Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported, but little attention has been paid so far to their sensitivity and reliability for diagnostic purposes. We therefore compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large scale performance test ten datasets of 21-24 nt small (s)RNA sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty to detect viral agents when they are novel and/or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases and (iv) the significant level of scientific expertise needed when interpreting pipelines results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.
Little cherry virus 1 (LChV1, Velarivirus, Closteroviridae) is a widespread pathogen of sweet or sour cherry and other Prunus species, which exhibits high genetic diversity and lacks a putative efficient transmission vector. Thus far, four distinct phylogenetic clusters of LChV1 have been described, including isolates from different Prunus species. The recent application of high throughput sequencing (HTS) technologies in fruit tree virology has facilitated the acquisition of new viral genomes and the study of virus diversity. In the present work, several new LChV1 isolates from different countries were fully sequenced using different HTS approaches. Our results reveal the presence of further genetic diversity within the LChV1 species. Interestingly, mixed infections of the same sweet cherry tree with different LChV1 variants were identified for the first time. Taken together, the high intra-host and intra-species diversities of LChV1 might affect its pathogenicity and have clear implications for its accurate diagnostics.
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