Villamor, D.E.V.; Ho, T.; Al Rwahnih, M.; Martin, R.R.; Tzanetakis, I.E. High throughput sequencing for plant virus detection and discovery. Phytopathology 2019, 109, 716–725, doi:10.1094/PHYTO‐07‐18‐0257‐RVW.
Kreuze, J.F.; Perez, A.; Untiveros, M.; Quispe, D.; Fuentes, S.; Barker, I.; Simon, R. Complete viral genome sequence and discovery of novel viruses by deep sequencing of small RNAs: A generic method for diagnosis, discovery and sequencing of viruses. Virology 2009, 388, 1–7, doi:10.1016/j.virol.2009.03.024.
Adams, I.P.; Glover, R.H.; Monger, W.A.; Mumford, R.; Jackeviciene, E.; Navalinskiene, M.; Samuitiene, M.; Boonham, N. Next-generation sequencing and metagenomic analysis: A universal diagnostic tool in plant virology. Mol. Plant Pathol. 2009, 10, 537– 545, doi:10.1111/j.1364‐3703.2009.00545.x.
Al Rwahnih, M.; Daubert, S.; Golino, D.; Rowhani, A. Deep sequencing analysis of RNAs from a grapevine showing syrah decline symptoms reveals a multiple virus infection that includes a novel virus. Virology 2009, 387, 395–401, doi:10.1016/j.vi-rol.2009.02.028.
Donaire, L.; Wang, Y.; Gonzalez‐Ibeas, D.; Mayer, K.F.; Aranda, M.A.; Llave, C. Deep‐sequencing of plant viral small RNAs reveals effective and widespread targeting of viral genomes. Virology 2009, 392, 203–214, doi:10.1016/j.virol.2009.07.005.
Massart, S.; Chiumenti, M.; De Jonghe, K.; Glover, R.; Haegeman, A.; Koloniuk, I.; Komínek, P.; Kreuze, J.; Kutnjak, D.; Lotos, L.; et al. Virus detection by high‐throughput sequencing of small RNAs: Large‐scale performance testing of sequence analysis strategies. Phytopathology 2019, 109, 488–497, doi:10.1094/PHYTO‐02‐18‐0067‐R.
Olmos, A.; Boonham, N.; Candresse, T.; Gentit, P.; Giovani, B.; Kutnjak, D.; Liefting, L.; Maree, H.J.; Minafra, A.; Moreira, A.; et al. High‐throughput sequencing technologies for plant pest diagnosis: Challenges and opportunities. EPPO Bull. 2018, 48, 219– 224, doi:10.1111/epp.12472.
Weymann, D.; Laskin, J.; Roscoe, R.; Schrader, K.A.; Chia, S.; Yip, S.; Cheung, W.Y.; Gelmon, K.A.; Karsan, A.; Renouf, D.J.; et al. The cost and cost trajectory of whole‐genome analysis guiding treatment of patients with advanced cancers. Mol. Genet. Genomic Med. 2017, 5, 251–260, doi:10.1002/mgg3.281.
Valitest EU Project Consortium Guidelines for the Selection, Development, Validation and Routine Use of High‐Throughput Sequencing Analysis in Plant Health Diagnostic Laboratories: Grant Agreement N. 773139: Deliverable N° 2.2. (Confidential). 2020. Available online: https://www.valitest.eu/work_packages/(accessed on 13 April 2021).
Maliogka, V.I.; Minafra, A.; Saldarelli, P.; Ruiz‐García, A.B.; Glasa, M.; Katis, N.; Olmos, A. Recent advances on detection and characterization of fruit tree viruses using high‐throughput sequencing technologies. Viruses 2018, 10, 436, doi:10.3390/v10080436.
Roossinck, M.J. Deep sequencing for discovery and evolutionary analysis of plant viruses. Virus Res. 2017, 239, 82–86, doi:10.1016/j.virusres.2016.11.019.
Roossinck, M.J.; Martin, D.P.; Roumagnac, P. Plant virus metagenomics: Advances in virus discovery. Phytopathology 2015, 105, 716–727, doi:10.1094/PHYTO‐12‐14‐0356‐RVW.
Marais, A.; Faure, C.; Bergey, B.; Candresse, T. Viral double‐stranded RNAs (dsRNAs) from plants: Alternative nucleic acid substrates for high‐throughput sequencing. In Viral Metagenomics: Methods and Protocols; Pantaleo, V., Chiumenti, M., Eds.; Hu-mana Press: New York, NY, USA, 2018; pp. 45–53, ISBN 978‐1‐4939‐7682‐9.
Massart, S.; Olmos, A.; Jijakli, H.; Candresse, T. Current impact and future directions of high throughput sequencing in plant virus diagnostics. Virus Res. 2014, 188, 90–96, doi:10.1016/j.virusres.2014.03.029.
Pecman, A.; Kutnjak, D.; Gutiérrez‐Aguirre, I.; Adams, I.; Fox, A.; Boonham, N.; Ravnikar, M. Next generation sequencing for detection and discovery of plant viruses and viroids: Comparison of two approaches. Front. Microbiol. 2017, 8, doi:10.3389/fmicb.2017.01998.
Boone, M.; De Koker, A.; Callewaert, N. Survey and summary capturing the “ome”: The expanding molecular toolbox for RNA and DNA library construction. Nucleic Acids Res. 2018, 46, 2701–2721, doi:10.1093/nar/gky167.
