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Record W4410451784 · doi:10.5376/pgt.2024.15.0018

Cloning, Functional Analysis, and Breeding Application of the Powdery Mildew Resistance Gene <i>MlWE74</i> in Wheat

2024· article· en· W4410451784 on OpenAlexvenueno aff
Feng Huang, Xiaoyu Du, Shaokui Zou, Lina Wang

Bibliographic record

VenuePlant Gene and Trait · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
FundersModern Agricultural Technology Industry System of Shandong province
KeywordsPowdery mildewCloning (programming)BiologyGeneticsResistance (ecology)GeneAgronomyBiotechnologyComputer science

Abstract

fetched live from OpenAlex

The MlWE74  gene, a novel powdery mildew resistance gene, has garnered widespread attention for its potential to enhance disease resistance in wheat. This study provides a comprehensive summary of the positional cloning, functional analysis, and breeding application of the wheat powdery mildew resistance gene MlWE74 . A systematic analysis of the cloning strategy, functional mechanisms, and its application in molecular breeding was conducted, evaluating its contributions to disease resistance improvement and its practical value in modern wheat breeding. The findings reveal that the MlWE74  gene holds significant potential for use in wheat disease resistance breeding. Its functional analysis and breeding applications will further advance the development of resistant wheat varieties. Future research should focus on in-depth studies of the MlWE74  gene, combining gene editing and multi-gene resistance strategies to enhance its breeding efficiency. The successful cloning and functional analysis of the MlWE74  gene offer new perspectives and tools for the development of powdery mildew-resistant wheat varieties. With the advancement of genome selection, marker-assisted breeding, and gene editing technologies, the application of MlWE74  is expected to greatly improve disease resistance in wheat varieties, contributing to global food security.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.185
Teacher spread0.174 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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