The effects of crop attributes, selection, and recombination on Canadian bread wheat molecular variation
Bibliographic record
Abstract
Cultivated germplasm provides an opportunity to investigate how crop agronomic traits, selection for major genes, and differences in crossing-over rates drive patterns of allelic variation. To identify how these factors correlated with allelic variation within a collection of cultivated bread wheat (Triticum aestivum L.), we generated genotypes for 388 accessions grown in Canada over the past 170 yr using filtered single nucleotide polymorphism (SNP) calls from an Illumina Wheat iSelect 90K SNP-array. Entries' breeding program, era of release, grain texture, kernel color, and growth habit contributed to allelic differentiation. Allelic diversity and linkage disequilibrium (LD) of markers flanking some major loci known to affect traits such as gluten strength, growth habit, and grain color were consistent with selective sweeps. Nonetheless, some flanking markers of major loci had low LD and high allelic diversity. Positive selection may have acted upon homoeologous genes that had significant enrichment for the gene ontology terms 'response-to-auxin' and 'response-to-wounding.' Long regions of LD, spanning approximately one-third the length of entire chromosomes, were associated with many pericentromeric regions. These regions were also characterized by low diversity. Enhancing recombination across these regions could generate novel allele combinations to accelerate Canadian wheat improvement.
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".