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Record W4284709701 · doi:10.21203/rs.3.rs-1807889/v1

An unusual tandem kinase fusion protein confers leaf rust resistance in wheat

2022· preprint· en· W4284709701 on OpenAlexaff
Yajun Wang, Michaël Abrouk, Spyridon Gourdoupis, Dal‐Hoe Koo, Miroslava Karafiátová, István Molnár, Jaroslav Doležel, Naveenkumar Athiyannan, Emile Cavalet-Giorsa, Łukasz Jaremko, Jesse Poland, Simon G. Krattinger

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsKootenay Association for Science & Technology
FundersNational Research, Development and Innovation OfficeEuropean Regional Development FundHorizon 2020 Framework ProgrammeKing Abdullah University of Science and TechnologyNational Science Foundation
KeywordsChromosomal translocationBiologyGeneGeneticsPlant disease resistanceIntrogression

Abstract

fetched live from OpenAlex

Abstract The introgression of chromosome segments from wild relatives is an established strategy to enrich crop germplasm with novel disease resistance genes. Here, we use mutagenesis and transcriptome sequencing to clone the leaf rust resistance gene Lr9, which was introduced into bread wheat from the wild grass species Aegilops umbellulata. We establish that Lr9 encodes an unusual tandem kinase fusion protein. Long-read sequencing of a wheat Lr9 introgression line and the putative Ae. umbellulata Lr9 donor enabled us to assemble the ~28.4-Mb Lr9 translocation and to identify the translocation breakpoint. We likewise cloned Lr58, which was reportedly introgressed from Ae. triuncialis, but has an identical coding sequence compared to Lr9. Cytogenetic and haplotype analyses corroborate that the two genes originate from the same translocation event. Our work sheds light on the emerging role of kinase fusion proteins in wheat disease resistance, expanding the repertoire of disease resistance genes for breeding.

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 score0.005

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)0.0020.001

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 head0.071
GPT teacher head0.350
Teacher spread0.279 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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