Abstract
Shot-gun next generation sequencing (NGS) on whole DNA extracted from specimens collected from mammals often produces reads that are not mapped (i.e. unmapped reads) on the host reference genome and that are usually discarded as by-products of the experiments. In this study, we mined Ion Torrent reads obtained by sequencing DNA isolated from archived blood samples collected from 100 performance tested Italian Large White pigs. Two reduced representation libraries were prepared from two DNA pools constructed each from 50 equimolar DNA samples. Bioinformatic analyses were carried out to mine unmapped reads on the reference pig genome that were obtained from the two NGS datasets. In silico analyses included read mapping and sequence assembly approaches for a viral metagenomic analysis using the NCBI Viral Genome Resource. Our approach identified sequences matching several viruses of the Parvoviridae family: porcine parvovirus 2 (PPV2), PPV4, PPV5 and PPV6 and porcine bocavirus 1-H18 isolate (PBoV1-H18). The presence of these viruses was confirmed by PCR and Sanger sequencing of individual DNA samples. PPV2, PPV4, PPV5, PPV6 and PBoV1-H18 were all identified in samples collected in 1998–2007, 1998–2000, 1997–2000, 1998–2004 and 2003, respectively. For most of these viruses (PPV4, PPV5, PPV6 and PBoV1-H18) previous studies reported their first occurrence much later (from 5 to more than 10 years) than our identification period and in different geographic areas. Our study provided a retrospective evaluation of apparently asymptomatic parvovirus infected pigs providing information that could be important to define occurrence and prevalence of different parvoviruses in South Europe. This study demonstrated the potential of mining NGS datasets non-originally derived by metagenomics experiments for viral metagenomics analyses in a livestock species.
Highlights
Generation sequencing (NGS) technologies have largely increased dimensionality of DNA sequencing projects for many different applications in all fields of biology, including the possibility to perform metagenomic studies, leading to a tremendous explosion of data that will continue increasing trend in the future [1].Metagenomics, defined as the sequencing of all nucleic acids present in a sample despite its origin, can explore complex microbial communities, including viral components, in a culture- and sequence-independent manner, overcoming the limits of traditional detection techniques (e.g. [2,3,4])
One of the most relevant challenges of viral metagenomics derives by the fact that viral sequences are usually present at a very low proportion in the analyzed specimens compared to the host DNA sequences [8]
Next generation sequencing (NGS) datasets generated from shot-gun sequencing approaches may contain reads that are derived from infecting organisms potentially transforming the original experiment in a metagenomic study even if not previously designed for this specific purpose [33]
Summary
Generation sequencing (NGS) technologies have largely increased dimensionality of DNA sequencing projects for many different applications in all fields of biology, including the possibility to perform metagenomic studies, leading to a tremendous explosion of data that will continue increasing trend in the future [1].Metagenomics, defined as the sequencing of all nucleic acids present in a sample despite its origin (e.g. environmental, specimen-derived), can explore complex microbial communities, including viral components, in a culture- and sequence-independent manner, overcoming the limits of traditional detection techniques (e.g. [2,3,4]). Generation sequencing (NGS) technologies have largely increased dimensionality of DNA sequencing projects for many different applications in all fields of biology, including the possibility to perform metagenomic studies, leading to a tremendous explosion of data that will continue increasing trend in the future [1]. Metagenomics, defined as the sequencing of all nucleic acids present in a sample despite its origin (e.g. environmental, specimen-derived), can explore complex microbial communities, including viral components, in a culture- and sequence-independent manner, overcoming the limits of traditional detection techniques One of the most relevant challenges of viral metagenomics derives by the fact that viral sequences are usually present at a very low proportion in the analyzed specimens compared to the host DNA sequences [8]. Common viral metagenomic approaches include viral particles or viral nucleic acid enrichment steps or other analytical procedures that reduce or remove non-viral DNA [2]
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