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Record W1936727819 · doi:10.1111/mpp.12105

An avirulence gene, <i> <scp>AvrLmJ1</scp> </i> , from the blackleg fungus, <i> <scp>L</scp> eptosphaeria maculans </i> , confers avirulence to <i> <scp>B</scp> rassica juncea </i> cultivars

2013· article· en· W1936727819 on OpenAlexfundno aff
Angela P. Van de Wouw, Rohan G. T. Lowe, Candace E. Elliott, David J. Dubois, Barbara J. Howlett

Bibliographic record

VenueMolecular Plant Pathology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaGrains Research and Development Corporation
KeywordsLeptosphaeria maculansBlacklegBiologyGeneGeneticsComplementationGenomeBrassicaBotanyMutant

Abstract

fetched live from OpenAlex

The fungus Leptosphaeria maculans causes blackleg of Brassica species. Here, we report the mapping and subsequent cloning of an avirulence gene from L. maculans. This gene, termed AvrLmJ1, confers avirulence towards all three Brassica juncea cultivars tested. Analysis of RNA-seq data showed that AvrLmJ1 is housed in a region of the L. maculans genome which contains only one gene that is highly expressed in planta. The closest genes are 57 and 33 kb away and, like other avirulence genes of L. maculans, AvrLmJ1 is located within an AT-rich, gene-poor region of the genome. The encoded protein is 141 amino acids, has a predicted signal peptide and is cysteine rich. Two virulent isolates contain a premature stop codon in AvrLmJ1. Complementation of an isolate that forms cotyledonary lesions on B. juncea with the wild-type allele of AvrLmJ1 confers avirulence towards all three B. juncea cultivars tested, suggesting that the gene may confer species-specific avirulence activity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

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 integrity0.0000.001
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 head0.011
GPT teacher head0.211
Teacher spread0.199 · 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 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

Citations105
Published2013
Admission routes1
Has abstractyes

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