Systematic identification of edited microRNAs in the human brain

Abstract

Adenosine-to-inosine (A-to-I) editing modifies RNA transcripts from their genomic blueprint. A prerequisite for this process is a double-stranded RNA (dsRNA) structure. Such dsRNAs are formed as part of the microRNA (miRNA) maturation process, and it is therefore expected that miRNAs are affected by A-to-I editing. Editing of miRNAs has the potential to add another layer of complexity to gene regulation pathways, especially if editing occurs within the miRNA-mRNA recognition site. Thus, it is of interest to study the extent of this phenomenon. Current reports in the literature disagree on its extent; while some reports claim that it may be widespread, others deem the reported events as rare. Utilizing a next-generation sequencing (NGS) approach supplemented by an extensive bioinformatic analysis, we were able to systematically identify A-to-I editing events in mature miRNAs derived from human brain tissues. Our algorithm successfully identified many of the known editing sites in mature miRNAs and revealed 17 novel human sites, 12 of which are in the recognition sites of the miRNAs. We confirmed most of the editing events using in vitro ADAR overexpression assays. The editing efficiency of most sites identified is very low. Similar results are obtained for publicly available data sets of mouse brain-regions tissues. Thus, we find that A-to-I editing does alter several miRNAs, but it is not widespread.

Figure 1.

A schematic representation of the procedure for identifying editing sites in mature miRNAs using the brain sample data (for details, see Methods). In each one of the four steps (A–D), the total number of mismatches of any type is given in absolute numbers (bar chart) and in relative proportions (pie chart). (A) If the untrimmed reads are aligned against the known miRNA sequences, a strong signal of adenylation and uridylation is observed. (B) After trimming the 3′ end of the reads, A-to-G modifications become dominant. (C) If the trimmed reads are aligned against the genome and not directly against the miRNA sequences, the relative proportion of the A-to-G mismatches is enhanced as a result of less cross-mapping. (D) After possible sequencing errors are removed by using binomial statistics, only A-to-G modifications are observed.

Figure 2.

Sequence preference in the bases flanking the A-to-G editing sites detected in the human brain samples (A) and the mouse brain samples (C), in sequence Logo format (Crooks et al. 2004). (B,D) Sequence preference in the bases opposing the A-to-G editing sites for the human brain samples and the mouse brain samples, respectively.

Figure 3.

Novel human miRNA editing sites detected in the pooled brain and frontal lobe samples and validated using in vitro overexpression experiments in U87 and U118 cell-lines. The editing levels in four miRNAs are shown: (A) miR-455 5p mature position 17, confirmed by ADARB1 overexpression in both U87 and U118 cell-lines; (B) miR-421 mature position 14, confirmed by ADARB1 overexpression in both U87 and U118 cell-lines; (C) miR-381 mature position 4, confirmed by ADAR overexpression in the U87 cell-line; and (D) miR-497 mature position 2, confirmed by ADARB1 overexpression in the U118 cell-line. If the editing site is detected in the mouse brain data of Chiang et al. (2010), the editing levels in this tissue are also presented. The number of sequencing reads supporting the editing site is indicated on the bar. (E,F) The predicted change in mRNA targets as a result of editing in the binding site of miR-381 and miR-497, respectively.