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Record W2160724408 · doi:10.1094/mpmi-02-13-0036-r

Deletion of the <i>Phytophthora sojae</i> Avirulence Gene <i>Avr1d</i> Causes Gain of Virulence on <i>Rps</i>1d

2013· article· en· W2160724408 on OpenAlexaff
Ren Na, Dan Yu, Dinah Qutob, Jun Zhao, Mark Gijzen

Bibliographic record

VenueMolecular Plant-Microbe Interactions · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPhytophthora sojaeEffectorBiologyVirulenceOomyceteGeneGeneticsPathogenPopulationCell biology

Abstract

fetched live from OpenAlex

Phytophthora sojae is an oomycete and a pathogen of soybean that causes root rot. During infection P. sojae delivers effector proteins into host cells to foster disease. However, effector-triggered immunity (ETI) results when pathogen factors are recognized by host resistance (R) proteins. We have now identified the P. sojae Avr1d gene, which encodes a predicted effector protein with the amino acid motif Arg-X-Leu-Arg (RXLR). Genetic mapping of 16 different P. sojae isolates and of a segregating F2 population of 40 individuals shows that the predicted RXLR effector gene Avh6 precisely cosegregates with the Avr1d phenotype. Transient expression assays confirm that Avr1d triggers cell death specifically in Rps1d soybean plants. The Avr1d gene is present in P. sojae strains that are avirulent on Rps1d, whereas the gene is deleted from the genome of virulent strains. Two sequence variants of the Avr1d gene encoding different protein products occur in P. sojae strains, but both are recognized by Rps1d and cause ETI. Liposome binding assays show that Avr1d has affinity for phosphatidylinositol 4-phosphate and that binding can be disrupted by mutation of lysine residues in the carboxy-terminal effector domain of the protein. The identification of Avr1d aids pathogen diagnostics and soybean cultivar development.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.308

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 head0.010
GPT teacher head0.197
Teacher spread0.187 · 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

Citations43
Published2013
Admission routes1
Has abstractyes

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