RNA secondary structure, an important bioinformatics tool to enhance multiple sequence alignment: a case study (Sordariomycetes, Fungi)
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Periodical |
| Magazine / Source | Mycological Progress |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1007/s11557-012-0836-8 |
| Field | Biochemistry |
| Keywords | 2D structure; 2D mask; alignment; fungal phylogeny; 18 S rRNA; 28 S rRNA |
| Description | In a case study of fungi of the class Sordariomycetes, we evaluated the effect of multiple sequence alignment (MSA) on the reliability of the phylogenetic trees, topology and confidence of major phylogenetic clades. We compared two main approaches for constructing MSA based on (1) the knowledge of the secondary (2D) structure of ribosomal RNA (rRNA) genes, and automatic construction of MSA by four alignment programs characterized by different algorithms and evaluation methods, CLUSTAL, MAFFT, MUSCLE, and SAM. In the primary fungal sequences of the two functional rRNA genes, the nuclear small and large ribosomal subunits (18 S and 28 S), we identified four and six, respectively, highly variable regions, which correspond mainly to hairpin loops in the 2D structure. These loops are often positioned in expansion segments, which are missing or are not completely developed in the Archaeal and Eubacterial kingdoms. Proper sorting of these sites was a key for constructing an accurate MSA. We utilized DNA sequences from 28 S as an example for one-gene analysis. Five different MSAs were created and analyzed with maximum parsimony and maximum likelihood methods. The phylogenies inferred from the alignments improved with 2D structure with identified homologous segments, and those constructed using the MAFFT alignment program, with all highly variable regions included, provided the most reliable phylograms with higher bootstrap support for the majority of clades. We illustrate and provide examples demonstrating that re-evaluating ambiguous positions in the consensus sequences using 2D structure and covariance is a promising means in order to improve the quality and reliability of sequence alignments. |
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