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Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies.
Rollin, Johan; Bester, Rachelle; Brostaux, Yves; Caglayan, Kadriye; De Jonghe, Kris; Eichmeier, Ales; Foucart, Yoika; Haegeman, Annelies; Koloniuk, Igor; Kominek, Petr; Maree, Hans; Onder, Serkan; Posada Céspedes, Susana; Roumi, Vahid; Safárová, Dana; Schumpp, Olivier; Ulubas Serce, Cigdem; Sõmera, Merike; Tamisier, Lucie; Vainio, Eeva; van der Vlugt, Rene Aa; Massart, Sebastien.
Afiliación
  • Rollin J; Laboratory of Plant Pathology-TERRA-Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
  • Bester R; Citrus Research International, Matieland, South Africa.
  • Brostaux Y; Department of Genetics, Stellenbosch University, Matieland, South Africa.
  • Caglayan K; Laboratory of Statistics, Computer Science and Modelling Applied to Bioengineering, TERRA, Gembloux Agro-Bio Tech, Teaching and Research Centre, University of Liège, Gembloux, Belgium.
  • De Jonghe K; Plant Protection Department, Agricultural Faculty, Hatay Mustafa Kemal University, Hatay, Turkey.
  • Eichmeier A; Fisheries and Food (ILVO), Plant Sciences Unit, Flanders Research Institute for Agriculture, Merelbeke, Belgium.
  • Foucart Y; Mendeleum-Institute of Genetics, Faculty of Horticulture, Mendel University in Brno, Lednice, Czech Republic.
  • Haegeman A; Fisheries and Food (ILVO), Plant Sciences Unit, Flanders Research Institute for Agriculture, Merelbeke, Belgium.
  • Koloniuk I; Fisheries and Food (ILVO), Plant Sciences Unit, Flanders Research Institute for Agriculture, Merelbeke, Belgium.
  • Kominek P; Biology Centre CAS, Ceske Budejovice, Czech Republic.
  • Maree H; Crop Research Institute, Praha, Czech Republic.
  • Onder S; Citrus Research International, Matieland, South Africa.
  • Posada Céspedes S; Department of Genetics, Stellenbosch University, Matieland, South Africa.
  • Roumi V; Department of Plant Protection, Faculty of Agriculture, Eskisehir Osmangazi University, Eskisehir, Turkey.
  • Safárová D; Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland.
  • Schumpp O; Swiss Institute of Bioinformatics (SIB), Basel, Switzerland.
  • Ulubas Serce C; Plant Protection Department, Faculty of Agriculture, University of Maragheh, Maragheh, Iran.
  • Sõmera M; Department of Cell Biology and Genetics, Faculty of Science, Palacký University Olomouc, Olomouc, Czech Republic.
  • Tamisier L; Plant Protection Department, Agroscope, Nyon, Switzerland.
  • Vainio E; Plant Production and Technologies Department, Ayhan Sahenk Faculty of Agricultural Science and Technologies, Nigde Ömer Halisdemir University, Nigde, Turkey.
  • van der Vlugt RA; Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia.
  • Massart S; Pathologie Végétale, Institut National de la Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), Montfavet, France.
PeerJ ; 11: e15816, 2023.
Article en En | MEDLINE | ID: mdl-37601254
Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Polimorfismo de Nucleótido Simple / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: PeerJ Año: 2023 Tipo del documento: Article País de afiliación: Bélgica Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Polimorfismo de Nucleótido Simple / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: PeerJ Año: 2023 Tipo del documento: Article País de afiliación: Bélgica Pais de publicación: Estados Unidos