A genetic map of an Australian wild<i>Gossypium</i>C genome and assignment of homoeologies with tetraploid cultivated cotton
Bibliographic record
Abstract
Genetic diversity for traits such as fibre quality or disease resistance to microorganisms is limited in the elite cotton germplasm; consequently, cotton breeders are looking for novel alleles in the secondary or even in the tertiary gene pools. The wild Australian Gossypium species (tertiary gene pool) represent an alternative source of novel alleles. However, to use these species efficiently, enabling tools are required. Chromosome-specific molecular markers are particularly useful tools to track the transmission of this exotic genetic material into the cultivated cotton during introgression. In this study, we report the construction of a genetic linkage map of the Australian wild C-genome species Gossypium sturtianum. The map, based on an F(2) population of 114 individuals, contains 291 AFLP loci. The map spans 1697 cM with an average distance of 5.8 cM between markers. To associate C-genome chromosomes with the A and D subgenomes of cultivated cotton, 29 SSR and RFLP-STS markers were assigned to chromosomes using cultivated cotton mapped marker information. Polymorphisms were revealed by 51 AFLP primer combinations and 38 RFLP-STS and 115 SSR cotton mapped markers. The utility of transferring RFLP-STS and SSR cotton mapped markers to other Gossypium species shows the usefulness of a comparative approach as a source of markers and for aligning the genetic map of G. sturtianum with the cultivated species in the future. This also indicates that the overall structure of the G. sturtianum linkage groups is similar to that of the A and D subgenomes of cotton at the gross structural level. Applications of the map for the Australia wild C-genome species and cotton breeding are discussed.
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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 | 0.002 | 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) | 0.001 | 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".