Modification of Gene Expression, DNA Methylation and Small RNAs Expression in Rice Plants under In Vitro Culture
Bibliographic record
Abstract
Tissue culture is an important experimental technique widely used for plant transformation and can induce somaclonal variation that is shown to be associated with genetic and epigenetic changes. However, the molecular basis of somaclonal variation and plant cell response to tissue culture has yet to be fully understood. In this study, we investigated gene expression, DNA methylation, and small RNA changes in regenerated lines (RL) compared with the wild-type progenitor plants (WT) of rice cv. Hitomebore. Using microarray, we identified many genes that were differentially expressed in the shoot-tip tissue and showed that TEs were generally activated in RL. Methylation Sensitive Amplification Polymorphism (MSAP) analysis of 5′CCGG sites combined with bisulfite sequencing detected a generally reduced DNA methylation in the RL lines. Small RNA sequencing analysis detected widespread changes in small RNA accumulation between RL and WT. In particular, repeat and TE-associated 24-nt size class of small RNAs, the inducer of RNA-directed DNA methylation, was in general down-regulated in RL, consistent with reduced CHG and CHH methylation at some of the differentially methylated TE loci. A large number of differentially expressed miRNAs were identified in RL and WT lines, including known and novel miRNAs. The expression of some of these miRNAs exhibited inverse correlation with the predicted target genes, suggesting a regulatory function. The RL plants looked similar to WT plants under normal conditions but showed significant phenotypic alterations under abiotic stress conditions. The widespread changes in DNA methylation, small RNA accumulation and gene expression in regenerated plants supports the role of epigenetic changes in tissue culture-induced somaclonal variation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".