Genome-wide association analyses of common wheat (Triticum aestivum L.) germplasm identifies multiple loci for aluminium resistanceThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”
Bibliographic record
Abstract
Aluminium (Al3+) toxicity restricts productivity and profitability of wheat (Triticum aestivum L.) crops grown on acid soils worldwide. Continued gains will be obtained by identifying superior alleles and novel Al3+ resistance loci that can be incorporated into breeding programs. We used association mapping to identify genomic regions associated with Al3+ resistance using 1055 accessions of common wheat from different geographic regions of the world and 178 polymorphic diversity arrays technology (DArT) markers. Bayesian analyses based on genetic distance matrices classified these accessions into 12 subgroups. Genome-wide association analyses detected markers that were significantly associated with Al3+ resistance on chromosomes 1A, 1B, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5B, 6A, 6B, 7A, and 7B. Some of these genomic regions correspond to previously identified loci for Al3+ resistance, whereas others appear to be novel. Among the markers targeting TaALMT1 (the major Al3+-resistance gene located on chromosome 4D), those that detected alleles in the promoter explained most of the phenotypic variance for Al3+ resistance, which is consistent with this region controlling the level of TaALMT1 expression. These results demonstrate that genome-wide association mapping cannot only confirm known Al3+-resistance loci, such as those on chromosomes 4D and 4B, but they also highlight the utility of this technique in identifying novel resistance loci.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".