Genetic dissection of two elite japonica varieties reveals founder transmission and selection in breeding
Bibliographic record
Abstract
Understanding the genetic basis of elite rice varieties is conducive to the strategic utilization of genetic resources in modern breeding programs. To elucidate the genetic component and transmission across pedigrees, we investigated two elite inbred japonica varieties, Huruan1212 (HR1212) and Hugeng137 (HG137), through whole-genome sequencing with an average depth of 38.2× and pedigree analysis. We identified specific SNPs and enriched pathways underlying HR1212's excellent eating and cooking quality and HG137's stress resistance. Genomic scans traced the contributions of founder parents Xiushui04 and Wuyugeng3, revealing transmission patterns of favorable alleles across generations. Notably, the shared identity-by-descent (sIBD) segments of the two pedigrees overlapped by 74 Mb, total formed 118.42 Mb of conserved genetic segments, with validation in other founder-derived lines. This research provides valuable insights for utilizing founder parents and elite varieties and highlights the critical need to implement genome-informed breeding strategies in future breeding practice. • Specific SNPs and pathway enrichment underlie trait divergence of elite varieties. • Common founder parents exerted sustained genetic introgression on elite varieties. • Artificial selection preferences could result in unconscious breeding blind spots. • The conserved genomic segments from founder parents were identified in pedigrees.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".