An InDel-based linkage map of hot pepper (Capsicum annuum)
Bibliographic record
Abstract
Two independent pepper ( Capsicum annuum ) genomes were published recently, opening a new era of molecular genetics research on pepper. However, pepper molecular marker technologies are still mainly focusing on the simple sequence repeats derived from public database or genomic library. The development and application of the third generation marker system such as single nucleotide polymorphisms, structure variations as well as insertion/deletion polymorphisms (InDels) is still in its infancy. In the present study, we developed InDel markers for pepper genetic mapping with the convenience of two whole-genome re-sequenced inbred lines BA3 ( C. annuum ) and B702 ( C. annuum ). A total of 154,519 and 149,755 InDel (1–5 bp) sites were identified for BA3 and B702, respectively, by the alignment of re-sequencing reads to Zunla-1 reference genome. Then, 14,498 InDel sites (only 4 and 5 bp) that are different between BA3 and B702 were predicted. Finally, within a random set of 1,000 primer pairs, 251 InDel markers were validated and mapped onto a linkage map using F 2 population derived from the intraspecific cross BA3 × B702. The first InDel-based map, named as BB-InDel map, consisted of 12 linkage groups, covered a genetic distance of 1,178.01 cM and the average distance between bin markers was 5.01 cM. Compared to the Zunla-1 reference physical map, high consistency was observed on all 12 chromosomes, and the total length of scaffold anchored and physical distance covered by this map was 299.66 and 2,558.68 Mb, respectively, which accounted for 8.95 and 76.38 % of the Zunla-1 reference genome (3.35 Gb), respectively. Furthermore, 37 scaffolds (total length of 36.21 Mb) from the pseudo-chromosome (P0) of the current genome assembly were newly assigned to the corresponding chromosomes by 40 InDel markers. Thus, this map provided good genome coverage and would be useful for basic and applied research in pepper.
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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 | 0.003 | 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".