Identifying small RNAs derived from maternal- and somatic-type rRNAs in zebrafish development
Bibliographic record
Abstract
rRNAs are non-coding RNAs present in all prokaryotes and eukaryotes. In eukaryotes there are four rRNAs: 18S, 5.8S, 28S, originating from a common precursor (45S), and 5S. We have recently discovered the existence of two distinct developmental types of rRNA: a maternal-type, present in eggs and a somatic-type, expressed in adult tissues. Lately, next-generation sequencing has allowed the discovery of new small-RNAs deriving from longer non-coding RNAs, including small-RNAs from rRNAs (srRNAs). Here, we systemically investigated srRNAs of maternal- or somatic-type 18S, 5.8S, 28S, with small-RNAseq from many zebrafish developmental stages. We identified new srRNAs for each rRNA. For 5.8S, we found srRNA consisting of the 5' or 3' halves, with only the latter having different sequence for the maternal- and somatic-types. For 18S, we discovered 21 nt srRNA from the 5' end of the 18S rRNA with a striking resemblance to microRNAs; as it is likely processed from a stem-loop precursor and present in human and mouse Argonaute-complexed small-RNA. For 28S, an abundant 80 nt srRNA from the 3' end of the 28S rRNA was found. The expression levels during embryogenesis of these srRNA indicate they are not generated from rRNA degradation and might have a role in the zebrafish development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".