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Record W2558238843 · doi:10.3389/fpls.2016.01771

Single R Gene Introgression Lines for Accurate Dissection of the Brassica - Leptosphaeria Pathosystem

2016· article· en· W2558238843 on OpenAlexafffund
Nicholas J. Larkan, Fengqun Yu, Derek J. Lydiate, S. R. Rimmer, M. Hossein Borhan

Bibliographic record

VenueFrontiers in Plant Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaAgriculture VictoriaInstitut National de la Recherche AgronomiqueCanola Council of Canada
KeywordsLeptosphaeria maculansPathosystemBlacklegIntrogressionBiologyGeneticsBrassicaGeneBotany

Abstract

fetched live from OpenAlex

Seven blackleg resistance (R) genes (Rlm1, Rlm2, Rlm3, Rlm4, LepR1, LepR2 & LepR3) were each introgressed into a common susceptible B. napus doubled-haploid (DH) line through reciprocal back-crossing, producing single-R gene introgression lines (ILs) for use in the pathological and molecular study of Brassica – Leptosphaeria interactions. The genomic positions of the R genes were defined through molecular mapping and analysis with transgenic L. maculans isolates was used to confirm the identity of the introgressed genes where possible. Using L. maculans isolates of contrasting avirulence gene (Avr) profiles, we preformed extensive differential pathology for phenotypic comparison of the ILs to other B. napus varieties, demonstrating the ILs can provide for the accurate assessment of Avr - R gene interactions by avoiding non-Avr dependant alterations to resistance responses which can occur in some commonly used B. napus varieties. Whole-genome SNP-based assessment allowed us to define the donor parent introgressions in each IL and provide a strong basis for comparative molecular dissection of the pathosystem.

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)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.212
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

Citations69
Published2016
Admission routes2
Has abstractyes

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