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ABSTRACT Structural characteristics are essential for the functioning of many noncoding RNAs and cis-regulatory elements of m RNAs. SNPs may disrupt these structures, interfere with their molecular function, and hence cause a phenotypic effect. RNA folding algorithms can provide detailed insights into structural effects of SNPs. The global measures employed so far suffer from limited accuracy of folding programs on large RNAs and are computationally too demanding for genome-wide applications. Here, we present a strategy that focuses on the local regions of maximal structural change between mutant and wild-type. These local regions are approximated in a 'screening mode' that is intended for genome-wide applications. Furthermore, localized regions are identified as those with maximal discrepancy. The mutation effects are quantified in terms of empirical P values. To this end, the RNAsnp software uses extensive precomputed tables of the distribution of SNP effects as function of length and GC content. RNAsnp thus achieves both a noise reduction and speed-up of several orders of magnitude over shuffling-based approaches. On a data set comprising 501 SNPs associated with human-inherited diseases, we predict 54 to have significant local structural effect in the untranslated region of m RNAs. RNAsnp is available at http://rth.dk/resources/rnasnp. [ABSTRACT FROM AUTHOR]

Self-contained structured domains of RNA sequences have often distinct molecular functions. Determining the boundaries of structured domains of a non-coding RNA (ncRNA) is needed for many ncRNA gene finder programs that predict RNA secondary structures in aligned genomes because these methods do not necessarily provide precise information about the boundaries or the location of the RNA structure inside the predicted ncRNA. Even without having a structure prediction, it is of interest to search for structured domains, such as for finding common RNA motifs in RNA-protein binding assays. The precise definition of the boundaries are essential for downstream analyses such as RNA structure modelling, e.g., through covariance models, and RNA structure clustering for the search of common motifs. Such efforts have so far been focused on single sequences, thus here we present a comparison for boundary definition between single sequence and multiple sequence alignments. We also present a novel approach, named RNAbound, for finding the boundaries that are based on probabilities of evolutionarily conserved base pairings. We tested the performance of two different methods on a limited number of Rfam families using the annotated structured RNA regions in the human genome and their multiple sequence alignments created from 14 species. The results show that multiple sequence alignments improve the boundary prediction for branched structures compared to single sequences independent of the chosen method. The actual performance of the two methods differs on single hairpin structures and branched structures. For the RNA families with branched structures, including transfer RNA (tRNA) and small nucleolar RNAs (snoRNAs), RNAbound improves the boundary predictions using multiple sequence alignments to median differences of −6 and −11.5 nucleotides (nts) for left and right boundary, respectively (window size of 200 nts). [ABSTRACT FROM AUTHOR]

• The Bacillaceae-1 RNA motif consists of two distinct classes. • Reverse complementary B-1 structure upstream of 16S rRNA has one stable motif. • Intergenic B-1 motifs have high structure diversity and may act as structural switch. Non-coding RNAs are key regulatory players in bacteria. Many computationally predicted non-coding RNAs, however, lack functional associations. An example is the Bacillaceae-1 RNA motif, whose Rfam model consists of two hairpin loops. We find the motif conserved in nine of 13 non-pathogenic strains of the genus Bacillus but only in one pathogenic strain. To elucidate functional characteristics, we studied 118 hits of the Rfam model in 11 Bacillus spp. and found two distinct classes based on the ensemble diversity of their RNA secondary structure and the genomic context concerning the ribosomal RNA (rRNA) cluster. Forty hits are associated with the rRNA cluster, of which all 19 hits upstream flanking of 16S rRNA have a reverse complementary structure of low structural diversity. Fifty-two hits have large ensemble diversity, of which 38 are located between two coding genes. For eight hits in Bacillus subtilis , we investigated public expression data under various conditions and observed either the forward or the reverse complementary motif expressed. Five hits are associated with the rRNA cluster. Four of them are located upstream of the 16S rRNA and are not transcriptionally active, but instead, their reverse complements with low structural diversity are expressed together with the rRNA cluster. The three other hits are located between two coding genes in non-conserved genomic loci. Two of them are independently expressed from their surrounding genes and are structurally diverse. In summary, we found that Bacillaceae-1 RNA motifs upstream flanking of ribosomal RNA clusters tend to have one stable structure with the reverse complementary motif expressed in B. subtilis. In contrast, a subgroup of intergenic motifs has the thermodynamic potential for structural switches. [ABSTRACT FROM AUTHOR]