Prediction and pan-cancer analysis of mammalian transcripts involved in target directed miRNA degradation

It is currently unknown how many RNA tran- scripts are able to induce degradation of microR- NAs (miRNA) via the mechanism known as target- directed miRNA degradation (TDMD). We developed TDMDfinder , a computational pipeline that identifies ‘high confidence’ TDMD interactions in the Human and Mouse transcriptomes by combining sequence alignment and feature selection approaches. Our pre- dictions suggested that TDMD is widespread, with potentially every miRNA controlled by endogenous targets. We experimentally tested 37 TDMDfinder predictions, of which 17 showed TDMD effects as measured by RT-qPCR and small RNA sequencing, linking the miR-17, miR-19, miR-30, miR-221, miR- 26 and miR-23 families to novel endogenous TD- MDs. In some cases, TDMD was found to affect dif- ferent members of the same miRNA family selec- tively. Features like complementarity to the miRNA 3′ region, bulge size and hybridization energy ap- peared to be the main factors determining sensitivity. Computational analyses performed using the multi- omic TCGA platform substantiated the involvement of many TDMD transcripts in human cancer and high- lighted 36 highly significant interactions, suggesting TDMD as a new potential oncogenic mechanism. In conclusion, TDMDfinder provides the first inventory of bona fide human and mouse TDMDs. Available as a free webtool, TDMDfinder allows users to search for any TDMD interaction of interest by customizing its selection criteria.