MicroRNA Sequence Variation Potentially Contributes to Within-Species Functional Divergence in the Nematode<i>Caenorhabditis briggsae</i>
Bibliographic record
Abstract
Mounting evidence points to differences in gene regulation as a major source of phenotypic variation. MicroRNA-mediated post-transcriptional regulation has emerged recently as a key factor controlling gene activity during development. MicroRNA genes are abundant in genomes, acting as managers of gene expression by directing translational repression. Thus, understanding the role of microRNA sequence variation within populations is essential for fully dissecting the origin and maintenance of phenotypic diversity in nature. In this study, we investigate allelic variation at microRNA loci in the nematode Caenorhabditis briggsae, a close relative of C. elegans. Phylogeographic structure in C. briggsae partitions most strains from around the globe into a "temperate" or a "tropical" clade, with a few strains having divergent, geographically restricted genotypes. Remarkably, strains that follow this latitudinal dichotomy also differ in temperature-associated fitness. With this phylogeographic pattern in mind, we examined polymorphisms in 18 miRNAs in a global sample of C. briggsae isolates and tested whether newly isolated strains conform to this phylogeography. Surprisingly, nucleotide diversity is relatively high in this class of gene that generally experiences strong purifying selection. In particular, we find that miRNAs in C. briggsae are substantially more polymorphic than in Arabidopsis thaliana, despite similar background levels of neutral site diversity between the two species. We find that some mutations suggest functional divergence on the basis of requirements for target site recognition and computational prediction of the effects of the polymorphisms on RNA folding. These findings demonstrate the potential for miRNA polymorphisms to contribute to phenotypic variation within a species. Sequences were deposited in GenBank under accession nos. JN251323-JN251744.
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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 | 0.001 | 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".