Visser, M.; Bester, R.; Burger, J.T.; Maree, H.J. Next‐generation sequencing for virus detection: Covering all the bases. Virol. J. 2016, 13, 4–9, doi:10.1186/s12985‐016‐0539‐x.
Idris, A.; Al‐Saleh, M.; Piatek, M.J.; Al‐Shahwan, I.; Ali, S.; Brown, J.K. Viral metagenomics: Analysis of begomoviruses by illumina high‐throughput sequencing. Viruses 2014, 6, 1219–1236, doi:10.3390/v6031219.
Sukal, A.C.; Kidanemariam, D.B.; Dale, J.L.; Harding, R.M.; James, A.P. Assessment and optimization of rolling circle amplification protocols for the detection and characterization of badnaviruses. Virology 2019, 529, 73–80, doi:10.1016/j.virol.2019.01.013.
Wyant, P.S.; Strohmeier, S.; Schäfer, B.; Krenz, B.; Assunção, I.P.; de Andrade Lima, G.S.; Jeske, H. Circular DNA genomics (circomics) exemplified for geminiviruses in bean crops and weeds of northeastern Brazil. Virology 2012, 427, 151–157, doi:10.1016/j.virol.2012.02.007.
Vivek, A.T.; Zahra, S.; Kumar, S. From current knowledge to best practice: A primer on viral diagnostics using deep sequencing of virus‐derived small interfering RNAs (vsiRNAs) in infected plants. Methods 2020, 183, 30–37, doi:10.1016/j.ymeth.2019.10.009.
Kutnjak, D.; Rupar, M.; Gutierrez‐Aguirre, I.; Curk, T.; Kreuze, J.F.; Ravnikar, M. Deep sequencing of virus‐derived small interfering RNAs and RNA from viral particles shows highly similar mutational landscapes of a plant virus population. J. Virol. 2015, 89, 4760–4769, doi:10.1128/JVI.03685‐14.
Seguin, J.; Rajeswaran, R.; Malpica‐López, N.; Martin, R.R.; Kasschau, K.; Dolja, V.V.; Otten, P.; Farinelli, L.; Pooggin, M.M. De novo reconstruction of consensus master genomes of plant RNA and DNA viruses from siRNAs. PLoS ONE 2014, 9, e88513, doi:10.1371/journal.pone.0088513.
Smith, O.; Clapham, A.; Rose, P.; Liu, Y.; Wang, J.; Allaby, R.G. A complete ancient RNA genome: Identification, reconstruction and evolutionary history of archaeological Barley Stripe Mosaic Virus. Sci. Rep. 2014, 4, 4003, doi:10.1038/srep04003.
Turco, S.; Golyaev, V.; Seguin, J.; Gilli, C.; Farinelli, L.; Boller, T.; Schumpp, O.; Pooggin, M.M. Small RNA‐omics for virome reconstruction and antiviral defense characterization in mixed infections of cultivated solanum plants. Mol. Plant‐Microbe Inter-act. 2018, 31, 707–723, doi:10.1094/MPMI‐12‐17‐0301‐R.
Melcher, U.; Muthukumar, V.; Wiley, G.B.; Min, B.E.; Palmer, M.W.; Verchot‐Lubicz, J.; Ali, A.; Nelson, R.S.; Roe, B.A.; Thapa, V.; et al. Evidence for novel viruses by analysis of nucleic acids in virus‐like particle fractions from Ambrosia psilostachya. J. Virol. Methods 2008, 152, 49–55, doi:10.1016/j.jviromet.2008.05.030.
Muthukumar, V.; Melcher, U.; Pierce, M.; Wiley, G.B.; Roe, B.A.; Palmer, M.W.; Thapa, V.; Ali, A.; Ding, T. Non‐cultivated plants of the tallgrass prairie preserve of northeastern oklahoma frequently contain virus‐like sequences in particulate fractions. Virus Res. 2009, 141, 169–173, doi:10.1016/j.virusres.2008.06.016.
Bernardo, P.; Charles‐Dominique, T.; Barakat, M.; Ortet, P.; Fernandez, E.; Filloux, D.; Hartnady, P.; Rebelo, T.A.; Cousins, S.R.; Mesleard, F.; et al. Geometagenomics illuminates the impact of agriculture on the distribution and prevalence of plant viruses at the ecosystem scale. ISME J. 2018, 12, 173–184, doi:10.1038/ismej.2017.155.
Filloux, D.; Dallot, S.; Delaunay, A.; Galzi, S.; Jacquot, E.; Roumagnac, P. Metagenomics approaches based on virion‐associated nucleic acids (VANA): An innovative tool for assessing without a priori viral diversity of plants. Methods Mol. Biol. 2015, 1302, 249–257, doi:10.1007/978‐1‐4939‐2620‐6_18.
Ma, Y.; Marais, A.; Lefebvre, M.; Theil, S.; Svanella‐Dumas, L.; Faure, C.; Candresse, T. Phytovirome analysis of wild plant populations: Comparison of double‐stranded rna and virion‐associated nucleic acid metagenomic approaches. J. Virol. 2019, 94, doi:10.1128/jvi.01462‐19.
Roossinck, M.J. Plants, viruses and the environment: Ecology and mutualism. Virology 2015, 479–480, 271–277, doi:10.1016/j.vi-rol.2015.03.041.
