Identification and characterization of sex‐biased and differentially expressed miRNAs in gonadal developments of the Chinese mitten crab, <i>Eriocheir sinensis</i>
Bibliographic record
Abstract
MicroRNA (miRNA) is a posttranscriptional downregulator that plays a vital role in a wide variety of biological processes. In this study, we constructed five ovarian and testicular small RNA libraries using two somatic libraries as reference controls for the identification of sex-biased miRNAs and gonadal differentially expressed miRNAs (DEMs) of the Chinese mitten crab, Eriocheir sinensis. A total of 535 known and 243 novel miRNAs were identified, including 312 sex-biased miRNAs and 402 gonadal DEMs. KEGG pathway analysis showed that DEM target genes were statistically enriched in MAPK, Wnt, and GnRH signaling pathway, and so on. A number of the sex-biased miRNAs target genes associated with sex determination/differentiation, such as IAG, Dsx, Dmrt1, and Fem1, while others target the genes related to gonadal development, such as P450s, Wnt, Ef1, and Tra-2c. Dual-luciferase reporter assay in vitro further confirmed that miR-34 and let-7b can downregulate IAG expression, miR-9-5p, let-7d, let-7b, and miR-8915 can downregulate Dsx. Taken together, these data strongly suggest a potential role for the sex-biased miRNAs in sex determination/differentiation and gonadal development in the crab.
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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".