Abstract
In this work, we present a computational screen conducted for functional RNA structures, resulting in over 100,000 conserved RNA structure elements found in alignments of mouse (mm10) against 59 other vertebrates. We explicitly included masked repeat regions to explore the potential of transposable elements and low-complexity regions to give rise to regulatory RNA elements. In our analysis pipeline, we implemented a four-step procedure: (i) we screened genome-wide alignments for potential structure elements using RNAz-2, (ii) realigned and refined candidate loci with LocARNA-P, (iii) scored candidates again with RNAz-2 in structure alignment mode, and (iv) searched for additional homologous loci in mouse genome that were not covered by genome alignments. The 3’-untranslated regions (3’-UTRs) of protein-coding genes and small noncoding RNAs are enriched for structures, while coding sequences are depleted. Repeat-associated loci make up about 95% of the homologous loci identified and are, as expected, predominantly found in intronic and intergenic regions. Nevertheless, we report the structure elements enriched in specific genome elements, such as 3’-UTRs and long noncoding RNAs (lncRNAs). We provide full access to our results via a custom UCSC genome browser trackhub freely available on our website (http://rna.tbi.univie.ac.at/trackhubs/#RNAz).
Highlights
RNAs fulfill a multitude of regulatory functions in the cell which are often mediated by a particular RNA structure
Our approach is based on RNAz [7,8], but it uses a novel pipeline with several improvements over previous screens
In contrast to the original pipeline, we mitigate some flaws of this first RNAz screen by introducing additional realignment and re-evaluation steps
Summary
RNAs fulfill a multitude of regulatory functions in the cell which are often mediated by a particular RNA structure. Functional—and evolutionarily conserved—RNA structures are abundant throughout the genome, both in the form of structured noncoding RNAs [1], as well as cis-regulatory structures within larger transcripts, such as messenger RNAs (mRNAs). To date, these functional elements remain poorly annotated, since they cannot be identified by high-throughput methods. Structure probing has been applied to mouse successfully [4] Such approaches suffer from the limited abundance of many transcripts, which leads to missing data at many nucleotide positions. By design, structural probing experiments only give information about the structuredness of the transcriptome and not about the
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