Isolation, characterisation and phylogenetic analysis of resistance gene analogues in a wild species of peach (<i>Prunus kansuensis</i>)
Bibliographic record
Abstract
Cao, K., Wang, L. R., Zhu, G. R., Fang, W. CH. and Chen, CH. W. 2011. Isolation, characterisation and phylogenetic analysis of resistance gene analogues in a wild species of peach ( Prunus kansuensis ). Can. J. Plant Sci. 91: 961–970. Conserved motifs, such as nucleotide binding site (NBS) and leucine-rich repeat (LRR) domains, have been found in resistance (R) genes cloned from plant species. These allow the study of plant defence mechanisms and isolating candidate genes in several species including peaches. Seventy-five resistance gene analogues (RGA) were identified using two different degenerative primer pairs in the Honggengansutao (Prunus kansuensis), a wild species of peach resistant to drought and nematodes. Through aligning their amino-acid sequences, P-loop and GLPL motifs were found in 48 RGAs with open-reading frames (ORF). These RGAs and 17 RGAs from Arabidopsis thaliana, Capsicum annuum and Solanum lycopersicum were grouped into two classes by phylogenetic analysis: toll and interleukin-1 receptor (TIR)- and non-TIR-NBS. Most Honggengansutao RGAs were TIR-NBS. A semiquantitative RT-PCR analysis revealed transcript-level variations of 22 RGAs in the young leaves, flowers, fruits and roots of the Honggengansutao, demonstrating their probable role in resistance against diseases attacking the organs. This is the first large-scale analysis of NBS-LRR RGAs in P. kansuensis, this technique has the potential for involvement in rootstock breeding. It will foster further R gene isolation and exploitation.
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 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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".