Hull, R. Origins and evolution of plant viruses. In Plant Virology; Elsevier: London, UK, 2014; pp. 423–476.
Al Rwahnih, M.; Daubert, S.; Golino, D.; Islas, C.; Rowhani, A. Comparison of next‐generation sequencing versus biological indexing for the optimal detection of viral pathogens in grapevine. Phytopathology 2015, 105, 758–763, doi:10.1094/PHYTO‐06‐ 14‐0165‐R.
Kesanakurti, P.; Belton, M.; Saeed, H.; Rast, H.; Boyes, I.; Rott, M. Screening for plant viruses by next generation sequencing using a modified double strand RNA extraction protocol with an internal amplification control. J. Virol. Methods 2016, 236, 35– 40, doi:10.1016/j.jviromet.2016.07.001.
Loconsole, G.; Saldarelli, P.; Doddapaneni, H.; Savino, V.; Martelli, G.P.; Saponari, M. Identification of a single‐stranded DNA virus associated with citrus chlorotic dwarf disease, a new member in the family geminiviridae. Virology 2012, 432, 162–172, doi:10.1016/j.virol.2012.06.005.
Rott, M.; Xiang, Y.; Boyes, I.; Belton, M.; Saeed, H.; Kesanakurti, P.; Hayes, S.; Lawrence, T.; Birch, C.; Bhagwat, B.; et al. Application of next generation sequencing for diagnostic testing of tree fruit viruses and viroids. Plant Dis. 2017, 101, 1489–1499, doi:10.1094/PDIS‐03‐17‐0306‐RE.
Weber, F.; Wagner, V.; Rasmussen, S.B.; Hartmann, R.; Paludan, S.R. Double‐stranded RNA is produced by positive‐strand RNA viruses and DNA viruses but not in detectable amounts by negative‐strand RNA viruses. J. Virol. 2006, 80, 5059–5064, doi:10.1128/jvi.80.10.5059‐5064.2006.
Gaafar, Y.Z.A.; Ziebell, H. Comparative study on three viral enrichment approaches based on RNA extraction for plant virus/vi-roid detection using high‐throughput sequencing. PLoS ONE 2020, 15, e0237951, doi:10.1371/journal.pone.0237951.
Thapa, V.; McGlinn, D.J.; Melcher, U.; Palmer, M.W.; Roossinck, M.J. Determinants of taxonomic composition of plant viruses at the nature conservancy’s tallgrass prairie preserve, Oklahoma. Virus Evol. 2015, 1, vev007, doi:10.1093/ve/vev007.
Blouin, A.G.; Ross, H.A.; Hobson‐Peters, J.; O’Brien, C.A.; Warren, B.; MacDiarmid, R. A new virus discovered by immunocap-ture of double‐stranded RNA, a rapid method for virus enrichment in metagenomic studies. Mol. Ecol. Resour. 2016, 16, 1255– 1263, doi:10.1111/1755‐0998.12525.
Kobayashi, K.; Tomita, R.; Sakamoto, M. Recombinant plant dsRNA‐binding protein as an effective tool for the isolation of viral replicative form dsRNA and universal detection of RNA viruses. J. Gen. Plant Pathol. 2009, 75, 87–91, doi:10.1007/s10327‐009‐ 0155‐3.
Chalupowicz, L.; Dombrovsky, A.; Gaba, V.; Luria, N.; Reuven, M.; Beerman, A.; Lachman, O.; Dror, O.; Nissan, G.; Manulis‐ Sasson, S. Diagnosis of plant diseases using the nanopore sequencing platform. Plant Pathol. 2019, 68, 229–238, doi:10.1111/ppa.12957.
Lusk, R.W. Diverse and widespread contamination evident in the unmapped depths of high throughput sequencing data. PLoS ONE 2014, 9, e110808, doi:10.1371/journal.pone.0110808.
Laurence, M.; Hatzis, C.; Brash, D.E. Common contaminants in next‐generation sequencing that hinder discovery of low‐abun-dance microbes. PLoS ONE 2014, 9, e97876, doi:10.1371/journal.pone.0097876.
Schmieder, R.; Edwards, R. Fast identification and removal of sequence contamination from genomic and metagenomic da-tasets. PLoS ONE 2011, 6, e17288, doi:10.1371/journal.pone.0017288.
Naccache, S.N.; Greninger, A.L.; Lee, D.; Coffey, L.L.; Phan, T.; Rein‐Weston, A.; Aronsohn, A.; Hackett, J.; Delwart, E.L.; Chiu, C.Y. The perils of pathogen discovery: Origin of a novel parvovirus‐like hybrid genome traced to nucleic acid extraction spin columns. J. Virol. 2013, 87, 11966–11977, doi:10.1128/JVI.02323‐13.
Martin, M. Cutadapt removes adapter sequences from high‐throughput sequencing reads. EMBnet. J. 2011, 17, 10, doi:10.14806/ej.17.1.200.
Illumina bcl2fastq and bcl2fastq2 Conversion Software. v.2.20; Illumina: San Diego, CA, USA, 2019. Available online: https://emea.support.illumina.com/sequencing/sequencing_software/bcl2fastq‐conversion‐software.html (accessed on 13 April 2021).
