TY - JOUR
T1 - Pairwise local structural alignment of RNA sequences with sequence similarity less than 40%
AU - Havgaard, Jakob Hull
AU - Lyngsø, Rune B.
AU - Stormo, Gary D.
AU - Gorodkin, Jan
N1 - Funding Information:
This work was supported by the Danish Technical Research Council, the Ministry of Food, Agriculture and Fisheries, and the Danish Center for Scientific Computing. We thank Dave Mathews for the help with Dynalign.
PY - 2005/5/1
Y1 - 2005/5/1
N2 - Motivation: Searching for non-coding RNA (ncRNA) genes and structural RNA elements (eleRNA) are major challenges in gene finding today as these often are conserved in structure rather than in sequence. Even though the number of available methods is growing, it is still of interest to pairwise detect two genes with low sequence similarity, where the genes are part of a larger genomic region. Results: Here we present such an approach for pairwise local alignment which is based on FOLDALIGN and the Sankoff algorithm for simultaneous structural alignment of multiple sequences. We include the ability to conduct mutual scans of two sequences of arbitrary length while searching for common local structural motifs of some maximum length. This drastically reduces the complexity of the algorithm. The scoring scheme includes structural parameters corresponding to those available for free energy as well as for substitution matrices similar to RIBOSUM. The new FOLDALIGN implementation is tested on a dataset where the ncRNAs and eleRNAs have sequence similarity <40% and where the ncRNAs and eleRNAs are energetically indistinguishable from the surrounding genomic sequence context. The method is tested in two ways: (1) its ability to find the common structure between the genes only and (2) its ability to locate ncRNAs and eleRNAs in a genomic context. In case (1), it makes sense to compare with methods like Dynalign, and the performances are very similar, but FOLDALIGN is substantially faster. The structure prediction performance for a family is typically around 0.7 using Matthews correlation coefficient. In case (2), the algorithm is successful at locating RNA families with an average sensitivity of 0.8 and a positive predictive value of 0.9 using a BLAST-like hit selection scheme.
AB - Motivation: Searching for non-coding RNA (ncRNA) genes and structural RNA elements (eleRNA) are major challenges in gene finding today as these often are conserved in structure rather than in sequence. Even though the number of available methods is growing, it is still of interest to pairwise detect two genes with low sequence similarity, where the genes are part of a larger genomic region. Results: Here we present such an approach for pairwise local alignment which is based on FOLDALIGN and the Sankoff algorithm for simultaneous structural alignment of multiple sequences. We include the ability to conduct mutual scans of two sequences of arbitrary length while searching for common local structural motifs of some maximum length. This drastically reduces the complexity of the algorithm. The scoring scheme includes structural parameters corresponding to those available for free energy as well as for substitution matrices similar to RIBOSUM. The new FOLDALIGN implementation is tested on a dataset where the ncRNAs and eleRNAs have sequence similarity <40% and where the ncRNAs and eleRNAs are energetically indistinguishable from the surrounding genomic sequence context. The method is tested in two ways: (1) its ability to find the common structure between the genes only and (2) its ability to locate ncRNAs and eleRNAs in a genomic context. In case (1), it makes sense to compare with methods like Dynalign, and the performances are very similar, but FOLDALIGN is substantially faster. The structure prediction performance for a family is typically around 0.7 using Matthews correlation coefficient. In case (2), the algorithm is successful at locating RNA families with an average sensitivity of 0.8 and a positive predictive value of 0.9 using a BLAST-like hit selection scheme.
UR - http://www.scopus.com/inward/record.url?scp=16344363338&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/bti279
DO - 10.1093/bioinformatics/bti279
M3 - Article
C2 - 15657094
AN - SCOPUS:16344363338
SN - 1367-4803
VL - 21
SP - 1815
EP - 1824
JO - Bioinformatics
JF - Bioinformatics
IS - 9
ER -