What’s the target: understanding two decades of in silico microRNA-target prediction

Abstract

Motivation Since the initial discovery of microRNAs as post-transcriptional, regulatory key players in the 1990s, a total number of $2656$ mature microRNAs have been publicly described for Homo sapiens. As discovery of new miRNAs is still on-going, target identification remains to be an essential and challenging step preceding functional annotation analysis. One key challenge for researchers seems to be the selection of the most appropriate tool out of the larger multiverse of published solutions for a given research study set-up. Results In this review we collectively describe the field of in silico target prediction in the course of time and point out long withstanding principles as well as recent developments. By compiling a catalog of characteristics about the 98 prediction methods and identifying common and exclusive traits, we signpost a simplified mechanism to address the problem of application selection. Going further we devised interpretation strategies for common types of output as generated by frequently used computational methods. To this end, our work specifically aims to make prospective users aware of common mistakes and practical questions that arise during the application of target prediction tools. Availability An interactive implementation of our recommendations including materials shown in the manuscript is freely available at https://www.ccb.uni-saarland.de/mtguide.

miRNA Targets: From Prediction Tools to Experimental Validation

“…Another approach was proposed by Kern and colleagues [ 6 ], who have set up an interactive webpage, freely available on-line, which helps users perform tool selection by answering a six-step questionnaire based on different criteria.…”

“…Predicted interactions are commonly validated by Microarrays, qRT-PCR, Western blots, Luciferase assays, and some HT-methods including CLIP-seq and CLASH [ 6 ].…”

“…Despite strengths and weaknesses characterizing each strategy, the difference between transcriptomic and proteomic outcomes is crucial. Transcriptomic procedures search for mRNAs of interest and cannot detect repressed targets; on the other hand, proteomic procedures fail to differentiate cleavage from repression events, but certainly do not miss any regulatory effect [ 6 ].…”

“…Despite the growing knowledge about the mechanisms involved in miRNA-mRNA interaction, the identification of potential targets in the human genome is still a challenge, which has been appropriately described as “a classical needle in a haystack problem” [ 6 ].…”

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

“…Among these, microRNAs (miRNAs) are small non-coding RNAs, typically 18-25 nucleotides in length, loaded by proteins of the AGO-family to build RNA-induced silencing complexes (RISC) [1]. Gene regulation through the RISC complex is facilitated by one or two mature (−5p; −3p) miRNA arms, arising from one or several transcribed precursors [2]. Besides other modes of action, activated complexes target preferentially 3 -untranslated regions of mRNAs to induce either catalytic cleavage or translation repression.…”