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. 2018 Feb 7;10(2):68.
doi: 10.3390/v10020068.

High Whole-Genome Sequence Diversity of Human Papillomavirus Type 18 Isolates

Affiliations

High Whole-Genome Sequence Diversity of Human Papillomavirus Type 18 Isolates

Pascal van der Weele et al. Viruses. .

Abstract

Background: The most commonly found human papillomavirus (HPV) types in cervical cancer are HPV16 and HPV18. Genome variants of these types have been associated with differential carcinogenic potential. To date, only a handful of studies have described HPV18 whole genome sequencing results. Here we describe HPV18 variant diversity and conservation of persistent infections in a longitudinal retrospective cohort study.

Methods: Cervical self-samples were obtained annually over four years and genotyped on the SPF10-DEIA-LiPA25 platform. Clearing and persistent HPV18 positive infections were selected, amplified in two overlapping fragments, and sequenced using 32 sequence primers.

Results: Complete viral genomes were obtained from 25 participants with persistent and 26 participants with clearing HPV18 infections, resulting in 52 unique HPV18 genomes. Sublineage A3 was predominant in this population. The consensus viral genome was completely conserved over time in persistent infections, with one exception, where different HPV18 variants were identified in follow-up samples.

Conclusions: This study identified a diverse set of HPV18 variants. In persistent infections, the consensus viral genome is conserved. The identification of only one HPV18 infection with different major variants in follow-up implies that this is a potentially rare event. This dataset adds 52 HPV18 genome variants to Genbank, more than doubling the currently available HPV18 information resource, and all but one variant are unique additions.

Keywords: HPV18; genetic epidemiology; whole genome sequencing.

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Conflict of interest statement

Pascal van der Weele and Audrey J. King declare no conflicts of interest. Chris J.L.M. Meijer received speaker’s fees from GlaxoSmithKline, Qiagen, SPMSD/Merck, Roche, Menarini, and Seegene. On occasion, he served on the scientific advisory boards (expert meeting) of GSK, Qiagen, SPMSD/Merck, Roche, and Genticel and as a consultant for Qiagen and Genticel. He holds a small number of Qiagen shares and is a minority shareholder of Self-Screen BV, a spin-off company of Vrije Universiteit University Medical Centre, of which he is also part time director. Until 2014, he held a small number of shares in Delphi Biosciences. Until April 2016, he was a minority stock holder of Diassay BV.

Figures

Figure 1
Figure 1
Schematic overview human papillomavirus 18 (HPV18) infections in this study, including loss to follow-up and selections made for persistent and clearing HPV18 infections.
Figure 2
Figure 2
Maximum parsimony phylogenetic tree representing obtained human papillomavirus (HPV) 18 sequence data with corresponding ethnicity and compared to the currently available sequences in Genbank. Numbers on branches indicate the number of nucleotide differences between variants. Each circle represents one sequenced HPV18 variant, with the parts showing how often a variant was found. In green are reference strains for HPV18 according to [4]. Red and pink circles represent sequences obtained from persisting infections with and without sequenced follow-up respectively. Blue circles represent sequences obtained from clearing infections. The yellow circles show an infection where the initial and follow-up samples from one participant cluster differently. Grey circles represent sequences obtained from Genbank. Ethnicity for these sequences was added if available or presented as “Unk” (unknown) if not available. Marked with * are two variants who clustered poorly with any reference strain, but are still closest to A3.
Figure 3
Figure 3
Circular plot of non-orphan single-nucleotide polymorphisms (SNPs) on the human papillomavirus (HPV) 18 genome. Each dot denotes a variable site within the dataset. Black dots show total SNPs occurring in this study. Blue dots were variations identified in clearing infections, while reds dots were variations identified in persisting infections. Total DNA variations are shown on the light grey circles. Height of dots on the respective circles shows how often the variation occurs in the dataset.
Figure 4
Figure 4
Plot of nucleotide diversity (pi) of human papillomavirus (HPV) 18 sequences obtained in this study. The black line shows data from clearing infections (n = 25), while the grey line shows data from persistent infections (n = 20).

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