Transcriptome Analysis and Functional Identification of <i>Xa13</i> and <i>Pi‐ta</i> Orthologs in <i>Oryza granulata</i>
Bibliographic record
Abstract
Nees & Arn. ex Watt, a perennial wild rice species with a GG genome, preserves many important genes for cultivated rice ( L.) improvement. At present, however, no genetic resource is available for studying . Here, we report 91,562 high-quality transcripts of assembled de novo. Moreover, comparative transcriptome analysis revealed that 1311 single-copy orthologous pairs shared by and (Zoll. & Moritzi) Baill. that may have undergone adaptive evolution. We performed an analysis of the genes potentially involved in plant-pathogen interactions to explore the molecular basis of disease resistance, and isolated the full-length cDNAs of () and () orthologs from . The overexpression of in Nipponbare and functional characterization showed enhanced the resistance of transgenic Nipponbare to rice blast resulting from the presence of the gene. , an alternatively spliced transcript of the blast resistance gene in encodes a 1024-amino acid polypeptide with a C-terminal thioredoxin domain. This study provides an important resource for functional and evolutionary studies of the genus .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".