Sequence Variants of the Phytophthora sojae RXLR Effector Avr3a/5 Are Differentially Recognized by Rps3a and Rps5 in Soybean
Bibliographic record
Abstract
The perception of Phytophthora sojae avirulence (Avr) gene products by corresponding soybean resistance (Rps) gene products causes effector triggered immunity. Past studies have shown that the Avr3a and Avr5 genes of P. sojae are genetically linked, and the Avr3a gene encoding a secreted RXLR effector protein was recently identified. We now provide evidence that Avr3a and Avr5 are allelic. Genetic mapping data from F(2) progeny indicates that Avr3a and Avr5 co-segregate, and haplotype analysis of P. sojae strain collections reveal sequence and transcriptional polymorphisms that are consistent with a single genetic locus encoding Avr3a/5. Transformation of P. sojae and transient expression in soybean were performed to test how Avr3a/5 alleles interact with soybean Rps3a and Rps5. Over-expression of Avr3a/5 in a P. sojae strain that is normally virulent on Rps3a and Rps5 results in avirulence to Rps3a and Rps5; whereas silencing of Avr3a/5 causes gain of virulence in a P. sojae strain that is normally avirulent on Rps3a and Rps5 soybean lines. Transient expression and co-bombardment with a reporter gene confirms that Avr3a/5 triggers cell death in Rps5 soybean leaves in an appropriate allele-specific manner. Sequence analysis of the Avr3a/5 gene identifies crucial residues in the effector domain that distinguish recognition by Rps3a and Rps5.
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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 | 0.000 |
| 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".