so in a relatively short time period. Whether response to selective pressure upon the E5 and E6 ORFs contributes to the biological success of HPV16, its specific biological niche, and/or its oncogenic potential remains to be established.

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Figures

FIG. 1.

FIG. 1.

Phylogenetic trees inferred from the complete genomes of representative HPV16 variants. Trees were generated using multiple algorithms. (A) Tree created using Bayesian construction and MP based on the nucleotide sequences of the eight ORFs and the URR. (B) Tree created using Bayesian construction and ML based on the nucleotide sequences of the eight ORFs and the URR. (C) Tree created using Bayesian construction and MP based on the amino acid sequences of the eight ORFs. The parsimony tree based on the concatenated amino acid and nucleotide sequences was similar to the tree shown in panel C (data not shown). The numbers on or near branches are support indices for the algorithms described for each tree.

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