Oxford Nanopore Technologies Guppy: Local Accelerated Basecalling for Nanopore Data. Available online: https://commu-nity.nanoporetech.com/downloads (accessed on 13 April 2021).
Illumina Effects of Index Misassignment on Multiplexing and Downstream Analysis (770‐2017‐004‐D). Available online: https://www.illumina.com/content/dam/illumina‐marketing/documents/products/whitepapers/index‐hopping‐white‐paper‐ 770‐2017‐004.pdf (accessed on 13 April 2021).
van der Valk, T.; Vezzi, F.; Ormestad, M.; Dalén, L.; Guschanski, K. Index hopping on the Illumina HiseqX platform and its consequences for ancient DNA studies. Mol. Ecol. Resour. 2020, 20, 1171–1181, doi:10.1111/1755‐0998.13009.
MacConaill, L.E.; Burns, R.T.; Nag, A.; Coleman, H.A.; Slevin, M.K.; Giorda, K.; Light, M.; Lai, K.; Jarosz, M.; McNeill, M.S.; et al. Unique, dual‐indexed sequencing adapters with UMIs effectively eliminate index cross‐talk and significantly improve sen-sitivity of massively parallel sequencing. BMC Genom. 2018, 19, 30, doi:10.1186/s12864‐017‐4428‐5.
Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114– 2120, doi:10.1093/bioinformatics/btu170.
Wick, B. Porechop. Available online: https://github.com/rrwick/Porechop (accessed on 13 April 2021).
De Coster, W.; D’Hert, S.; Schultz, D.T.; Cruts, M.; Van Broeckhoven, C. NanoPack: Visualizing and processing long‐read sequencing data. Bioinformatics 2018, 34, 2666–2669, doi:10.1093/bioinformatics/bty149.
Cock, P.J.A.; Fields, C.J.; Goto, N.; Heuer, M.L.; Rice, P.M. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 2009, 38, 1767–1771, doi:10.1093/nar/gkp1137.
Andrews, S. FastQC. Availible online: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/(accessed on 13 April 2021).
Ewels, P.; Magnusson, M.; Lundin, S.; Käller, M. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics 2016, 32, 3047–3048, doi:10.1093/bioinformatics/btw354.
Loman, N.J.; Quinlan, A.R. Poretools: A toolkit for analyzing nanopore sequence data. Bioinformatics 2014, 30, 3399–3401, doi:10.1093/bioinformatics/btu555.
Najoshi Sickle—A Windowed Adaptive Trimming Tool for FASTQ Files Using Quality. Available online: https://github.com/najoshi/sickle (accessed on 13 April 2021).
Paszkiewicz, K.; Studholme, D.J. De novo assembly of short sequence reads. Brief. Bioinform. 2010, 11, 457–472, doi:10.1093/bib/bbq020.
Sohn, J.‐I.; Nam, J.‐W. The present and future of de novo whole‐genome assembly. Brief. Bioinform. 2018, 19, 23–40, doi:10.1093/bib/bbw096.
Luo, R.; Liu, B.; Xie, Y.; Li, Z.; Huang, W.; Yuan, J.; He, G.; Chen, Y.; Pan, Q.; Liu, Y.; et al. SOAPdenovo2: An empirically improved memory‐efficient short‐read de novo assembler. Gigascience 2012, 1, 2047‐217X‐1‐18, doi:10.1186/2047‐217X‐1‐18.
Gnerre, S.; MacCallum, I.; Przybylski, D.; Ribeiro, F.J.; Burton, J.N.; Walker, B.J.; Sharpe, T.; Hall, G.; Shea, T.P.; Sykes, S.; et al. High‐quality draft assemblies of mammalian genomes from massively parallel sequence data. Proc. Natl. Acad. Sci. USA 2011, 108, 1513–1518, doi:10.1073/pnas.1017351108.
Simpson, J.T.; Wong, K.; Jackman, S.D.; Schein, J.E.; Jones, S.J.M.; Birol, I. ABySS: A parallel assembler for short read sequence data. Genome Res. 2009, 19, 1117–1123, doi:10.1101/gr.089532.108.
Zerbino, D.R.; Birney, E. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008, 18, 821– 829, doi:10.1101/gr.074492.107.
Peng, Y.; Leung, H.C.M.; Yiu, S.M.; Chin, F.Y.L. IDBA‐UD: A de novo assembler for single‐cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 2012, 28, 1420–1428, doi:10.1093/bioinformatics/bts174.
Bankevich, A.; Nurk, S.; Antipov, D.; Gurevich, A.A.; Dvorkin, M.; Kulikov, A.S.; Lesin, V.M.; Nikolenko, S.I.; Pham, S.; Prjibel-ski, A.D.; et al. SPAdes: A new genome assembly algorithm and its applications to single‐cell sequencing. J. Comput. Biol. 2012, 19, 455–477, doi:10.1089/cmb.2012.0021.
Nurk, S.; Bankevich, A.; Antipov, D.; Gurevich, A.A.; Korobeynikov, A.; Lapidus, A.; Prjibelski, A.D.; Pyshkin, A.; Sirotkin, A.; Sirotkin, Y.; et al. Assembling single‐cell genomes and mini‐metagenomes from chimeric MDA products. J. Comput. Biol. 2013, 20, 714–737, doi:10.1089/cmb.2013.0084.
