Mapping barley genes to chromosome arms by transcript profiling of wheat–barley ditelosomic chromosome addition lines
Bibliographic record
Abstract
Wheat-barley disomic and ditelosomic chromosome addition lines have been used as genetic tools for a range of applications since their development in the 1980s. In the present study, we used the Affymetrix Barley1 GeneChip for comparative transcript analysis of the barley cultivar Betzes, the wheat cultivar Chinese Spring, and Chinese Spring - Betzes ditelosomic chromosome addition lines to physically map barley genes to their respective chromosome arm locations. We mapped 1257 barley genes to chromosome arms 1HS, 2HS, 2HL, 3HS, 3HL, 4HS, 4HL, 5HS, 5HL, 7HS, and 7HL based on their transcript levels in the ditelosomic addition lines. The number of genes assigned to individual chromosome arms ranged from 24 to 197. We validated the physical locations of the genes through comparison with our previous chromosome-based physical mapping, comparative in silico mapping with rice and wheat, and single feature polymorphism (SFP) analysis. We found our physical mapping of barley genes to chromosome arms to be consistent with our previous physical mapping to whole chromosomes. In silico comparative mapping of barley genes assigned to chromosome arms revealed that the average genomic synteny to wheat and rice chromosome arms was 63.2% and 65.5%, respectively. In the 1257 mapped genes, we identified SFPs in 924 genes between the appropriate ditelosomic line and Chinese Spring that supported physical map placements. We also identified a single small rearrangement event between rice chromosome 9 and barley chromosome 4H that accounts for the loss of synteny for several genes.
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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".