Tagging and Mapping <i>Pse‐1</i> Gene for Resistance to Halo Blight in Common Bean Differential Cultivar UI‐3
Bibliographic record
Abstract
ABSTRACT Halo blight [caused by Pseudomonas syringae pv. phaseolicola (Burkh.) Young et al. ( Psp )] is a serious seed‐borne bacterial disease of common bean ( Phaseolus vulgaris L.). A few resistance (R) genes and quantitative trait loci provide control to one or more races of the pathogen. To better understand monogenic resistance and improve breeding efficiency, we sought to tag and map a gene ( Pse‐1 ) in host differential cultivar UI‐3 (previously named ‘Red Mexican UI‐3’) that provides resistance to races 1, 5, 7, and 9 of Psp Cosegregation for resistance to races 1, 5, 7, and 9, in a recombinant inbred population, ‘Canadian Wonder’/UI‐3 (CU), confirmed the effect of Pse‐1 against multiple races of the pathogen. Bulked‐segregant analysis in the CU population identified six random amplified polymorphic DNA (RAPD) markers tightly linked (0–3.3 cM) to Pse‐1 . Three of the RAPDs completely linked with Pse‐1 in the CU population were converted to sequence characterized amplified region (SCAR) markers SH11.800, SR13.1150, and ST8.1350. The linked markers were used to integrate Pse‐1 to linkage group B10 of the core map. Allelism tests (F 2 ) confirmed relationships of Pse‐1 and Pse‐4 derived from UI‐3 with R genes in the other host differential cultivars. A survey of advanced lines and cultivars revealed that the SCAR markers generated in this study will have utility for marker‐assisted selection of Pse‐1 in germplasm from the Andean gene pool (e.g., kidney, calima) and from race Mesoamerican within the Middle American gene pool (black, carioca).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 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 teacher head, 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".