Bushmanova, E.; Antipov, D.; Lapidus, A.; Prjibelski, A.D. RnaSPAdes: A de novo transcriptome assembler and its application to RNA‐Seq data. Gigascience 2019, 8, giz100, doi:10.1093/gigascience/giz100.
Rang, F.J.; Kloosterman, W.P.; de Ridder, J. From squiggle to basepair: Computational approaches for improving nanopore sequencing read accuracy. Genome Biol. 2018, 19, 90, doi:10.1186/s13059‐018‐1462‐9.
Koren, S.; Schatz, M.C.; Walenz, B.P.; Martin, J.; Howard, J.T.; Ganapathy, G.; Wang, Z.; Rasko, D.A.; McCombie, W.R.; Jarvis, E.D.; et al. Hybrid error correction and de novo assembly of single‐molecule sequencing reads. Nat. Biotechnol. 2012, 30, 693– 700, doi:10.1038/nbt.2280.
Koren, S.; Walenz, B.P.; Berlin, K.; Miller, J.R.; Bergman, N.H.; Phillippy, A.M. Canu: Scalable and accurate long‐read assembly via adaptive κ‐mer weighting and repeat separation. Genome Res. 2017, 27, 722–736, doi:10.1101/gr.215087.116.
Oxford Nanopore Technologies Pomoxis—Bioinformatics Tools for Nanopore Research. Available online: https://github.com/nanoporetech/pomoxis (accessed on 13 April 2021).
Li, H.; Durbin, R. Fast and accurate short read alignment with burrows‐wheeler transform. Bioinformatics 2009, 25, 1754–1760, doi:10.1093/bioinformatics/btp324.
Stobbe, A.H.; Daniels, J.; Espindola, A.S.; Verma, R.; Melcher, U.; Ochoa‐Corona, F.; Garzon, C.; Fletcher, J.; Schneider, W. E‐ probe diagnostic nucleic acid analysis (EDNA): A theoretical approach for handling of next generation sequencing data for diagnostics. J. Microbiol. Methods 2013, 94, 356–366, doi:10.1016/j.mimet.2013.07.002.
Punta, M.; Coggill, P.C.; Eberhardt, R.Y.; Mistry, J.; Tate, J.; Boursnell, C.; Pang, N.; Forslund, K.; Ceric, G.; Clements, J.; et al. The Pfam protein families database. Nucleic Acids Res. 2012, 40, 290–301, doi:10.1093/nar/gkr1065.
Marchler‐Bauer, A.; Panchenko, A.R.; Shoemarker, B.A.; Thiessen, P.A.; Geer, L.Y.; Bryant, S.H. CDD: A database of conserved domain alignments with links to domain three‐dimensional structure. Nucleic Acids Res. 2002, 30, 281–283, doi:10.1093/nar/30.1.281.
Agranovsky, A.A.; Boyko, V.P.; Karasev, A.V.; Koonin, E.V.; Dolja, V.V. Putative 65 kDa protein of beet yellows closterovirus is a homologue of HSP70 heat shock proteins. J. Mol. Biol. 1991, 217, 603–610, doi:10.1016/0022‐2836(91)90517‐A.
Amselem, J.; Cornut, G.; Choisne, N.; Alaux, M.; Alfama‐Depauw, F.; Jamilloux, V.; Maumus, F.; Letellier, T.; Luyten, I.; Pom-mier, C.; et al. RepetDB: A unified resource for transposable element references. Mob. DNA 2019, 10, 6, doi:10.1186/s13100‐019‐ 0150‐y.
Geering, A.D.W.; Maumus, F.; Copetti, D.; Choisne, N.; Zwickl, D.J.; Zytnicki, M.; McTaggart, A.R.; Scalabrin, S.; Vezzulli, S.; Wing, R.A.; et al. Endogenous florendoviruses are major components of plant genomes and hallmarks of virus evolution. Nat. Commun. 2014, 5, 5269, doi:10.1038/ncomms6269.
Diop, S.I.; Geering, A.D.W.; Alfama‐Depauw, F.; Loaec, M.; Teycheney, P.‐Y.; Maumus, F. Tracheophyte genomes keep track of the deep evolution of the caulimoviridae. Sci. Rep. 2018, 8, 572, doi:10.1038/s41598‐017‐16399‐x.
Sharma, V.; Lefeuvre, P.; Roumagnac, P.; Filloux, D.; Teycheney, P.‐Y.; Martin, D.P.; Maumus, F. Large‐scale survey reveals pervasiveness and potential function of endogenous geminiviral sequences in plants. Virus Evol. 2020, 6, veaa071, doi:10.1093/ve/veaa071.
Tangherlini, M.; Dell’Anno, A.; Zeigler Allen, L.; Riccioni, G.; Corinaldesi, C. Assessing viral taxonomic composition in benthic marine ecosystems: Reliability and efficiency of different bioinformatic tools for viral metagenomic analyses. Sci. Rep. 2016, 6, 28428, doi:10.1038/srep28428.
Buchfink, B.; Xie, C.; Huson, D.H. Fast and sensitive protein alignment using diamond. Nat. Methods 2014, 12, 59–60, doi:10.1038/nmeth.3176.
Langmead, B.; Trapnell, C.; Pop, M.; Salzberg, S.L. Ultrafast and memory‐efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009, 10, R25, doi:10.1186/gb‐2009‐10‐3‐r25.
