4.6 Article

ViR: a tool to solve intrasample variability in the prediction of viral integration sites using whole genome sequencing data

Journal

BMC BIOINFORMATICS
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12859-021-03980-5

Keywords

Viral integration; Repetitive DNA; Lateral gene transfer; Non-model organisms

Funding

  1. European Research Council [ERC-CoG 682394]
  2. Italian Ministry of Education, University and Research (FARE-MIUR project) [R1623HZAH5]
  3. Human Frontier Science Program Research grant [RGP0007/2017]
  4. Dipartimenti Eccellenza Program 2018-2022

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Researchers developed the ViR pipeline to address the issues in detecting viral integration sites in non-model organisms, and validated its accuracy using both in silico and real sequencing data. ViR is expected to facilitate a deeper exploration of the biological roles and significance of EVEs in non-model organisms.
Background Several bioinformatics pipelines have been developed to detect sequences from viruses that integrate into the human genome because of the health relevance of these integrations, such as in the persistence of viral infection and/or in generating genotoxic effects, often progressing into cancer. Recent genomics and metagenomics analyses have shown that viruses also integrate into the genome of non-model organisms (i.e., arthropods, fish, plants, vertebrates). However, rarely studies of endogenous viral elements (EVEs) in non-model organisms have gone beyond their characterization from reference genome assemblies. In non-model organisms, we lack a thorough understanding of the widespread occurrence of EVEs and their biological relevance, apart from sporadic cases which nevertheless point to significant roles of EVEs in immunity and regulation of expression. The concomitance of repetitive DNA, duplications and/or assembly fragmentations in a genome sequence and intrasample variability in whole-genome sequencing (WGS) data could determine misalignments when mapping data to a genome assembly. This phenomenon hinders our ability to properly identify integration sites. Results To fill this gap, we developed ViR, a pipeline which solves the dispersion of reads due to intrasample variability in sequencing data from both single and pooled DNA samples thus ameliorating the detection of integration sites. We tested ViR to work with both in silico and real sequencing data from a non-model organism, the arboviral vector Aedes albopictus. Potential viral integrations predicted by ViR were molecularly validated supporting the accuracy of ViR results. Conclusion ViR will open new venues to explore the biology of EVEs, especially in non-model organisms. Importantly, while we generated ViR with the identification of EVEs in mind, its application can be extended to detect any lateral transfer event providing an ad-hoc sequence to interrogate.

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