Positive selection on hotspot and reinforcing regulatory alleles contributed to hexaploid bread wheat improvement
Bibliographic record
Abstract
Abstract Background Genetic variation of regulatory alleles plays a key role in evolution and breeding. In polyploids, regulatory differences may preferentially affect genes on homoeologous chromosomes or sub-genomes. Selection in plant breeding may act upon total transcript dosage across homoeologous genes and on alleles that have strong effects on the transcriptome. Results To investigate these questions, we identified regulatory polymorphisms between an old and a recent hexaploid bread wheat cultivar ( Triticum aestivum , 2n=6x=42, AABBDD). The recent cultivar was the product of decades of selection for grain yield and quality. Regulatory allele polymorphisms preferentially affected genes on homoeologous chromosomes but rarely affected genes on specific sub-genomes. The chromosomal distributions of regulatory alleles indicated that past selection had acted upon them, and the effect of selection differed between alleles targeting environmental response genes and genes involved in other processes. Modern cultivar alleles that affected many genes’ transcripts corresponded to known selection targets and improved field crop performance. Modern cultivar alleles also had significant effects on homoeologous genes, and these alleles also improved crop performance. Conclusions Polyploid breeding across many species has been and will continue to be the key factor in plant improvement. By enhancing the favorability of strong regulatory alleles and by expanding the range of gene transcript abundances, genome duplications enable breeding progress.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".