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Record W1484417316 · doi:10.1111/mpp.12113

Transcriptome analyses suggest a disturbance of iron homeostasis in soybean leaves during white mould disease establishment

2013· article· en· W1484417316 on OpenAlex
Bernarda Calla, Laureen Blahut‐Beatty, Lisa Koziol, Daina H. Simmonds, Steven J. Clough

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Plant Pathology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaU.S. Department of Agriculture
KeywordsBiologyTranscriptomeGeneGene expressionPhenylpropanoidPathogenMicroarrayGenetics

Abstract

fetched live from OpenAlex

Sclerotinia sclerotiorum is a serious pathogen of numerous crops around the world. The major virulence factor of this pathogen is oxalic acid (OA). Mutants that cannot produce OA do not cause disease, and plants that express enzymes that degrade OA, such as oxalate oxidase (OxO), are very resistant to S. sclerotiorum. To examine the effect of OA on plants, we infiltrated soybean leaves with 5 mm OA and examined the gene expression changes at 2 h post-infiltration. By comparing the gene expression levels between leaves of a transgenic soybean carrying an OxO gene (OxO) and its parent AC Colibri (AC) infiltrated with OA (pH 2.4) or water (pH 2.4 or 5.5), we were able to compare the effects of OA dependent or independent of its pH. Gene expression by microarray analysis identified 2390 genes that showed changes in expression, as determined using an overall F-test P-value cut-off of 0.001. The additional requirement that at least one pairwise t-test false discovery rate (FDR)-corrected P value should be less than 0.001 reduced the list of the most highly significant differentially expressed genes to 1054. Independent of pH, OA altered the expression levels of 78 genes, with ferritin showing the strongest induction by OA. The combination of OA plus its low pH caused 1045 genes (99% of all significant genes) to be differentially expressed, with many of the up-regulated genes being related to basal defence, such as genes of the phenylpropanoid pathway and various cytochrome P450s. RNA-seq was also conducted on four samples: OxO and AC genotypes infiltrated with either OA pH 2.4 or water pH 2.4. The RNA-seq analysis also identified ferritin paralogues as being strongly induced by OA. As the expression of ferritin, a gene that encodes for an iron storage protein, is induced by free iron, these results suggest that S. sclerotiorum benefits from the ability of OA to free iron from plant proteins, as this induces host cell death, and also allows the uptake and assimilation of the iron for its own metabolic needs.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.015
GPT teacher head0.216
Teacher spread0.201 · 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