TRUEE; a bioinformatic pipeline to define the functional microRNA targetome of plants

Abstract

In plants, microRNAs (miRNAs) are short non-coding RNAs of approximately 20-24 nt in length which are involved in post-transcriptional regulation of genes controlling many fundamental biological pathways. They guide the miRNA Induced Silencing Complex (miRISC) to bind to target mRNAs of high complementarity where they are negative regulators of gene expression, acting via transcript cleavage and/or translational repression mechanism(s). Identifying functional miRNA-target interactions (MTIs) is central to understanding miRNA function, and this has led to the development of many miRNA target prediction tools. As high miRNA-target complementarity is required for a MTI in plants, it has been a central factor of these miRNA target prediction tools. However, most of these tools result in long lists of targets, for which there is no experimental evidence supporting the MTI, suggesting the majority of predicted targets are false positives. Furthermore, the degree of complementarity is often used to rank the likelihood of a predicted target as a miRNA target, however, many exceptions have been found. These limitations have impeded our understanding of miRNA biology and the functional scope of miRNA-mediated regulation in plants.

In this thesis, bioinformatic workflow is developed named TRUEE (Targets Ranked Using Experimental Evidence) that ranks MTIs on the extent to which they are subjected to miRNA-mediated cleavage. It sorts predicted targets into high (HE) and low evidence (LE) groupings based on the frequency and strength of miRNA-guided cleavage degradome signals across multiple degradome experiments. From this, each target is assigned a numerical value, termed a Category Score, ranking the extent to which it is subjected to miRNA-mediated cleavage. As a proof-of-concept, the 428 Arabidopsis miRNAs annotated in miRBase were processed through TRUEE to determine the miRNA "targetome". The vast majority of high-ranking Category Score targets corresponded to highly conserved MTIs, validating the workflow. Very few Arabidopsis-specific, Brassicaceae-specific, or conserved-passenger miRNAs had HE targets with high Category Scores. In total, only several hundred MTIs were found to have Category Scores characteristic of currently known physiologically significant MTIs. Although non-exhaustive, clearly the number of functional MTIs is much narrower than many studies claim.

As miRNA-target binding site complementarity is not a definitive indicator of a MTI, this suggests that there are other factors involved in miRNA-mediated regulation. To explore this, TRUEE was applied to conserved miRNAs to determine the identity of HE targets across species and to investigate potential additional factors involved in miRNA-mediated regulation. Firstly, for each conserved miRNA family, HE targets mostly consisted of one conserved primary target family. If an additional HE target family was identified, it was often functionally related to the former. This suggests that a plant miRNA may preferentially regulate genes that are involved in a functionally similar process. To investigate whether sequences beyond complementarity maybe facilitating MTIs, multiple sequences alignments of conserved target gene homologues were performed. In many instances, these alignments found conserved sequences flanking the miRNA-target binding site. Further bioinformatic analysis found that homologues containing these conserved flanking sequences were enriched in HE targets compared to LE targets, suggesting they are facilitating miRNA-mediated regulation. The function of these conserved sequences in the miR160 target, ARF10, were functionally tested. The introduction of synonymous point mutations in the flanking sequences of ARF10 attenuated its silencing by miR160. Together, these findings suggest that these ancient miRNA-target relationships, have developed regulatory complexities beyond complementarity that define them as strongly regulated target genes of miRNAs.