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Record W2998172734 · doi:10.3390/pathogens9010027

The Notorious Soilborne Pathogenic Fungus Sclerotinia sclerotiorum: An Update on Genes Studied with Mutant Analysis

2019· review· en· W2998172734 on OpenAlexafffund
Shitou Xia, Yan Xu, Ryan Hoy, Julia Zhang, Lei Qin, Xin Li

Bibliographic record

VenuePathogens · 2019
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsSclerotinia sclerotiorumBiologyAscosporeFungusMyceliumAscocarpFungal pathogenMutantVirulencePathogenic fungusAppressoriumGeneAscomycotaSclerotiniaPathogenConidiationGeneticsMicrobiologyBotanySpore

Abstract

fetched live from OpenAlex

Ascomycete Sclerotinia sclerotiorum (Lib.) de Bary is one of the most damaging soilborne fungal pathogens affecting hundreds of plant hosts, including many economically important crops. Its genomic sequence has been available for less than a decade, and it was recently updated with higher completion and better gene annotation. Here, we review key molecular findings on the unique biology and pathogenesis process of S. sclerotiorum, focusing on genes that have been studied in depth using mutant analysis. Analyses of these genes have revealed critical players in the basic biological processes of this unique pathogen, including mycelial growth, appressorium establishment, sclerotial formation, apothecial and ascospore development, and virulence. Additionally, the synthesis has uncovered gaps in the current knowledge regarding this fungus. We hope that this review will serve to build a better current understanding of the biology of this under-studied notorious soilborne pathogenic fungus.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.051
GPT teacher head0.262
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations71
Published2019
Admission routes2
Has abstractyes

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