Journal
HUMAN MUTATION
Volume 34, Issue 4, Pages 546-556Publisher
WILEY-HINDAWI
DOI: 10.1002/humu.22273
Keywords
RNA secondary structure; structural disruption; gene regulation; disease
Categories
Funding
- Danish Center for Scientific Computing (DCSC, DeiC)
- European Community [222664]
- German BMBF project ICGC MMML-Seq [01KU1002J]
- Danish Council for Strategic Research (Programme Commission on Strategic Growth Technologies)
- Danish Council for Independent Research (Technology and Production Sciences)
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Structural characteristics are essential for the functioning of many noncoding RNAs and cis-regulatory elements of mRNAs. 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 mRNAs. RNAsnp is available at http://rth.dk/resources/rnasnp.
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