Diversity in parasitic nematode genomes: the microRNAs of Brugia pahangi and Haemonchus contortus are largely novel
Bibliographic record
Abstract
BACKGROUND: MicroRNAs (miRNAs) play key roles in regulating post-transcriptional gene expression and are essential for development in the free-living nematode Caenorhabditis elegans and in higher organisms. Whether microRNAs are involved in regulating developmental programs of parasitic nematodes is currently unknown. Here we describe the the miRNA repertoire of two important parasitic nematodes as an essential first step in addressing this question. RESULTS: The small RNAs from larval and adult stages of two parasitic species, Brugia pahangi and Haemonchus contortus, were identified using deep-sequencing and bioinformatic approaches. Comparative analysis to known miRNA sequences reveals that the majority of these miRNAs are novel. Some novel miRNAs are abundantly expressed and display developmental regulation, suggesting important functional roles. Despite the lack of conservation in the miRNA repertoire, genomic positioning of certain miRNAs within or close to specific coding genes is remarkably conserved across diverse species, indicating selection for these associations. Endogenous small-interfering RNAs and Piwi-interacting (pi)RNAs, which regulate gene and transposon expression, were also identified. piRNAs are expressed in adult stage H. contortus, supporting a conserved role in germline maintenance in some parasitic nematodes. CONCLUSIONS: This in-depth comparative analysis of nematode miRNAs reveals the high level of divergence across species and identifies novel sequences potentially involved in development. Expression of novel miRNAs may reflect adaptations to different environments and lifestyles. Our findings provide a detailed foundation for further study of the evolution and function of miRNAs within nematodes and for identifying potential targets for intervention.
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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 | 0.000 |
| 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 | 0.001 |
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".