Abstract
Purpose: Evidence suggests that circulating serum microRNAs (miRNAs) might preferentially target immune-related mRNAs. If this were the case, we hypothesized that immune-related mRNAs would have more predicted serum miRNA binding sites than other mRNAs and, reciprocally, that serum miRNAs would have more immune-related mRNA targets than nonserum miRNAs. Materials and methods: We developed a consensus target predictor using the random forest framework and calculated the number of predicted miRNA-mRNA interactions in various subsets of miRNAs (serum, non-serum) and mRNAs (immune related, nonimmune related). Results: Immune-related mRNAs were predicted to be targeted by serum miRNA more than other mRNAs. Moreover, serum miRNAs were predicted to target many more immune-related mRNA targets than non-serum miRNAs; however, these two biases in immune-related mRNAs and serum miRNAs appear to be completely independent. Conclusion: Immune-related mRNAs have more miRNA binding sites in general, not just for serum miRNAs; likewise, serum miRNAs target many more mRNAs than non-serum miRNAs overall, regardless of whether they are immune related or not. Nevertheless, these two independent phenomena result in a significantly larger number of predicted serum miRNA-immune mRNA interactions than would be expected by chance.
| Original language | English |
|---|---|
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Advances and Applications in Bioinformatics and Chemistry |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2017 |
Keywords
- Biomarker
- Posttranscriptional regulation
- Random forest
- Target prediction
ASJC Scopus subject areas
- Chemistry (miscellaneous)
- Biochemistry
- Biochemistry, Genetics and Molecular Biology (miscellaneous)
- Computer Science Applications