RNAscClust: Clustering RNA sequences using structure conservation and graph based motifs

TY - JOUR

T1 - RNAscClust

T2 - Clustering RNA sequences using structure conservation and graph based motifs

AU - Miladi, Milad

AU - Junge, Alexander

AU - Costa, Fabrizio

AU - Seemann, Stefan E.

AU - Havgaard, Jakob Hull

AU - Gorodkin, Jan

AU - Backofen, Rolf

PY - 2017

Y1 - 2017

N2 - Motivation: Clustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account. Results: Here, we present RNAscClust, the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments.

AB - Motivation: Clustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account. Results: Here, we present RNAscClust, the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments.

U2 - 10.1093/bioinformatics/btx114

DO - 10.1093/bioinformatics/btx114

M3 - Journal article

C2 - 28334186

AN - SCOPUS:85024483430

SN - 1367-4803

VL - 33

SP - 2089

EP - 2096

JO - Bioinformatics

JF - Bioinformatics

IS - 14

ER -