Genome Re-Sequencing and Functional Analysis Places the Phytophthora sojae Avirulence Genes Avr1c and Avr1a in a Tandem Repeat at a Single Locus
Bibliographic record
Abstract
The aim of this work was to map and identify the Phytophthora sojae Avr1c gene. Progeny from a cross of P. sojae strains ACR10×P7076 were tested for virulence on plants carrying Rps1c. Results indicate that avirulence segregates as a dominant trait. We mapped the Avr1c locus by performing whole genome re-sequencing of composite libraries created from pooled samples. Sequence reads from avirulent (Pool1) and virulent (Pool2) samples were aligned to the reference genome and single nucleotide polymorphisms (SNP) were identified for each pool. High quality SNPs were filtered to select for positions where SNP frequency was close to expected values for each pool. Only three SNP positions fit all requirements, and these occurred in close proximity. Additional DNA markers were developed and scored in the F₂ progeny, producing a fine genetic map that places Avr1c within the Avr1a gene cluster. Transient expression of Avr1c or Avr1a triggers cell death on Rps1c plants, but Avr1c does not trigger cell death on Rps1a plants. Sequence comparisons show that the RXLR effector genes Avr1c and Avr1a are closely related paralogs. Gain of virulence on Rps1c in P. sojae strain P7076 is achieved by gene deletion, but in most other strains this is accomplished by gene silencing. This work provides practical tools for crop breeding and diagnostics, as the Rps1c gene is widely deployed in commercial soybean cultivars.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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.
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".