Mapping circulating serum miRNAs to their immune-related target mRNAs

Bakhtiyor Nosirov, Joël Billaud, Alexis Vandenbon, Diego Diez, Edward Wijaya, Ken J. Ishii, Shunsuke Teraguchi*, Daron M. Standley

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)


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 languageEnglish
Pages (from-to)1-9
Number of pages9
JournalAdvances and Applications in Bioinformatics and Chemistry
Issue number1
Publication statusPublished - 2017
Externally publishedYes


  • Biomarker
  • Posttranscriptional regulation
  • Random forest
  • Target prediction


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