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Record W3087450541 · doi:10.1094/pdis-08-20-1662-pdn

First Report of Grapevine Rupestris Vein Feathering Virus in Grapevines from Washington State

2020· article· en· W3087450541 on OpenAlexaboutno aff
Nomatter Chingandu, Sridhar Jarugula, Jati Adiputra, Basavaraj Bagewadi, Raphael O. Adegbola, Chandrasekhar Thammina, R. A. Naidu

Bibliographic record

VenuePlant Disease · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersWashington State Department of AgricultureWashington State University
KeywordsBiologyVitis viniferaGenBankCultivarHorticultureGenusVinePlant virusBotanyVirusGeneticsGene

Abstract

fetched live from OpenAlex

Since the first report of grapevine rupestris vein feathering virus (GRVFV; genus Marafivirus, family Tymoviridae) in a Greek grapevine causing chlorotic discoloration of leaf veins (El Beaino et al., 2001), GRVFV was reported in some European countries, and in Australia, China, Korea, New Zealand, Uruguay, and Canada (Blouin et al., 2017; Cho et al., 2018; Reynard et al., 2017). In the USA, the virus was reported only from California in vines showing Syrah decline symptoms (Al Rwahnih et al., 2009). During virus surveys conducted between 2015 and 2019, 424 samples (petioles from individual or composite of five vines, with 4 petioles/vine) with and without discernible symptoms were collected randomly from 39 Vitis vinifera cultivars in vineyards and nurseries in eastern Washington State. Total RNA was isolated from these samples separately using SpectrumTM Plant Total RNA Kit (Sigma-Aldrich) and subjected individually to Illumina RNAseq (Huntsman Cancer Institute, Salt Lake City, UT). An average of ~28 million 120-base pair (bp) paired-end reads using HiSeq2500 platform and an average of ~18 million 145-bp paired-end reads using Novaseq 6000 platform were obtained per sample. The contigs from de novo assembly of quality-filtered reads from each sample (CLC Genomics workbench 12) were subjected to BLASTn analysis against the virus database from GenBank. In addition to grapevine viruses and viroids previously reported in Washington State, GRVFV-specific sequences were obtained in samples from 11 of the 39 cultivars; namely, Muscat Ottonel, Pinot gris and Sangiovese from vineyards and Aglianico, Bonarda, Cabernet Sauvignon, Chardonnay, Garnacha Tinta, Riesling, Tempranillo and Valdiguie from nurseries. BLASTn analysis of the 73 GRVFV-specific contigs, ranging in size between 500 nt and 6474 nt, showed sequence identity between 79.4% and 95.5% with GRVFV sequences deposited in GenBank. The data also revealed that GRVFV was always present as coinfection with one or more viruses and viroids (grapevine leafroll-associated virus 3, grapevine red blotch virus, grapevine virus A and B, grapevine rupestris stem pitting-associated virus, hop stunt viroid and grapevine yellow speckle viroid 1) making it difficult to correlate presence of the virus with specific symptoms. To confirm the presence of GRVFV, samples from cvs. Sangiovese (n = 45) and Pinot gris (n = 1) were tested by RT-PCR using custom designed primers SaF-215 (5'- TACAAGGTGAATTGCTCCACAC -3') and SaR-1027 (5'-TCATTGGCGATGCGTTCG-3') to amplify the 813 bp sequence covering partial replicase associated polyprotein region of the virus genome. Sanger sfour amplicons (MT782067-MT782070) showed identities from 86% (700 bp out of 813 bp) with an Australian isolate (MT084811.1) to 90.9% (738 bp out of 813 bp) with an isolate from New Zealand (MF000326.1). Additional studies are in progress to examine the etiology, genetic diversity and impact of GRVFV in Washington vineyards.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.237
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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