Genomic Simple Sequence Repeat Markers Reveal Patterns of Genetic Relatedness and Diversity in Sesame
Bibliographic record
Abstract
Sesame (Sesamum indicum L. syn. Sesamum orientale L.) is an orphan crop species with most molecular genetic research work done in the last decade. In this study, we used a pyrosequencing approach for the development of genomic simple-sequence repeat (SSR) markers in sesame. Our approach proved successful in identifying 19,816 nonredundant SSRs, 5727 of which were identified in a contig assembly that covers 19.29% of the sesame genome. Mononucleotide repeats were the most abundant SSR type identified in the sesame genome (48.5% of all SSRs), followed by dinucleotide SSRs (45.0%). Adenine-thymine-rich motifs were predominant, representing 81.7, 51.7, 66.5, and 22.1% of the mononucleotide, dinucleotide, trinucleotide, and tetranucleotide SSRs, respectively. As a result of this work, we introduce 933 experimentally validated sesame specific markers, 849 of which are also applicable in Sesamum mulayanum (syn. Sesamum orientale var. malabaricum Nar.), the wild progenitor of cultivated sesame. Using a subset of the newly identified SSR markers, we analyzed molecular genetic diversity and population structure of a collection of world accessions. Results of the two analyses almost overlapped and suggested correlation between genetic similarity and geographical proximity. Indeed, a pattern of gene flow among sesame diversity centers was apparent, with levels of variability in some regions similar to that seen in the domestication origin of the crop. Taken together with the high rate of genomic marker transferability detected between S. indicum and S. mulayanum, our results represent additional molecular genetic evidence for designating the two taxa as cultivated and wild forms of the same species.
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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 | 0.001 |
| 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) | 0.000 | 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 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".