Comparative transcriptomics analysis of testicular miRNA from indicine and taurine cattle
Bibliographic record
Abstract
Numerous studies have shown that several microRNAs (miRNAs) are specifically expressed in testis, play an essential role in regulating testicular spermatogenesis. Hainan and Mongolian cattle are two representative Chinese native cattle breeds representing Bos indicus (indicine cattle) and Bos taurus (taurine cattle), respectively, which are distributed in hot Hainan and cold Inner Mongolia province. To study the functional differences of miRNA in spermatogenesis between indicine and taurine cattle, six mature testes samples from indicine cattle (n = 3) and taurine cattle (n = 3) were collected, respectively. We detected miRNA expression using small RNA sequencing technology following bioinformatic analysis. A total of 578 known miRNAs and 132 novel miRNAs were detected in the six libraries. Among the 710 miRNAs, 564 miRNAs were expressed in both indicine and taurine cattle, 73 miRNAs were found solely in indicine cattle and 73 miRNAs were found solely in taurine cattle. After further analysis, among the miRNAs were identified in both indicine and taurine cattle, 184 miRNAs were differentially expressed (|log2 fold change| ≥ 1 and corrected p-value <0.05). Among the miRNAs that were only expressed in indicine cattle, 10 miRNAs were differentially expressed, whereas, among the miRNAs that were only expressed in taurine cattle, six miRNAs were differentially expressed. The enrichment analysis result showed that predicted target genes of a total of 200 differentially expressed miRNAs were enriched on some testicular spermatogenesis-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, especially mitogen-activated protein kinase (MAPK) signaling pathway. These findings identify miRNAs as key factors to regulate spermatogenesis in both indicine and taurine cattle, which may also be helpful for improving cattle reproductive performance in future studies.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".