Centromere histone H3- and phospholipase-mediated haploid induction in plants
Bibliographic record
Abstract
Simple and consistent production of haploid is always an appealing pursuit for both crop breeders and researchers. Although diverse strategies have been developed to produce haploids over the past decades, most of them are applicable in only a limited number of plant species. In 2010, Ravi and Chan reported that haploid Arabidopsis thaliana plants can be efficiently induced through the introduction of a single genetic alteration in centromere histone H3 (CENH3). Subsequent studies demonstrated that haploids can be efficiently induced either through genetic engineering of CENH3 N-terminal tail or histone fold domain or by replacing CENH3 with an ortholog. The mutation of a pollen-specific phospholipase gene, MATRILINEAL ( MTL ) has been revealed to trigger the haploid induction (HI) in maize, which present another promising HI approach by the editing of MTL in plant. Here, we review the progress of the CENH3-medialed HI and propose a revised centromere-size model by suggesting a competitive loading process between wild-type and mutant CENH3 during HI. This model can explain both the findings of HI failure when wild-type and mutant CENH3 genes are coexpressed and the alien centromere loading of CENH3 in stable hybrids. In addition, we review the current understanding of MTL -mediated HI in plant. The conservation of CENH3 and MTL in plants indicates wide potential application for HI. We discuss the utility and potential of these two methods in crops by comparing their mechanisms and applications to date in plants. This review will promote the study and application of both CENH3- and MTL -mediated haploid induction in plants.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".