Abundance of distal repetitive DNA sequences in <i>Capsicum</i> L. (Solanaceae) chromosomes
Bibliographic record
Abstract
Chili peppers (Solanaceae family) have great commercial value. They are commercialized in natura and used as spices and for ornamental and medicinal purposes. Although three whole genomes have been published, limited information about satellite DNA sequences, their composition, and genomic distribution has been provided. Here, we exploited the noncoding repetitive fraction, represented by satellite sequences, that tends to accumulate in blocks along chromosomes, especially near the chromosome ends of peppers. Two satellite DNA sequences were identified (CDR-1 and CDR-2), characterized and mapped in silico in three Capsicum genomes ( C. annuum, C. chinense, and C. baccatum) using data from the published high-coverage sequencing and repeats finding bioinformatic tools. Localization using FISH in the chromosomes of these species and in two others ( C. frutescens and C. chacoense), totaling five species, showed signals adjacent to the rDNA sites. A sequence comparison with existing Solanaceae repeats showed that CDR-1 and CDR-2 have different origins but without homology to rDNA sequences. Satellites occupied subterminal chromosomal regions, sometimes collocated with or adjacent to 35S rDNA sequences. Our results expand knowledge about the diversity of subterminal regions of Capsicum chromosomes, showing different amounts and distributions within and between karyotypes. In addition, these sequences may be useful for future phylogenetic studies.
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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 | 0.001 | 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 | 0.000 |
| 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".