OrbId

Abstract

MicroRNAs coordinate networks of mRNAs, but predicting specific sites of interactions is complicated by the very few bases of complementarity needed for regulation. Although efforts to characterize the specific requirements for microRNA (miR) regulation have made some advances, no general model of target recognition has been widely accepted. In this work, we describe an entirely novel approach to miR target identification. The genomic events responsible for the creation of individual miR loci have now been described with many miRs now known to have been initially formed from transposable element (TE) sequences. In light of this, we propose that limiting miR target searches to transcripts containing a miR’s progenitor TE can facilitate accurate target identification. In this report we outline the methodology behind OrbId (Origin-based identification of microRNA targets). In stark contrast to the principal miR target algorithms (which rely heavily on target site conservation across species and are therefore most effective at predicting targets for older miRs), we find OrbId is particularly efficacious at predicting the mRNA targets of miRs formed more recently in evolutionary time. After defining the TE origins of > 200 human miRs, OrbId successfully generated likely target sets for 191 predominately primate-specific human miR loci. While only a handful of the loci examined were well enough conserved to have been previously evaluated by existing algorithms, we find ~80% of the targets for the oldest miR (miR-28) in our analysis contained within the principal Diana and TargetScan prediction sets. More importantly, four of the 15 OrbId miR-28 putative targets have been previously verified experimentally. In light of OrbId proving best-suited for predicting targets for more recently formed miRs, we suggest OrbId makes a logical complement to existing, conservation based, miR target algorithms.

Continuing analysis of microRNA origins

“…1). Now confirmed in several subsequent analyses, [16][17][18][19][20][25][26][27] their model indicates that transcription across neighboring TE insertions on opposite strands, followed by DICER processing and RISC incorporation, was initially responsible for the formation of the majority of functional miR loci. In addition, a transposable element-based miR origin suggests an additionally advantageous role for continued genome colonization-the miRs formed by this mechanism would likely be able to repress any mRNAs bearing sequences obtained from that miR's progenitor TE.…”

“…MicroRNA target prediction As we have now described the TEs responsible for forming over 3,300 distinct microRNA genomic loci 24 and have previously demonstrated the utility of this information in predicting human miR targets, 19 we next examined origin-based target prediction in additional species. To achieve this, we selected Gallus gallus (chicken) miR-6672 (which we found was originally formed from CR1 sequences) and Sus scrufa (pig) miR-4331(which we found was originally formed from PRE1 sequences) to predict mRNA targets utilizing our OrBId methodology which requires a shared origin common to both a miR and its target.…”

“…To achieve this, we selected Gallus gallus (chicken) miR-6672 (which we found was originally formed from CR1 sequences) and Sus scrufa (pig) miR-4331(which we found was originally formed from PRE1 sequences) to predict mRNA targets utilizing our OrBId methodology which requires a shared origin common to both a miR and its target. 19 Importantly, this strategy requires the sites targeted by a particular miR to contain a complete miR seed match and at least 50% of sequence identity between sequences immediately flanking a mature miR (in the pre-miR) and the sequences immediately flanking a putative mRNA target site. Examples of alignments between each miR, progenitor TEs and putative targets are illustrated in Figure 6.…”

“…[8][9][10][11][12][13][14][15] While the genomic origins for the majority of miRs and their mRNA target sites remain undescribed, a relationship between miRs and TEs has long been suggested and the random nature of TE colonization has caused several groups to adopt a similar mechanism for the establishment of functional miRs. [16][17][18][19][20] As approximately half of the human genome is composed of TEs 21 and as much as 80% of plant genomes 18 are comprised of TE sequences, widespread TE colonization is a hallmark of the genomes of higher, more complex organisms. Although long thought to be detrimental to genomic integrity (as TE insertions into coding sequences are usually detrimental), strikingly over 50% of metazoan transcripts bear at least some amount of TE sequence (typically in their 3′ or 5′UTRs).…”

“…While there are several additional implications of miRs originating from TE sequences (e.g., determining transcriptional regulation 16 ), our recently developed miR target prediction algorithm (OrbId: Origin-based identification of microRNA targets 19 ) suggests that a particularly advantageous utility for this information is the refinement of target prediction through restricting putative targets to mRNAs which contain the TE giving rise to a particular miR. Therefore, in light of our having previously defined the genomic events behind the formation of over 2,300 distinct miRs 24 and having successfully developed a novel miR target prediction algorithm utilizing this information to accurately predict mRNAs targeted by miRs clearly formed from TE sequences, 19 this report now details our continuing analysis of this topic -a comprehensive update examining the over 7,000 novel miRs described since our initial study. 28 To our surprise, in addition to characterizing over 1,000 new miR molecular origins from TEs, we also find evidence suggesting that a subset of miRs actually arose from a distinct, previously undescribed mechanism -RNA structural alteration resulting from point mutations to noncoding RNAs such as tRNAs and snoRNAs.…”