Molecular variation in plant cell populations evolving in vitro in different physiological contexts
Bibliographic record
Abstract
Previous work has shown the fixation of context-specific random amplified polymorphic DNA (RAPD) patterns in tomato cell cultures grown for 2 years in different hormonal contexts. In this work, RAPD sequences were characterised and RAPD-derived molecular markers used for a further study of variation between and within auto- and auxo-trophic tomato cultures grown in different hormonal equilibria. Results were then compared with those obtained using microsatellite markers located in noncoding regions of differentiation- and hormone-related genes and with those obtained with the external transcribed spacer (ETS) from tomato rDNA. Hybridisation of RAPDs on a tomato genomic DNA bank, or on total DNA after enzymatic digestion, suggested that the markers were repetitive in nature. Sequence analysis. however, showed that the homology between different fragments was due mainly to the presence of homo-AT nucleotide stretches. Moreover, a series of computational methods, such as an information-theory algorithm coupled with AG estimates, suggested that the RAPD fragments isolated in our experiments are noncoding. The amplification of SSR-containing RAPD-derived markers, and of other SSRs located in noncoding regions of tomato functional genes, consistently showed polymorphism between auxo- and auto-trophic somaclones (the latter being either habituated or transgenic for Agrobacterium tumefaciens oncogenes) but not within these same clones. Differences were also found between auxotrophic clones and the differentiated tissue. These findings were confirmed by restriction fragment length polymorphism (RFLP) analysis with the REII repetitive element of the ETS from tomato rDNA, which was isolated during this study. The results obtained suggest a possible role for physiological context in the selection of RAPD patterns during the evolution of tomato cells with different endogenous hormonal equilibria. The results are discussed in terms of a possible role for variation in noncoding regions of hormone-related genes in the adaptation to different physiological contexts.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".