Environment-dependent selection impacts heritable developmental stability and trait canalization in rice
Bibliographic record
Abstract
Abstract Canalization, or the maintenance of trait values regardless of environmental or genetic variability, is fundamentally important for maintaining developmental stability. While this concept was described decades ago, we still know relatively little about how canalization is influenced by environmental stress, how it is shaped by natural selection, and the genetic underpinnings of canalization. In this study, we examined natural selection on microenvironmental canalization in rice ( Oryza sativa ) in wet and dry field conditions. We measured developmental stability in genetically identical replicates obtained from geographically widespread Indica and Japonica rice accessions, providing precise estimates of canalization in thousands of plants. We found that drought stress decreased canalization, showing that stress can increase instability. We also found evidence that canalization can evolve, given that canalization of several traits was heritable and under selection. We further uncovered specific genes underlying canalization, with genetic mapping and functional genetic experiments showing that the bZIP transcription factor-encoding gene OsTGA5 / rTGA2.3 , which is part of a module that balances stress response and plant growth, regulates canalization of several traits in an environment-dependent manner. At a genome-wide scale, canalization was associated with lower gene expression stochasticity at an earlier life stage, indicating that expression variation can reduce canalization and increase instability. Trait canalization was also positively correlated to temperature at accessions’ source environments, suggesting that selection on canalization can vary among environments. Overall, our study provides novel insights into the molecular genetic basis of environmental differences in developmental stability and how it might be shaped by selection. Significance Mechanisms stabilizing organismal development in response to genetic mutations or environmental stressors (canalization) have been reported for numerous animals and plants, but their underlying genetic basis and whether they may be shaped by selection remain unclear. Here, we report patterns of drought-induced trait decanalization in populations of rice ( Oryza sativa ) grown in field environments. We determined that trait canalization is heritable and can evolve separately from trait means. We identified the gene OsTGA5 , part of a regulatory module shaping trade-offs between growth and stress responses, as impacting trait canalization. Plants with less noisy gene expression and evolving in warmer environments display greater developmental stability, contributing to the notion that canalization in rice may be adaptive.
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 | 0.001 |
| 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".