A retrotransposon insertion in <i>MUTL-HOMOLOG 1</i> affects wild rice seed set and cultivated rice crossover rate
Bibliographic record
Abstract
Wild rice (Oryza rufipogon) has a lower panicle seed setting rate (PSSR) and gamete fertility than domesticated rice (Oryza sativa), but the genetic mechanisms of this phenomenon remain unknown. Here, we cloned a null allele of OsMLH1, an ortholog of MutL-homolog 1 to yeast and mammals, from wild rice O. rufipogon W1943 and revealed a 5.4-kb retrotransposon insertion in OsMLH1 is responsible for the low PSSR in wild rice. In contrast to the wild-type, a near isogenic line NIL-mlh1 exhibits defective crossover (CO) formation during meiosis, resulting in reduced pollen viability, partial embryo lethality, and low PSSR. Except for the mutant of mismatch repair gene postmeiotic segregation 1 (Ospms1), all other MutL mutants from O. sativa indica subspecies displayed male and female semi-sterility similar to NIL-mlh1, but less severe than those from O. sativa japonica subspecies. MLH1 and MLH3 did not contribute in an additive fashion to fertility. Two types of MutL heterodimers, MLH1-PMS1 and MLH1-MLH3, were identified in rice, but only the latter functions in promoting meiotic CO formation. Compared to japonica varieties, indica cultivars had greater numbers of CO events per meiosis. Our results suggest that low fertility in wild rice may be caused by different gene defects, and indica and japonica subspecies have substantially different CO rates responsible for the discrepancy between the fertility of mlh1 and mlh3 mutants.
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 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 | 0.000 | 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) | 0.001 | 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".