Hong, C.; Manimaran, S.; Shen, Y.; Perez‐Rogers, J.F.; Byrd, A.L.; Castro‐Nallar, E.; Crandall, K.A.; Johnson, W.E. PathoScope 2.0: A complete computational framework for strain identification in environmental or clinical sequencing samples. Microbiome 2014, 2, 33, doi:10.1186/2049‐2618‐2‐33.
Mistry, J.; Finn, R.D.; Eddy, S.R.; Bateman, A.; Punta, M. Challenges in homology search: HMMER3 and convergent evolution of coiled‐coil regions. Nucleic Acids Res. 2013, 41, e121, doi:10.1093/nar/gkt263.
Skewes‐Cox, P.; Sharpton, T.J.; Pollard, K.S.; DeRisi, J.L. Profile hidden Markov models for the detection of viruses within met-agenomic sequence data. PLoS ONE 2014, 9, e105067, doi:10.1371/journal.pone.0105067.
Bzhalava, Z.; Hultin, E.; Dillner, J. Extension of the viral ecology in humans using viral profile hidden Markov models. PLoS ONE 2018, 13, e0190938, doi:10.1371/journal.pone.0190938.
Wood, D.E.; Lu, J.; Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 2019, 20, 257, doi:10.1186/s13059‐ 019‐1891‐0.
Menzel, P.; Ng, K.L.; Krogh, A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat. Commun. 2016, 7, 11257, doi:10.1038/ncomms11257.
Flygare, S.; Simmon, K.; Miller, C.; Qiao, Y.; Kennedy, B.; Di Sera, T.; Graf, E.H.; Tardif, K.D.; Kapusta, A.; Rynearson, S.; et al. Taxonomer: An interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profil-ing. Genome Biol. 2016, 17, 111, doi:10.1186/s13059‐016‐0969‐1.
Baizan‐Edge, A.; Cock, P.; MacFarlane, S.; McGavin, W.; Torrance, L.; Jones, S. Kodoja: A workflow for virus detection in plants using k‐mer analysis of RNA‐sequencing data. J. Gen. Virol. 2019, 100, 533–542, doi:10.1099/jgv.0.001210.
Tampuu, A.; Bzhalava, Z.; Dillner, J.; Vicente, R. ViraMiner: Deep learning on raw DNA sequences for identifying viral genomes in human samples. PLoS ONE 2019, 14, e0222271, doi:10.1371/journal.pone.0222271.
Ren, J.; Song, K.; Deng, C.; Ahlgren, N.A.; Fuhrman, J.A.; Li, Y.; Xie, X.; Poplin, R.; Sun, F. Identifying viruses from metagenomic data using deep learning. Quant. Biol. 2020, 8, 64–77, doi:10.1007/s40484‐019‐0187‐4.
Abdelkareem, A.O.; Khalil, M.I.; Elaraby, M.; Abbas, H.; Elbehery, A.H.A. VirNet: Deep attention model for viral reads identi-fication. In Proceedings of the 2018 13th International Conference on Computer Engineering and Systems (ICCES), Cairo, Egypt, 18–19 December 2018; pp. 623–626.
Ren, Y.; Xu, Y.; Lee, W.M.; Di Bisceglie, A.M.; Fan, X. In‐depth serum virome analysis in patients with acute liver failure with indeterminate etiology. Arch. Virol. 2020, 165, 127–135, doi:10.1007/s00705‐019‐04466‐9.
Li, H. Minimap2: Pairwise alignment for nucleotide sequences. Bioinformatics 2018, 34, 3094–3100, doi:10.1093/bioinformat-ics/bty191.
Warwick‐Dugdale, J.; Solonenko, N.; Moore, K.; Chittick, L.; Gregory, A.C.; Allen, M.J.; Sullivan, M.B.; Temperton, B. Long-read viral metagenomics captures abundant and microdiverse viral populations and their niche‐defining genomic islands. PeerJ 2019, 7, e6800, doi:10.7717/peerj.6800.
Lefkowitz, E.J.; Dempsey, D.M.; Hendrickson, R.C.; Orton, R.J.; Siddell, S.G.; Smith, D.B. Virus taxonomy: The database of the international committee on taxonomy of viruses (ICTV). Nucleic Acids Res. 2018, 46, D708–D717, doi:10.1093/nar/gkx932.
Davison, A.J. Journal of general virology—Introduction to ‘ICTV virus taxonomy profiles.’ J. Gen. Virol. 2017, 98, 1, doi:10.1099/jgv.0.000686.
Bao, Y.; Chetvernin, V.; Tatusova, T. Improvements to pairwise sequence comparison (PASC): A genome‐based web tool for virus classification. Arch. Virol. 2014, 159, 3293–3304, doi:10.1007/s00705‐014‐2197‐x.
Gibbs, A.J.; Hajizadeh, M.; Ohshima, K.; Jones, R.A.C. The potyviruses: An evolutionary synthesis is emerging. Viruses 2020, 12, 132, doi:10.3390/v12020132.
Jones, S.; Baizan‐Edge, A.; MacFarlane, S.; Torrance, L. Viral diagnostics in plants using next generation sequencing: Computational analysis in practice. Front. Plant Sci. 2017, 8, 1770, doi:10.3389/fpls.2017.01770.
