Extensive Allelic Variation in Gene Expression in Populus F1 Hybrids
Bibliographic record
Abstract
Hybridization between plant species can induce speciation as well as phenotypic novelty and heterosis. Hybrids also can show genome rearrangements and gene expression changes compared with their parents. Here we determined the allelic variation in gene expression in Populus trichocarpa x Populus deltoides F(1) hybrids. Among 30 genes analyzed in four independently formed hybrids, 17 showed >1.5-fold expression biases for one of the two alleles, and there was monoallelic expression of one gene. Expression ratios of the alleles differed between leaves and stems for 10 genes. The results suggest differential regulation of the two parental alleles in the hybrids. To determine if the allelic expression biases were caused by hybridization we compared the ratios of species-specific transcripts between an F(1) hybrid and its parents. Thirteen of 19 genes showed allelic expression ratios in the hybrid that were significantly different from the ratios of the parental species. The P. deltoides allele of one gene was silenced in the hybrid. Modes of gene regulation were inferred from the hybrid-parent comparisons. Cis-regulation was inferred for 6 genes, trans-regulation for 1 gene, and combined cis- and trans-regulation for 9 genes. The results from this study indicate that hybridization between plant species can have extensive effects on allelic expression patterns, some of which might lead to phenotypic changes.
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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 | 0.001 | 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 | 0.000 |
| 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".