Title of article :
Mapping circulating serum miRNAs to their immune-related target mRNAs
Author/Authors :
r Nosirov, Bakhtiyo Systems Immunology Lab - Osaka University, Suita , Billaud, Joël Systems Immunology Lab - Osaka University, Suita , Vandenbon, Alexis Systems Immunology Lab - Osaka University, Suita , Diez, Diego Systems Immunology Lab - Osaka University, Suita , Wijaya, Edward Systems Immunology Lab - Osaka University, Suita , Ishii, Ken J Systems Immunology Lab - Osaka University, Suita , Teraguchi, Shunsuke Systems Immunology Lab - Osaka University, Suita , Standley, Daron M Systems Immunology Lab - Osaka University, Suita
Pages :
9
From page :
1
To page :
9
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 non- serum miRNAs. Materials and methods: We developed a consensus target predictor using the random for- est 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.
Farsi abstract :
فاقد چكيده فارسي
Keywords :
biomarker , posttranscriptional regulation , random forest , target prediction
Journal title :
Advances and Applications in Bioinformatics and Chemistry: AABC
Serial Year :
2017
Full Text URL :
Record number :
2625543
Link To Document :
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