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Record W2752072354 · doi:10.1371/journal.pone.0184095

The transcriptional landscape of Rhizoctonia solani AG1-IA during infection of soybean as defined by RNA-seq

2017· article· en· W2752072354 on OpenAlexafffund
Tanya Copley, Raj Duggavathi, Suha Jabaji

Bibliographic record

VenuePLoS ONE · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRhizoctonia solaniBiologyGeneRNA-SeqPathosystemPlant disease resistanceGeneticsMicrobiologyTranscriptomeGene expressionBotany

Abstract

fetched live from OpenAlex

Rhizoctonia solani Kühn infects most plant families and can cause significant agricultural yield losses worldwide; however, plant resistance to this disease is rare and short-lived, and therefore poorly understood, resulting in the use of chemical pesticides for its control. Understanding the functional responses of this pathogen during host infection can help elucidate the molecular mechanisms that are necessary for successful host invasion. Using the pathosystem model soybean-R. solani anastomosis group AG1-IA, we examined the global transcriptional responses of R. solani during early and late infection stages of soybean by applying an RNA-seq approach. Approximately, 148 million clean paired-end reads, representing 93% of R. solani AG1-IA genes, were obtained from the sequenced libraries. Analysis of R. solani AG1-IA transcripts during soybean invasion revealed that most genes were similarly expressed during early and late infection stages, and only 11% and 15% of the expressed genes were differentially expressed during early and late infection stages, respectively. Analyses of the differentially expressed genes (DEGs) revealed shifts in molecular pathways involved in antibiotics biosynthesis, amino acid and carbohydrate metabolism, as well as pathways involved in antioxidant production. Furthermore, several KEGG pathways were unique to each time point, particularly the up-regulation of genes related to toxin degradation (e.g., nicotinate and nicotinamid metabolism) at onset of necrosis, and those linked to synthesis of anti-microbial compounds and pyridoxine (vitamin B6) biosynthesis 24 h.p.o. of necrosis. These results suggest that particular genes or pathways are required for either invasion or disease development. Overall, this study provides the first insights into R. solani AG1-IA transcriptome responses to soybean invasion providing beneficial information for future targeted control methods of this successful pathogen.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.210
Teacher spread0.186 · 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 designObservational
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

Citations28
Published2017
Admission routes2
Has abstractyes

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