Quantitative trait loci controlling aluminium tolerance in two accessions of <i>Arabidopsis thaliana</i> (Landsberg <i>erecta</i> and Cape Verde Islands)
Bibliographic record
Abstract
ABSTRACT Quantitative trait loci (QTL) analysis of aluminium (Al) tolerance was performed using Ler/Cvi recombinant inbred (RI) lines of Arabidopsis thaliana. Relative root length (RRL) (root length with 4 µm Al/root length with no Al at pH 5.0) on day 5 was used as the Al tolerance index for QTL analysis. Al tolerance judged by RRL was well correlated to tolerance judged by other indexes, including accumulation of callose, reactive oxygen species in the root apex and growth performance on acid soil containing a large amount of exchangeable Al. Using data sets with an hb2 of 0.91, two QTLs were detected at the top of chromosome 1 and bottom of chromosome 3. These QTLs explained 40 and 16% of the phenotypic variation of Al tolerance, respectively, and the positive effect of the Cvi allele. The QTL on chromosome 1 overlapped with a major QTL in another recombinant inbred population, and is possibly related to malate excretion. A complete pair‐wise search revealed 11 sets of epistatic interacting loci pairs, which accounted for the transgressive segregation among the RI population. Several epistatic interactions shared the same chromosomal region, indicating the possible involvement of regulatory proteins in Al tolerance in Arabidopsis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".