Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies
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 dete...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2020
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| Acceso en línea: | http://hdl.handle.net/20.500.11939/6314 https://apsjournals.apsnet.org/doi/10.1094/PHYTO-02-18-0067-R |
| _version_ | 1855492060417622016 |
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| author | Massart, Sebastien Chiumenti, Michela De-Jonghe, Kris Glover, Rachel Haegeman, Annelies Koloniuk, Igor Kominek, Petr Kreuze, Jan Kutnjak, Denis Lotos, Leonidas Maclot, Francois Maliogka, Varvara Maree, Hans J. Olivier, Thibaut Olmos, Antonio Pooggin, Mikhail M. Reynard, Jean-Sebastien Ruiz-García, Ana B. Safarova, Dana Schneeberger, Pierre H. Sela, Noa Turco, Silvia Vainio, Eeva J. Varallyay, Eva Verdin, Eric Westenberg, Marcel Brostaux, Yves Candresse, Thierry |
| author_browse | Brostaux, Yves Candresse, Thierry Chiumenti, Michela De-Jonghe, Kris Glover, Rachel Haegeman, Annelies Koloniuk, Igor Kominek, Petr Kreuze, Jan Kutnjak, Denis Lotos, Leonidas Maclot, Francois Maliogka, Varvara Maree, Hans J. Massart, Sebastien Olivier, Thibaut Olmos, Antonio Pooggin, Mikhail M. Reynard, Jean-Sebastien Ruiz-García, Ana B. Safarova, Dana Schneeberger, Pierre H. Sela, Noa Turco, Silvia Vainio, Eeva J. Varallyay, Eva Verdin, Eric Westenberg, Marcel |
| author_facet | Massart, Sebastien Chiumenti, Michela De-Jonghe, Kris Glover, Rachel Haegeman, Annelies Koloniuk, Igor Kominek, Petr Kreuze, Jan Kutnjak, Denis Lotos, Leonidas Maclot, Francois Maliogka, Varvara Maree, Hans J. Olivier, Thibaut Olmos, Antonio Pooggin, Mikhail M. Reynard, Jean-Sebastien Ruiz-García, Ana B. Safarova, Dana Schneeberger, Pierre H. Sela, Noa Turco, Silvia Vainio, Eeva J. Varallyay, Eva Verdin, Eric Westenberg, Marcel Brostaux, Yves Candresse, Thierry |
| author_sort | Massart, Sebastien |
| collection | ReDivia |
| description | 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 thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we 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 using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) 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 in detecting viral agents when they are novel 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 pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses. |
| format | Artículo |
| id | ReDivia6314 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| record_format | dspace |
| spelling | ReDivia63142025-04-25T14:46:50Z Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies Massart, Sebastien Chiumenti, Michela De-Jonghe, Kris Glover, Rachel Haegeman, Annelies Koloniuk, Igor Kominek, Petr Kreuze, Jan Kutnjak, Denis Lotos, Leonidas Maclot, Francois Maliogka, Varvara Maree, Hans J. Olivier, Thibaut Olmos, Antonio Pooggin, Mikhail M. Reynard, Jean-Sebastien Ruiz-García, Ana B. Safarova, Dana Schneeberger, Pierre H. Sela, Noa Turco, Silvia Vainio, Eeva J. Varallyay, Eva Verdin, Eric Westenberg, Marcel Brostaux, Yves Candresse, Thierry 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 thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we 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 using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) 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 in detecting viral agents when they are novel 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 pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses. 2020-02-21T11:51:31Z 2020-02-21T11:51:31Z 2019 article publishedVersion Massart, S., Chiumenti, M., De Jonghe, K., Glover, R., Haegeman, A., Koloniuk, I., . . . Candresse, T. (2019). Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies. Phytopathology, 109(3), 488-497. 0031-949X http://hdl.handle.net/20.500.11939/6314 10.1094/PHYTO-02-18-0067-R https://apsjournals.apsnet.org/doi/10.1094/PHYTO-02-18-0067-R en openAccess electronico |
| spellingShingle | Massart, Sebastien Chiumenti, Michela De-Jonghe, Kris Glover, Rachel Haegeman, Annelies Koloniuk, Igor Kominek, Petr Kreuze, Jan Kutnjak, Denis Lotos, Leonidas Maclot, Francois Maliogka, Varvara Maree, Hans J. Olivier, Thibaut Olmos, Antonio Pooggin, Mikhail M. Reynard, Jean-Sebastien Ruiz-García, Ana B. Safarova, Dana Schneeberger, Pierre H. Sela, Noa Turco, Silvia Vainio, Eeva J. Varallyay, Eva Verdin, Eric Westenberg, Marcel Brostaux, Yves Candresse, Thierry Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies |
| title | Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies |
| title_full | Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies |
| title_fullStr | Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies |
| title_full_unstemmed | Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies |
| title_short | Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies |
| title_sort | virus detection by high throughput sequencing of small rnas large scale performance testing of sequence analysis strategies |
| url | http://hdl.handle.net/20.500.11939/6314 https://apsjournals.apsnet.org/doi/10.1094/PHYTO-02-18-0067-R |
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