Nucleomorph Small RNAs in Cryptophyte and Chlorarachniophyte Algae
Bibliographic record
Abstract
The regulation of gene expression and RNA maturation underlies fundamental processes such as cell homeostasis, development, and stress acclimation. The biogenesis and modification of RNA is tightly controlled by an array of regulatory RNAs and nucleic acid-binding proteins. While the role of small RNAs (sRNAs) in gene expression has been studied in-depth in select model organisms, little is known about sRNA biology across the eukaryotic tree of life. We used deep sequencing to explore the repertoires of sRNAs encoded by the miniaturized, endosymbiotically derived "nucleomorph" genomes of two single-celled algae, the cryptophyte Guillardia theta and the chlorarachniophyte Bigelowiella natans. A total of 32.3 and 35.3 million reads were generated from G. theta and B. natans, respectively. In G. theta, we identified nucleomorph U1, U2, and U4 spliceosomal small nuclear RNAs (snRNAs) as well as 11 C/D box small nucleolar RNAs (snoRNAs), five of which have potential plant and animal homologs. The snoRNAs are predicted to perform 2'-O methylation of rRNA (but not snRNA). In B. natans, we found the previously undetected 5S rRNA as well as six orphan sRNAs. Analysis of chlorarachniophyte snRNAs shed light on the removal of the miniature 18-21 nt introns found in B. natans nucleomorph genes. Neither of the nucleomorph genomes appears to encode RNA pseudouridylation machinery, and U5 snRNA cannot be found in the cryptophyte G. theta. Considering the central roles of U5 snRNA and RNA modifications in other organisms, cytoplasm-to-nucleomorph RNA shuttling in cryptophyte algae is a distinct possibility.
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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".