A high-resolution, intraspecific linkage map of pepper (Capsicum annuum L.) and selection of reduced recombinant inbred line subsets for fast mapping
Bibliographic record
Abstract
A high-resolution, intraspecific linkage map of pepper (Capsicum annuum L.) was constructed from a population of 297 recombinant inbred lines. The parents were the large-fruited inbred cultivar 'Yolo Wonder' and the hot pepper line 'Criollo de Morelos 334', which is heavily used as a source of resistance to a number of diseases. A set of 587 markers (507 amplified fragment length polymorphisms, 40 simple sequence repeats, 19 restriction fragment length polymorphisms, 17 sequence-specific amplified polymorphisms, and 4 sequence tagged sites) were used to generate the map; of these, 489 were assembled into 49 linkage groups (LGs), including 14 LGs with 10 to 60 markers per LG and 35 with 2 to 9 markers per LG. The framework map covered 1857 cM with an average intermarker distance of 5.71 cM. Twenty-three LGs, composed of 69% of the markers and covering 1553 cM, were assigned to 1 of the 12 haploid pepper chromosomes, leaving 26 LGs (304 cM) unassigned. The chromosome framework map built with 250 markers led to a high level of mapping confidence and an average intermarker distance of 6.54 cM. By applying MapPop software, it was possible to select smaller subsets of 141 or 93 most informative individuals with a view to reducing the time and cost of further mapping and phenotyping. To define the smallest number of individuals sufficient for assigning any new marker to a chromosome, subsets from 12 to 45 individuals and a set of 13 markers distributed over all 12 chromosomes were screened. In most cases, the markers were correctly assigned to their expected chromosome, but the accuracy of the map position decreased as the number of individuals was reduced.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".