Sequence-independent characterization of viruses based on the pattern of viral small RNAs produced by the host

Aguiar, Eric Roberto Guimarães Rocha; Olmo, Roenick Proveti; Paro, Simona; Ferreira, Flávia V; Faria, Isaque João da Silva de; Todjro, Yaovi Mathias Honore; Lobo, Francisco Pereira; Kroon, Erna Geessien; Meignin, Carine; Gatherer, Derek; Imler, Jean‐Luc; Marques, João Trindade

doi:10.1093/nar/gkw044

Cited by 22 publications

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“…All 5 negative control contigs with unclear or no RNA signature only aligned significantly to non-viral proteins (S3 Table). Together, these results illustrate the use of Metavisitor to implement a sequence-independent strategy based on siRNAs for virus identification [12,13]. …”

Section: Resultsmentioning

confidence: 90%

“…Several teams have used siRNA signature (a peak at 21 nt in the size distribution of re-aligned small RNA sequences) as an alternate approach to sequence similarity to identify contigs of potential viral origin [12,13]. In order to further illustrate the flexibility of Metavisitor for implementing this strategy, we built a workflow (S10 Fig) to realign ERP012577 small RNA sequences to Oases contigs of length higher than 300 nt and to generate in batch read maps and read size distributions for these contigs using the “Generate readmap and histograms from alignment files” tool (S1 Table).…”

Section: Resultsmentioning

confidence: 99%

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Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

et al. 2017

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Metavisitor is a software package that allows biologists and clinicians without specialized bioinformatics expertise to detect and assemble viral genomes from deep sequence datasets. The package is composed of a set of modular bioinformatic tools and workflows that are implemented in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions.

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Section: Resultsmentioning

confidence: 90%

Section: Resultsmentioning

confidence: 99%

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

et al. 2017

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“…To meet this challenge, the community of insect immunologists can take advantage of new tools that are becoming available. For example, the genomic revolution is rapidly increasing the number of sequenced insect genomes and leading to the discovery of novel viruses [1– 3,15]. Thus, genomic data mining of divergent insect-viral pairs can help identify viral escape mechanisms and reveal novel antiviral pathways.…”

Section: Discussionmentioning

confidence: 99%

“…RNAi refers to a series of mechanisms of gene regulation mediated by small RNAs associated with proteins of the Argonaute family that drive degradation of viral RNA in a sequence specific manner [13]. In insects, two distinct types of virus-derived small RNAs, small interfering RNAs (siRNAs) and piwi-interacting RNAs (piRNAs), have been detected in vivo [14,15]. …”

Section: General Overview Of Antiviral Pathways In Insectsmentioning

confidence: 99%

The diversity of insect antiviral immunity: insights from viruses

Marques

Imler

2016

Current Opinion in Microbiology

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Insects represent over 70% of all animal species. Recent virome analyses reveal unprecedented genetic diversity of insect viruses, which appears to match that of their hosts. Thus, insect-virus interactions may provide information on a vast repertoire of antiviral immune mechanisms. Tapping into this diversity is challenging because of several constraints imposed by the uniqueness of each insect model. Nevertheless, it is clear that many conserved and divergent pathways participate in the control of viral infection in insects. Co-evolution between hosts and viruses favors the development of immune evasion mechanisms by the pathogen. Viral suppressors can offer unique perspective on host pathways and emphasize the importance of RNA interference, apoptosis, but also NF-κB pathways and translation control in insect antiviral immunity.

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“…Although vsRNAs are commonly observed in different organisms, their relative abundance can vary substantially . In insects, for example, viral sequences are 10‐fold enriched in the small RNA fraction compared to what was observed in the long RNA pool from infected cells . In contrast, viral sequences in lungs of infected mice were underrepresented by a factor of 100 in the pool of small compared with long RNAs .…”

Section: Introductionmentioning

confidence: 99%

Virus‐derived small RNAs: molecular footprints of host–pathogen interactions

2016

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Viruses are obligatory intracellular parasites that require the host machinery to replicate. During their replication cycle, viral RNA intermediates can be recognized and degraded by different antiviral mechanisms that include RNA decay, RNA interference, and RNase L pathways. As a consequence of viral RNA degradation, infected cells can accumulate virus-derived small RNAs at high levels compared to cellular molecules. These small RNAs are imprinted with molecular characteristics that reflect their origin. First, small RNAs can be used to reconstruct viral sequences and identify the virus from which they originated. Second, other molecular features of small RNAs such as size, polarity, and base preferences depend on the type of viral substrate and host mechanism of degradation. Thus, the pattern of small RNAs generated in infected cells can be used as a molecular footprint to identify and characterize viruses independent on sequence homology searches against known references. Hence, sequencing of small RNAs obtained from infected cells enables virus discovery and characterization using both sequence-dependent strategies and novel pattern-based approaches. Recent studies are helping unlock the full application of small RNA sequencing for virus discovery and characterization. WIREs RNA 2016, 7:824-837. doi: 10.1002/wrna.1361 For further resources related to this article, please visit the WIREs website.

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Sequence-independent characterization of viruses based on the pattern of viral small RNAs produced by the host

Cited by 22 publications

References 0 publications

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

The diversity of insect antiviral immunity: insights from viruses

Virus‐derived small RNAs: molecular footprints of host–pathogen interactions

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