miRNAs Do Not Regulate Circadian Protein Synthesis in the Dinoflagellate Lingulodinium polyedrum
Bibliographic record
Abstract
Dinoflagellates have been shown to express miRNA by bioinformatics and RNA blot (Northern) analyses. However, it is not yet known if miRNAs are able to alter gene expression in this class of organisms. We have assessed the possibility that miRNA may mediate circadian regulation of gene expression in the dinoflagellate Lingulodinium polyedrum using the Luciferin Binding Protein (LBP) as a specific example. LBP is a good candidate for regulation by miRNA since mRNA levels are constant over the daily cycle while protein synthesis is restricted by the circadian clock to a period of several hours at the start of the night phase. The transcriptome contains a potential DICER and an ARGONAUTE, suggesting the machinery for generating miRNAs is present. Furthermore, a probe directed against an abundant Symbiodinium miRNA cross reacts on Northern blots. However, L. polyedrum has no small RNAs detectable by ethidium bromide staining, even though higher plant miRNAs run in parallel are readily observed. Illumina sequencing of small RNAs showed that the majority of reads did not have a match in the L. polyedrum transcriptome, and those that did were almost all sense strand mRNA fragments. A direct search for 18-26 nucleotide long RNAs capable of forming duplexes with a 2 base 3' overhang detected 53 different potential miRNAs, none of which was able to target any of the known circadian regulated genes. Lastly, a microscopy-based test to assess synthesis of the naturally fluorescent LBP in single cells showed that neither double-stranded nor antisense lbp RNA introduced into cells by microparticle bombardment prior to the time of LBP synthesis were able to reduce the amount of LBP produced. Taken together, our results indicate that circadian control of protein synthesis in L. polyedrum is not mediated by miRNAs.
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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".