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Record W2053492299 · doi:10.1139/b09-056

Patterns of defence gene expression in the tomato–<i>Verticillium</i>interaction

2009· article· en· W2053492299 on OpenAlexaffvenue
Jane Robb, Christian Danve M. Castroverde, Hakeem Shittu, Ross N. Nazar

Bibliographic record

VenueBotany · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyGeneVerticillium dahliaeGeneticsGene expressionDNA microarrayPhenotypeVerticilliumGene expression profilingMicroarrayVerticillium wiltMicroarray analysis techniquesBotany

Abstract

fetched live from OpenAlex

In a tomato plant infected by Verticillium dahliae , race 1, compatibility or incompatibility appears to be determined in the stem, but little is known about the genes that either regulate or effect critical cellular events. In the present study, microarray and RT-PCR analyses were used to assess changes in tomato mRNA populations during both interactions. Initially, a commercially available DNA chip was used to screen gene expression at a single critical time point after inoculation of resistant and susceptible plants. From the results, the most-affected genes were selected to develop a tomato Verticillium response (TVR) DNA chip for detailed analyses of gene expression for 15 d after inoculation. Taken together, over half of the genes on the TVR array exhibited one of three distinct patterns of change, one reflecting a resistant phenotype and two being consistent with a susceptible phenotype. Of particular interest was a cluster of strongly expressed genes belonging to groups 2 and 3 that appeared to be co-ordinately down regulated in infected resistant plants relative to susceptible. Many of these genes encode pathogenesis related (PR) proteins. The data demonstrate that even though complex, the biological system can be standardized sufficiently to allow the reproducible analysis of gene expression in a whole plant system and provide patterns of transcriptional variation that can be used to assess the significance of specific genes in pathogenesis and resistance.

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 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 score0.793
Threshold uncertainty score0.143

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 head0.022
GPT teacher head0.239
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations14
Published2009
Admission routes2
Has abstractyes

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