Divergent gene expression levels between diploid and autotetraploid <i>Tolmiea</i> relative to the total transcriptome, the cell, and biomass
Bibliographic record
Abstract
PREMISE OF THE STUDY: Studies of gene expression and polyploidy are typically restricted to characterizing differences in transcript concentration. Using diploid and autotetraploid Tolmiea, we present an integrated approach for cross-ploidy comparisons that account for differences in transcriptome size and cell density and make multiple comparisons of transcript abundance. METHODS: We use RNA spike-in standards in concert with cell size and density to identify and correct for differences in transcriptome size and compare levels of gene expression across multiple scales: per transcriptome, per cell, and per biomass. KEY RESULTS: In total, ~17% of all loci were identified as differentially expressed (DEGs) between the diploid and autopolyploid species. The per-transcriptome normalization, the method researchers typically use, captured the fewest DEGs (58% of total DEGs) and failed to detect any DEGs not found by the alternative normalizations. When transcript abundance was normalized per biomass and per cell, ~66% and ~82% of the total DEGs were recovered, respectively. The discrepancy between per-transcriptome and per-cell recovery of DEGs occurs because per-transcriptome normalizations are concentration-based and therefore blind to differences in transcriptome size. CONCLUSIONS: While each normalization enables valid comparisons at biologically relevant scales, a holistic comparison of multiple normalizations provides additional explanatory power not available from any single approach. Notably, autotetraploid loci tend to conserve diploid-like transcript abundance per biomass through increased gene expression per cell, and these loci are enriched for photosynthesis-related functions.
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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".