A Natural Major Module Confers the Trade‐Off between Phenotypic Mean and Plasticity of Grain Chalkiness in Rice
Bibliographic record
Abstract
A critical challenge in crop breeding is the trade-off between improving the mean of an important trait and maintaining its phenotypic plasticity. Grain chalkiness is a key cereal grain-quality trait highly susceptible to environments. However, the genetic and molecular mechanisms controlling the trade-off between phenotypic mean and plasticity of grain chalkiness remain unknown. Here, utilizing comprehensive genome-wide association studies on ten grain chalkiness traits over five years in a mini-core collection, substantial phenotypic plasticity of grain chanlkiness is found, which declines during modern breeding. A general trade-off between phenotypic mean and plasticity of grain chalkiness is demonstrated, which are controlled by distinct genetic architectures revealed through a detailed QTL atlas. High temperature and wide grain significantly increase grain chalkiness mean but decrease its plasticity and genetic dissection, representing two major external drivers for the trade-off. Two key quantitative trait genes MPC5 and GCP6 are identified to control this trade-off. The transcription factor GCP6 biochemically and genetically inhibits MPC5 expression, forming a key module that confers the mean-plasticity trade-off of both grain chalkiness and width. Finally, minimal marker sets for molecular breeding accounted for two thirds of grain chalkiness variation. These findings elucidate the genetic architecture of the mean-plasticity trade-off in grain chalkiness and offer a proof-of-concept breeding strategy to simultaneously optimize both phenotypic mean and plasticity in crop improvement.
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 | 0.001 |
| 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".