Integrated analysis of miRNA and mRNA expression profiles in testes of Duroc and Meishan boars
Bibliographic record
Abstract
BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNAs playing vital roles in regulating posttranscriptional gene expression. Elucidating the expression regulation of miRNAs underlying pig testis development will contribute to a better understanding of boar fertility and spermatogenesis. RESULTS: In this study, miRNA expression profile was investigated in testes of Duroc and Meishan boars at 20, 75, and 270 days of age by high-throughput sequencing. Forty-five differentially expressed miRNAs were identified from testes of Duroc and Meishan boars before and after puberty. Integrated analysis of miRNA and mRNA profiles predicted many miRNA-mRNA pairs. Gene ontology and biological pathway analyses revealed that predicted target genes of ssc-mir-423-5p, ssc-mir-34c, ssc-mir-107, ssc-mir-196b-5p, ssc-mir-92a, ssc-mir-320, ssc-mir-10a-5p, and ssc-mir-181b were involved in sexual reproduction, male gamete generation, and spermatogenesis, and GnRH, Wnt, and MAPK signaling pathway. Four significantly differentially expressed miRNAs and their predicted target genes were validated by quantitative real-time polymerase chain reaction, and phospholipase C beta 1 (PLCβ1) gene was verified to be a target of ssc-mir-423-5p. CONCLUSIONS: This study provides an insight into the functional roles of miRNAs in testis development and spermatogenesis and offers useful resources for understanding differences in sexual function development caused by the change in miRNAs expression between Duroc and Meishan boars.
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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".