Spaceflight-induced genetic and epigenetic changes in the rice (<i>Oryza sativa</i> L.) genome are independent of each other
Bibliographic record
Abstract
An array of studies have reported that the spaceflight environment is mutagenic and may induce phenotypic and genetic changes in diverse organisms. We reported recently that in at least some plant species (e.g., rice) the spaceflight environment can be particularly potent in generating heritable epigenetic changes in the form of altered cytosine methylation patterns and activation of transposable elements. To further study the issue of spaceflight-induced genomic instability, and in particular to test whether the incurred genetic and epigenetic changes are connected or independent of each other, we performed the present study. We subjected seeds of the standard laboratory rice (Oryza sativa L.) cultivar Nipponbare to a spaceflight in the spaceship Long March 2 for 18 days. We then investigated the genetic and DNA methylation stabilities of 11 randomly selected plants germinated from the spaceflown seeds by using two kinds of DNA markers, amplified fragment length polymorphism (AFLP) and methylation sensitive amplified polymorphism (MSAP). For AFLP, by using 15 primer combinations, we assessed 460 genomic loci and found that the frequencies of genetic changes across the 11 plants ranged from 0.7% to 6.7% with an average frequency of 3.5%. For MSAP, by using 14 primer combinations, we assessed 467 loci and detected the occurrence of four major types of cytosine methylation alterations at the CCGG sites, namely CG or CNG hypomethylation and CG or CNG hypermethylation. Collectively, the frequencies of the two kinds of hypermethylation, CG (1.95%) and CNG (1.44%), are about two times higher than those of the two kinds of hypomethylation, CG (0.76%) and CNG (0.80%), though different plants showed variable frequencies for each type of alteration. Further analysis suggested that both the genetic and cytosine methylation changes manifested apparent mutational bias towards specific genomic regions, but the two kinds of instabilities are independent of each other based on correlation analysis.
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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 | 0.000 | 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".