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Highly effective mlo-based powdery mildew resistance in hexaploid wheat without pleiotropic effects

2023· article· en· W4383218820 on OpenAlexfundno aff
Christina Rønn Ingvardsen, Julio A. Massange‐Sánchez, Finn Borum, Winnie S. Füchtbauer, Merethe Bagge, Søren Knudsen, Per L. Gregersen

Bibliographic record

VenuePlant Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y TecnologíaGrønt Udviklings- og Demonstrations ProgramMinistry of Agriculture and Food
KeywordsPowdery mildewBiologyMildewMutantGeneticsPlant disease resistanceResistance (ecology)MutationGeneBotanyAgronomy

Abstract

fetched live from OpenAlex

Application of the mlo-based resistance in barley against powdery mildew attacks is a major success in crop breeding, since it confers durable disease resistance. Resistance caused by mutations in the Mlo gene seems to be ubiquitous across a range of species. This work addresses the introduction of mlo-based resistance into hexaploid wheat, which is complicated by the occurrence of three homoeologous genes: Mlo-A1, Mlo-B1 and Mlo-D1. EMS-generated mutant plants were screened for mutations in the three homoeologues. We selected and combined 6, 8, and 4 mutations, respectively, to obtain triple homozygous mlo mutant lines. Twenty-four mutant lines showed highly effective resistance towards attack by the powdery mildew pathogen under field conditions. All 18 mutations appeared to contribute to resistance; however, they had different effects on the occurrence of symptoms such as chlorotic and necrotic spots, which are pleiotropic to the mlo-based powdery mildew resistance. We conclude that to obtain highly effective powdery mildew resistance in wheat and to avoid detrimental pleiotropic effects, all three Mlo homoeologues should be mutated; however, at least one of the mutations should be of the weaker type in order to alleviate strong pleiotropic effects from the other mutations.

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)0.001
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 score0.860
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.012
GPT teacher head0.219
Teacher spread0.208 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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