Experimental and Molecular Medicine (Apr 2024)

Experimental capture of miRNA targetomes: disease-specific 3′UTR library-based miRNA targetomics for Parkinson’s disease

  • Martin Hart,
  • Fabian Kern,
  • Claudia Fecher-Trost,
  • Lena Krammes,
  • Ernesto Aparicio,
  • Annika Engel,
  • Pascal Hirsch,
  • Viktoria Wagner,
  • Verena Keller,
  • Georges Pierre Schmartz,
  • Stefanie Rheinheimer,
  • Caroline Diener,
  • Ulrike Fischer,
  • Jens Mayer,
  • Markus R. Meyer,
  • Veit Flockerzi,
  • Andreas Keller,
  • Eckart Meese

DOI
https://doi.org/10.1038/s12276-024-01202-5
Journal volume & issue
Vol. 56, no. 4
pp. 935 – 945

Abstract

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Abstract The identification of targetomes remains a challenge given the pleiotropic effect of miRNAs, the limited effects of miRNAs on individual targets, and the sheer number of estimated miRNA–target gene interactions (MTIs), which is around 44,571,700. Currently, targetome identification for single miRNAs relies on computational evidence and functional studies covering smaller numbers of targets. To ensure that the targetome analysis could be experimentally verified by functional assays, we employed a systematic approach and explored the targetomes of four miRNAs (miR-129-5p, miR-129-1-3p, miR-133b, and miR-873-5p) by analyzing 410 predicted target genes, both of which were previously associated with Parkinson’s disease (PD). After performing 13,536 transfections, we validated 442 of the 705 putative MTIs (62,7%) through dual luciferase reporter assays. These analyses increased the number of validated MTIs by at least 2.1-fold for miR-133b and by a maximum of 24.3-fold for miR-873-5p. Our study contributes to the experimental capture of miRNA targetomes by addressing i) the ratio of experimentally verified MTIs to predicted MTIs, ii) the sizes of disease-related miRNA targetomes, and iii) the density of MTI networks. A web service to support the analyses on the MTI level is available online ( https://ccb-web.cs.uni-saarland.de/utr-seremato ), and all the data have been added to the miRATBase database ( https://ccb-web.cs.uni-saarland.de/miratbase ).