Comparison of Serological and Molecular Methods With High-Throughput Sequencing for the Detection and Quantification of Grapevine Fanleaf Virus in Vineyard Samples.
Identifieur interne : 000210 ( Main/Corpus ); précédent : 000209; suivant : 000211Comparison of Serological and Molecular Methods With High-Throughput Sequencing for the Detection and Quantification of Grapevine Fanleaf Virus in Vineyard Samples.
Auteurs : Emmanuelle Vigne ; Shahinez Garcia ; Véronique Komar ; Olivier Lemaire ; Jean-Michel HilySource :
- Frontiers in microbiology [ 1664-302X ] ; 2018.
Abstract
Grapevine fanleaf virus (GFLV) is the main causal agent of fanleaf degeneration, the most damaging viral disease of grapevine. GFLV is included in most grapevine certification programs that rely on robust diagnostic tools such as biological indexing, serological methods, and molecular techniques, for the identification of clean stocks. The emergence of high throughput sequencing (HTS) offers new opportunities for detecting GFLV and other viruses in grapevine accessions of interest. Here, two HTS-based methods, i.e., RNAseq and smallRNAseq (focusing on the 21 to 27 nt) were explored for their potential to characterize the virome of grapevine samples from two 30-year-old GFLV-infected vineyards in the Champagne region of France. smallrnaseq was optimal for the detection of a wide range of viral species within a sample and RNAseq was the method of choice for full-length viral genome assembly. The implementation of a protocol to discriminate between low GFLV titer and in silico contamination (intra-lane contamination due to index misassignment) during data processing was critical for data analyses. Furthermore, we compared the performance of semi-quantitative DAS-ELISA (double antibody enzyme-linked immunosorbent assay), RT-qPCR (Reverse transcription-quantitative polymerase chain reaction), Immuno capture (IC)-RT-PCR, northern blot for viral small interfering RNA (vsiRNA) detection and RNAseq for the detection and quantification of GFLV. While detection limits were variable among methods, as expected, GFLV diagnosis was consistently achieved with all of these diagnostic methods. Together, this work highlights the robustness of DAS-ELISA, the current method routinely used in the French grapevine certification program, for the detection of GFLV and offers perspectives on the potential of HTS as an approach of high interest for certification.
DOI: 10.3389/fmicb.2018.02726
PubMed: 30524388
PubMed Central: PMC6262039
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GFLV is included in most grapevine certification programs that rely on robust diagnostic tools such as biological indexing, serological methods, and molecular techniques, for the identification of clean stocks. The emergence of high throughput sequencing (HTS) offers new opportunities for detecting GFLV and other viruses in grapevine accessions of interest. Here, two HTS-based methods, <i>i.e.</i>, RNAseq and smallRNAseq (focusing on the 21 to 27 nt) were explored for their potential to characterize the virome of grapevine samples from two 30-year-old GFLV-infected vineyards in the Champagne region of France. smallrnaseq was optimal for the detection of a wide range of viral species within a sample and RNAseq was the method of choice for full-length viral genome assembly. The implementation of a protocol to discriminate between low GFLV titer and <i>in silico</i> contamination (intra-lane contamination due to index misassignment) during data processing was critical for data analyses. Furthermore, we compared the performance of semi-quantitative DAS-ELISA (double antibody enzyme-linked immunosorbent assay), RT-qPCR (Reverse transcription-quantitative polymerase chain reaction), Immuno capture (IC)-RT-PCR, northern blot for viral small interfering RNA (vsiRNA) detection and RNAseq for the detection and quantification of GFLV. While detection limits were variable among methods, as expected, GFLV diagnosis was consistently achieved with all of these diagnostic methods. Together, this work highlights the robustness of DAS-ELISA, the current method routinely used in the French grapevine certification program, for the detection of GFLV and offers perspectives on the potential of HTS as an approach of high interest for certification.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">30524388</PMID><DateRevised><Year>2020</Year><Month>10</Month><Day>01</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1664-302X</ISSN><JournalIssue CitedMedium="Print"><Volume>9</Volume><PubDate><Year>2018</Year></PubDate></JournalIssue><Title>Frontiers in microbiology</Title><ISOAbbreviation>Front Microbiol</ISOAbbreviation></Journal><ArticleTitle>Comparison of Serological and Molecular Methods With High-Throughput Sequencing for the Detection and Quantification of Grapevine Fanleaf Virus in Vineyard Samples.</ArticleTitle><Pagination><MedlinePgn>2726</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3389/fmicb.2018.02726</ELocationID><Abstract><AbstractText>Grapevine fanleaf virus (GFLV) is the main causal agent of fanleaf degeneration, the most damaging viral disease of grapevine. GFLV is included in most grapevine certification programs that rely on robust diagnostic tools such as biological indexing, serological methods, and molecular techniques, for the identification of clean stocks. The emergence of high throughput sequencing (HTS) offers new opportunities for detecting GFLV and other viruses in grapevine accessions of interest. Here, two HTS-based methods, <i>i.e.</i>, RNAseq and smallRNAseq (focusing on the 21 to 27 nt) were explored for their potential to characterize the virome of grapevine samples from two 30-year-old GFLV-infected vineyards in the Champagne region of France. smallrnaseq was optimal for the detection of a wide range of viral species within a sample and RNAseq was the method of choice for full-length viral genome assembly. The implementation of a protocol to discriminate between low GFLV titer and <i>in silico</i> contamination (intra-lane contamination due to index misassignment) during data processing was critical for data analyses. Furthermore, we compared the performance of semi-quantitative DAS-ELISA (double antibody enzyme-linked immunosorbent assay), RT-qPCR (Reverse transcription-quantitative polymerase chain reaction), Immuno capture (IC)-RT-PCR, northern blot for viral small interfering RNA (vsiRNA) detection and RNAseq for the detection and quantification of GFLV. While detection limits were variable among methods, as expected, GFLV diagnosis was consistently achieved with all of these diagnostic methods. Together, this work highlights the robustness of DAS-ELISA, the current method routinely used in the French grapevine certification program, for the detection of GFLV and offers perspectives on the potential of HTS as an approach of high interest for certification.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Vigne</LastName><ForeName>Emmanuelle</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>L'UMR Santé de la Vigne et Qualité du Vin, INRA-Université de Strasbourg, Colmar, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Garcia</LastName><ForeName>Shahinez</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>L'UMR Santé de la Vigne et Qualité du Vin, INRA-Université de Strasbourg, Colmar, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Komar</LastName><ForeName>Véronique</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>L'UMR Santé de la Vigne et Qualité du Vin, INRA-Université de Strasbourg, Colmar, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lemaire</LastName><ForeName>Olivier</ForeName><Initials>O</Initials><AffiliationInfo><Affiliation>L'UMR Santé de la Vigne et Qualité du Vin, INRA-Université de Strasbourg, Colmar, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hily</LastName><ForeName>Jean-Michel</ForeName><Initials>JM</Initials><AffiliationInfo><Affiliation>L'UMR Santé de la Vigne et Qualité du Vin, INRA-Université de Strasbourg, Colmar, France.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2018</Year><Month>11</Month><Day>22</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Front 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