Phenotyping low phosphate responses of Eutrema salsugineum ecotypes and their recombinant inbred lines
Bibliographic record
Abstract
Phosphorus, an essential nutrient for plants, is provided to crops in the form of phosphate containing fertilizers to maximize yield. Accessible rock phosphate deposits used in producing fertilizers are dwindling while harmful environmental impacts of increased fertilizer use and production grow, making it imperative to reduce our reliance on this nutrient. We study two ecotypes of Eutrema salsugineum, an extremophile crucifer related to the oilseed crop canola. The ecotype from Yukon, Canada, is tolerant to many abiotic stressors including low-phosphate while the ecotype from Shandong, China, is sensitive to low-phosphate. In this study we used 11 recombinant inbred lines (RILs) produced by crossing the two ecotypes to screen for their low-phosphate sensitivity. Seedlings were grown on agar with low (0 or 0.05 mM) or high (0.5 mM) phosphate and plants were grown up to 11 weeks in pots of soil-less media and fertilized with solutions lacking or supplemented with phosphate (0 or 2.5 mM). Seedling root architectural traits and root/shoot biomass were measured and plants in pots were analyzed by monitoring fluorescence parameters, leaf coverage and shoot biomass. Expression of Induced by Phosphate Starvation2 (IPS2) and five ecotype-specific genes were assessed for their utility as treatment and/or genotypic markers. Among root traits, primary root length was a reliable screening trait for identifying low-phosphate tolerant RILs while lateral root length or density gave inconsistent assignments. Non-photochemical quenching data suggests improved capacities to dissipate excess energy in phosphate-deprived plants, particularly Yukon plants, but further testing is needed given this unanticipated finding. IPS2 expression was a reliable bioindicator of low-phosphate exposure while the ecotype-specific genes proved too small a testing group to reveal meaningful patterns. Genome and transcriptome sequencing combined with a focused phenotype screen like primary root length offer a plausible path to identify genes underlying low-phosphate tolerance in plants.
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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".