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Record W4225937846 · doi:10.5376/rgg.2022.13.0003

Variation and Functional Markers of Xa23 Promoter of Rice Bacterial Blight Resistance Gene

2022· article· en· W4225937846 on OpenAlexvenueno aff
Dandan Zhang, Yulong Fan, Xiang‐Yun Ji, Zhihui Xia

Bibliographic record

VenueRice Genomics and Genetics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogenic Bacteria Studies
Canadian institutionsnot available
Fundersnot available
KeywordsXanthomonas oryzaeGeneBiologyAlleleGeneticsBacterial blightHaplotypePromoterGene expression

Abstract

fetched live from OpenAlex

Xa23 is a dominant gene with broad spectrum and strong resistance to bacterial blight of rice. The functional difference between Xa23 and the allele susceptible gene xa23 lies in the 28 bp core sequence on the promoter that is recognized and activated by the avirulent effector avrXa23 of Xanthomonas oryzae pv. Oryzae (EBEavrXa23) and development of Xa23 functional markers can speed up the process of rice breeding. In this study, the Xa23 promoters of 43 wild rice and 7 representative conventional rice were tested, and the 200 bp sequence upstream of the promoter was analyzed using Vector NTI . The results showed that only 9 common wild rice and 2 conventional rice could amplify about 200 bp sequence upstream of promoter, and the detection rate was only 22.0%, indicating that Xa23 was not widespread in rice. Further sequence analysis showed that there were abundant variations in the sequence of EBE avrXa23 , with at least seven haplotypes in its allele sequence, but EBE avrXa23 only exists in rice CBB23. Finally, the Xa23 dominant functional marker was developed based on the sequence of EBE avrXa23 . It was verified that the marker could clearly distinguish whether there was Xa23 gene in rice. This study will be helpful to further study the evolution mechanism of Xa23 and molecular mark assisted 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.169
Teacher spread0.157 · 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 designObservational
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

Citations1
Published2022
Admission routes1
Has abstractyes

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