Article
Next Generation Sequencing for the Analysis of Parvovirus B19 Genomic Diversity
Registro en:
BICHICHI, Federica et al. Next Generation Sequencing for the Analysis of Parvovirus B19 Genomic Diversity. Viruses, v. 15, 217, p. 1 - 14, Jan. 2023.
1999-4915
10.3390/v15010217
Autor
Bichicchi, Federica
Guglietta, Niccolò
Alves, Arthur Daniel Rocha
Fasano, Erika
Manaresi, Elisabetta
Bua, Gloria
Gallinella, Giorgio
Resumen
Parvovirus B19 (B19V) is a ssDNA human virus, responsible for an ample range of clinical
manifestations. Sequencing of B19V DNA from clinical samples is frequently reported in the literature
to assign genotype (genotypes 1–3) and for finer molecular epidemiological tracing. The increasing
availability of Next Generation Sequencing (NGS) with its depth of coverage potentially yields
information on intrinsic sequence heterogeneity; however, integration of this information in analysis
of sequence variation is not routinely obtained. The present work investigated genomic sequence
heterogeneity within and between B19V isolates by application of NGS techniques, and by the
development of a novel dedicated bioinformatic tool and analysis pipeline, yielding information on
two newly defined parameters. The first, -diversity, is a measure of the amount and distribution of
position-specific, normalised Shannon Entropy, as a measure of intra-sample sequence heterogeneity.
The second, -diversity, is a measure of the amount of inter-sample sequence heterogeneity, also
incorporating information on -diversity. Based on these indexes, further cluster analysis can be
performed. A set of 24 high-titre viraemic samples was investigated. Of these, 23 samples were
genotype 1 and one sample was genotype 2. Genotype 1 isolates showed low -diversity values,
with only a few samples showing distinct position-specific polymorphisms; a few genetically related
clusters emerged when analysing inter-sample distances, correlated to the year of isolation; the
single genotype 2 isolate showed the highest -diversity, even if not presenting polymorphisms, and
was an evident outlier when analysing inter-sample distance. In conclusion, NGS analysis and the
bioinformatic tool and pipeline developed and used in the present work can be considered effective
tools for investigating sequence diversity, an observable parameter that can be incorporated into the
quasispecies theory framework to yield a better insight into viral evolution dynamics.