Blawid, R.; Silva, J.M.F.; Nagata, T. Discovering and sequencing new plant viral genomes by next‐generation sequencing: Description of a practical pipeline. Ann. Appl. Biol. 2017, 170, 301–314, doi:10.1111/aab.12345.
Roenhorst, J.W.; de Krom, C.; Fox, A.; Mehle, N.; Ravnikar, M.; Werkman, A.W. Ensuring validation in diagnostic testing is fit for purpose: A view from the plant virology laboratory. EPPO Bull. 2018, 48, 105–115, doi:10.1111/epp.12445.
Simmonds, P.; Adams, M.J.; Benk, M.; Breitbart, M.; Brister, J.R.; Carstens, E.B.; Davison, A.J.; Delwart, E.; Gorbalenya, A.E.; Harrach, B.; et al. Consensus statement: Virus taxonomy in the age of metagenomics. Nat. Rev. Microbiol. 2017, 15, 161–168, doi:10.1038/nrmicro.2016.177.
Rwahnih, M.A.; Daubert, S.; Úrbez‐Torres, J.R.; Cordero, F.; Rowhani, A. Deep sequencing evidence from single grapevine plants reveals a virome dominated by mycoviruses. Arch. Virol. 2011, 156, 397–403, doi:10.1007/s00705‐010‐0869‐8.
Marzano, S.Y.L.; Domier, L.L. Novel mycoviruses discovered from metatranscriptomics survey of soybean phyllosphere phy-tobiomes. Virus Res. 2016, 213, 332–342, doi:10.1016/j.virusres.2015.11.002.
Kreuze, J. siRNA deep sequencing and assembly: Piecing together viral infections. In Detection and Diagnostics of Plant Pathogens; Gullino, M.L., Bonants, P.J.M., Eds.; Springer: Dordrecht, The Netherlands, 2014; pp. 21–38, ISBN 978‐94‐017‐9020‐8.
Massart, S.; Candresse, T.; Gil, J.; Lacomme, C.; Predajna, L.; Ravnikar, M.; Reynard, J.S.; Rumbou, A.; Saldarelli, P.; Škoric, D.; et al. A framework for the evaluation of biosecurity, commercial, regulatory, and scientific impacts of plant viruses and viroids identified by NGS technologies. Front. Microbiol. 2017, 8, 45, doi:10.3389/fmicb.2017.00045.
Kreuze, J.F.; Perez, A.; Gargurevich, M.G.; Cuellar, W.J. Badnaviruses of sweet potato: Symptomless coinhabitants on a global scale. Front. Plant Sci. 2020, 11, 313, doi:10.3389/fpls.2020.00313.
Sõmera, M.; Kvarnheden, A.; Desbiez, C.; Blystad, D.R.; Sooväli, P.; Kundu, J.K.; Gantsovski, M.; Nygren, J.; Lecoq, H.; Verdin, E.; et al. Sixty years after the first description: Genome sequence and biological characterization of European wheat striate mosaic virus infecting cereal crops. Phytopathology 2020, 110, 68–79, doi:10.1094/PHYTO‐07‐19‐0258‐FI.
Hammond, J.; Adams, I.; Fowkes, A.R.; McGreig, S.; Botermans, M.; van Oorspronk, J.J.A.; Westenberg, M.; Verbeek, M.; Dul-lemans, A.M.; Stijger, C.C.M.M.; et al. Sequence analysis of 43‐year old samples of plantago lanceolata show that plantain virus x is synonymous with actinidia virus X and is widely distributed. Plant Pathol. 2020, 249–258, doi:10.1111/ppa.13310.
Tamisier, L.; Haegeman, A.; Foucart, Y.; Fouillien, N.; Rwahnih, M.A.; Buzkan, N.; Candresse, T.; Chiumenti, M.; De Jonghe, K.; Lefebvre, M.; et al. Semi‐artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection. Zenodo 2020, 4273791, 1–15, doi:10.5281/zenodo.4584718.
Martin, D.P.; Murrell, B.; Golden, M.; Khoosal, A.; Muhire, B. RDP4: Detection and analysis of recombination patterns in virus genomes. Virus Evol. 2015, 1, vev003, doi:10.1093/ve/vev003.
Lole, K.S.; Bollinger, R.C.; Paranjape, R.S.; Gadkari, D.; Kulkarni, S.S.; Novak, N.G.; Ingersoll, R.; Sheppard, H.W.; Ray, S.C. Full‐length human immunodeficiency virus type 1 genomes from subtype c‐infected seroconverters in india, with evidence of intersubtype recombination. J. Virol. 1999, 73, 152–160, doi:10.1128/jvi.73.1.152‐160.1999.
Simmonds, P.; Midgley, S. Recombination in the genesis and evolution of hepatitis B virus genotypes. J. Virol. 2005, 79, 15467– 15476, doi:10.1128/jvi.79.24.15467‐15476.2005.
Routh, A.; Johnson, J.E. Discovery of functional genomic motifs in viruses with ViReMa‐a virus recombination mapper‐for analysis of next‐generation sequencing data. Nucleic Acids Res. 2014, 42, e11, doi:10.1093/nar/gkt916.
Xu, C.; Sun, X.; Taylor, A.; Jiao, C.; Xu, Y.; Cai, X.; Wang, X.; Ge, C.; Pan, G.; Wang, Q.; et al. Diversity, distribution, and evolution of tomato viruses in china uncovered by small RNA sequencing. J. Virol. 2017, 91, e00173‐17, doi:10.1128/JVI.00173‐17.
