A high frequency of overlapping gene expression in compacted eukaryotic genomes
Bibliographic record
Abstract
The gene density of eukaryotic nuclear genomes is generally low relative to prokaryotes, but several eukaryotic lineages (many parasites or endosymbionts) have independently evolved highly compacted, gene-dense genomes. The best studied of these are the microsporidia, highly adapted fungal parasites, and the nucleomorphs, relict nuclei of endosymbiotic algae found in cryptomonads and chlorarachniophytes. These systems are now models for the effects of compaction on the form and dynamics of the nuclear genome. Here we report a large-scale investigation of gene expression from compacted eukaryotic genomes. We have conducted EST surveys of the microsporidian Antonospora locustae and nucleomorphs of the cryptomonad Guillardia theta and the chlorarachniophyte Bigelowiella natans. In all three systems we find a high frequency of mRNA molecules that encode sequence from more than one gene. There is no bias for these genes to be on the same strand, so it is unlikely that these mRNAs represent operons. Instead, compaction appears to have reduced the intergenic regions to such an extent that control elements like promoters and terminators have been forced into or beyond adjacent genes, resulting in long untranslated regions that encode other genes. Normally, transcriptional overlap can interfere with expression of a gene, but these genomes cope with high frequencies of overlap and with termination signals within expressed genes. These findings also point to serious practical difficulties in studying expression in compacted genomes, because many techniques, such as arrays or serial analysis of gene expression will be misleading.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".