<i>Cis-</i> Regulatory Changes Associated with a Recent Mating System Shift and Floral Adaptation in <i>Capsella</i>
Bibliographic record
Abstract
The selfing syndrome constitutes a suite of floral and reproductive trait changes that have evolved repeatedly across many evolutionary lineages in response to the shift to selfing. Convergent evolution of the selfing syndrome suggests that these changes are adaptive, yet our understanding of the detailed molecular genetic basis of the selfing syndrome remains limited. Here, we investigate the role of cis-regulatory changes during the recent evolution of the selfing syndrome in Capsella rubella, which split from the outcrosser Capsella grandiflora less than 200 ka. We assess allele-specific expression (ASE) in leaves and flower buds at a total of 18,452 genes in three interspecific F1 C. grandiflora x C. rubella hybrids. Using a hierarchical Bayesian approach that accounts for technical variation using genomic reads, we find evidence for extensive cis-regulatory changes. On average, 44% of the assayed genes show evidence of ASE; however, only 6% show strong allelic expression biases. Flower buds, but not leaves, show an enrichment of cis-regulatory changes in genomic regions responsible for floral and reproductive trait divergence between C. rubella and C. grandiflora. We further detected an excess of heterozygous transposable element (TE) insertions near genes with ASE, and TE insertions targeted by uniquely mapping 24-nt small RNAs were associated with reduced expression of nearby genes. Our results suggest that cis-regulatory changes have been important during the recent adaptive floral evolution in Capsella and that differences in TE dynamics between selfing and outcrossing species could be important for rapid regulatory divergence in association with mating system shifts.
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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 | 0.000 |
| 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".