Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies

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dc.authoridMaree, Hano/0000-0001-9639-4558
dc.authoridEichmeier, Ales/0000-0001-7358-3903
dc.authoridULUBAS SERCE, CIGDEM/0000-0001-5337-5883
dc.authoridvan der Vlugt, Rene/0000-0001-9094-685X
dc.authoridTamisier, Lucie/0000-0002-9231-2997
dc.authoridDe Jonghe, Kris/0000-0003-1763-5654
dc.authoridHaegeman, Annelies/0000-0002-8192-5368
dc.contributor.authorRollin, Johan
dc.contributor.authorBester, Rachelle
dc.contributor.authorBrostaux, Yves
dc.contributor.authorCaglayan, Kadriye
dc.contributor.authorDe Jonghe, Kris
dc.contributor.authorEichmeier, Ales
dc.contributor.authorFoucart, Yoika
dc.date.accessioned2024-09-18T20:04:28Z
dc.date.available2024-09-18T20:04:28Z
dc.date.issued2023
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractRecent 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.en_US
dc.description.sponsorshipCOST (European Cooperation in Science and Technology); European Union [FA1407]; [813542T]en_US
dc.description.sponsorshipThis study is the follow-up of the work on COST Action FA1407 (DIVAS) , supported by COST (European Cooperation in Science and Technology) . This was supported by European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 813542T (INEXTVIR) . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en_US
dc.identifier.doi10.7717/peerj.15816
dc.identifier.issn2167-8359
dc.identifier.pmid37601254en_US
dc.identifier.scopus2-s2.0-85172734988en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.7717/peerj.15816
dc.identifier.urihttps://hdl.handle.net/20.500.12483/8195
dc.identifier.volume11en_US
dc.identifier.wosWOS:001053389700002en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherPeerj Incen_US
dc.relation.ispartofPeerjen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBioinformaticen_US
dc.subjectGenomicen_US
dc.subjectVirusen_US
dc.subjectPlanten_US
dc.subjectVarianten_US
dc.titleDetection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategiesen_US
dc.typeArticleen_US

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