A novel reporter for intrachromosomal homoeologous recombination in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
A reporter system using engineered introns as recombination substrates in the uidA (GUS) gene has been developed and characterized in Arabidopsis thaliana. The non-coding nature of the recombination substrate has allowed us to monitor recombination events between duplicated copies of the intron that are either identical (homologous recombination) or harbour sequence polymorphisms (homoeologous recombination). The effects of substrate length and divergence on the frequency of recombination events were examined. A positive correlation between substrate length and somatic recombination frequency was found as the frequency of recombination increased 183-fold when the recombination substrate was lengthened from 153 to 589 bp. The existence of 11 polymorphisms in a 589-bp recombination substrate (1.9% sequence divergence) led to an almost 10-fold reduction in the frequency of recombination. This result demonstrates that relatively modest levels of sequence divergence can substantially reduce the frequency of recombination in plants. A molecular analysis of recombination products revealed that the recombination junctions are more frequent in the central segment of the recombination substrate.
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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".