Identification of nutrient and physical seed trait QTL in the model legume<i>Lotus japonicus</i>
Bibliographic record
Abstract
Legume seeds have the potential to provide a significant portion of essential micronutrients to the human diet. To identify the genetic basis for seed nutrient density, quantitative trait locus (QTL) analysis was conducted with the Miyakojima MG-20 x Gifu B-129 recombinant inbred population from the model legume Lotus japonicus. This population was grown to seed under greenhouse conditions in 2006 and 2007. Phenotypic data were collected for seed calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn), phosphorus (P), sulfur (S), and zinc (Zn) concentrations and content. Data for physical seed traits (average seed mass and seed-pod allocation values) were also collected. Based on these phenotypic data, QTL analyses identified 103 QTL linked to 55 different molecular markers. Transgressive segregation, identified within this recombinant inbred population for both seed nutrient and physical traits, suggests new allelic combinations are available for agronomic trait improvement. QTL co-localization was also seen, suggesting that common transport processes might contribute to seed nutrient loading. Identification of loci involved in seed mineral density can be an important first step in identifying the genetic factors and, consequently, the physiological processes involved in mineral distribution to developing seeds. Longer term research efforts will focus on facilitating agronomic breeding efforts through ortholog identification in related crop legumes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".