Construction of diversity panels of landrace rice collections in Myanmar
Bibliographic record
Abstract
Abstract To meet the future demand of the global population, new varieties to adapt to regional climate changes such as salinity, drought, and submergence and new race emergence of pest disease and insects are expected to be developed for plant breeders. To facilitate efficient screening of germplasm and gene exploration on bi-parental cross populations and genome-wide association study (GWAS), the construction of a compact and genetically characterized germplasm platform is necessary in the National gene bank. In this study, genetic relationships of the representative core collections (CC) conserved in the National Seedbank of Myanmar were investigated using the genotyping-by-sequencing approach. It was found that the accessions were classified into the three clusters corresponding so-called japonica, indica, and aroma subpopulations. For efficient germplasm screening and gene exploration by GWAS on the indica landrace germplasm in Myanmar, a compact diversity panel designated “G” consisting of the 249 accessions was assembled, and genome-wide nucleotide variants were collected by the whole genome sequencing. The principal component analysis using genome-wide variants revealed that the selected accessions did not have an apparent population structure, but the first and second principal component scores correlated to the latitude and longitude, suggesting that latitude is the more causal factor of the geographical variation within the Myanmar landrace. When the reference genome of the leading variety in Myanmar was used, the mixed model genome-wide association analysis provided higher -log10(p) scores and detected seven peaks of apiculus pigmentation of spikelet. The five peak associations of the seven fall into the linkage disequllibrium blocks or neighbor blocks containing the isolated genes involved in anthocyanin pigmentation in rice. These results demonstrated that the combination of the landrace GWAS of the National seed banks and reference sequences genetically related to the landrace provide better research environments in characterization and gene exploration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".