Bertran, A.; Ciuffo, M.; Margaria, P.; Rosa, C.; Resende, R.O.; Turina, M. Host‐specific accumulation and temperature effects on the generation of dimeric viral RNA species derived from the S‐RNA of members of the Tospovirus genus. J. Gen. Virol. 2016, 97, 3051–3062, doi:10.1099/jgv.0.000598.
Maliogka, V.I.; Salvador, B.; Carbonell, A.; Sáenz, P.; León, D.S.; Oliveros, J.C.; Delgadillo, M.O.; García, J.A.; Simón‐Mateo, C.; Progenika Biopharma, S.A. Virus variants with differences in the p1 protein coexist in a plum pox virus population and display particular host‐dependent pathogenicity features. Mol. Plant Pathol. 2012, 13, 877–886, doi:10.1111/j.1364‐3703.2012.00796.x.
da Silva, W.; Kutnjak, D.; Xu, Y.; Xu, Y.; Giovannoni, J.; Elena, S.F.; Gray, S. Transmission modes affect the population structure of potato virus Y in potato. PLoS Pathog. 2020, 16, e1008608, doi:10.1371/journal.ppat.1008608.
Saitou, N.; Nei, M. The neighbor‐joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 1987, 4, 406–425, doi:10.1093/oxfordjournals.molbev.a040454.
Guindon, S.; Dufayard, J.F.; Lefort, V.; Anisimova, M.; Hordijk, W.; Gascuel, O. New algorithms and methods to estimate max-imum‐likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst. Biol. 2010, 59, 307–321, doi:10.1093/sysbio/syq010.
Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post‐analysis of large phylogenies. Bioinformatics 2014, 30, 1312–1313, doi:10.1093/bioinformatics/btu033.
Ronquist, F.; Teslenko, M.; Van Der Mark, P.; Ayres, D.L.; Darling, A.; Höhna, S.; Larget, B.; Liu, L.; Suchard, M.A.; Huelsenbeck, J.P. Mrbayes 3.2: Efficient bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 2012, 61, 539– 542, doi:10.1093/sysbio/sys029.
Huson, D.H.; Beier, S.; Flade, I.; Górska, A.; El‐Hadidi, M.; Mitra, S.; Ruscheweyh, H.J.; Tappu, R. MEGAN Community edi-tion—Interactive exploration and analysis of large‐scale microbiome sequencing data. PLoS Comput. Biol. 2016, 12, e1004957, doi:10.1371/journal.pcbi.1004957.
Suchard, M.A.; Lemey, P.; Baele, G.; Ayres, D.L.; Drummond, A.J.; Rambaut, A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 2018, 4, vey016, doi:10.1093/ve/vey016.
Fuentes, S.; Gibbs, A.J.; Adams, I.P.; Wilson, C.; Botermans, M.; Fox, A.; Kreuze, J.; Kehoe, M.A.; Jones, R.A.C. Potato virus A isolates from three continents: Their biological properties, phylogenetics, and prehistory. Phytopathology 2021, 111, 217–226, doi:10.1094/PHYTO‐08‐20‐0354‐FI.
Hardy, O.J.; Vekemans, X. SPAGeDI: A versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol. Ecol. Notes 2002, 2, 618–620, doi:10.1046/j.1471‐8286.2002.00305.x.
Zheng, Y.; Gao, S.; Padmanabhan, C.; Li, R.; Galvez, M.; Gutierrez, D.; Fuentes, S.; Ling, K.S.; Kreuze, J.; Fei, Z. VirusDetect: An automated pipeline for efficient virus discovery using deep sequencing of small RNAs. Virology 2017, 500, 130–138, doi:10.1016/j.virol.2016.10.017.
Lefebvre, M.; Theil, S.; Ma, Y.; Candresse, T. The virannot pipeline: A resource for automated viral diversity estimation and operational taxonomy units assignation for virome sequencing data. Phytobiomes, J. 2019, 3, 256–259, doi:10.1094/PBIOMES‐07‐ 19‐0037‐A.
Ho, T.; Tzanetakis, I.E. Development of a virus detection and discovery pipeline using next generation sequencing. Virology 2014, 471–473, 54–60, doi:10.1016/j.virol.2014.09.019.
Visser, M.; Burger, J.T.; Maree, H.J. Targeted virus detection in next‐generation sequencing data using an automated e‐probe based approach. Virology 2016, 495, 122–128, doi:10.1016/j.virol.2016.05.008.
Afgan, E.; Baker, D.; Batut, B.; Van Den Beek, M.; Bouvier, D.; Ech, M.; Chilton, J.; Clements, D.; Coraor, N.; Grüning, B.A.; et al. The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 2018, 46, W537–W544, doi:10.1093/nar/gky379.
Kalantar, K.L.; Carvalho, T.; de Bourcy, C.F.A.; Dimitrov, B.; Dingle, G.; Egger, R.; Han, J.; Holmes, O.B.; Juan, Y.F.; King, R.; et al. IDseq‐An open source cloud‐based pipeline and analysis service for metagenomic pathogen detection and monitoring. Gi-gascience 2020, 9, giaa111, doi:10.1093/gigascience/giaa111.
