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Updated: Jun 12, 2026

The ITS2 Database
Published on: March 12, 2012
The impact of rRNA secondary structure consideration in alignment and tree reconstruction: simulated data and a case
Harald O Letsch1, Patrick Kück, Roman R Stocsits
1Molecular Biodiversity Research Unit, Zoologisches Forschungsmuseum Alexander Koenig, Bonn, Germany. hletsch@uni-bonn.de
Abstract:
The use of secondary structures has been advocated to improve both the alignment and the tree reconstruction processes of ribosomal RNA (rRNA) data sets. We used simulated and empirical rRNA data to test the impact of secondary structure consideration in both steps of molecular phylogenetic analyses. A simulation approach was used to generate realistic rRNA data sets based on real 16S, 18S, and 28S sequences and structures in combination with different branch length and topologies. Alignment and tree reconstruction performance of four recent structural alignment methods was compared with exclusively sequence-based approaches. As empirical data, we used a hexapod rRNA data set to study the influence of nucleotide interdependencies in sequence alignment and tree reconstruction. Structural alignment methods delivered significantly better sequence alignments compared with pure sequence-based methods. Also, structural alignment methods delivered better trees judged by topological congruence to simulation base trees. However, the advantage of structural alignments was less pronounced and even vanished in several instances. For simulated data, application of mixed RNA/DNA models to stems and loops, respectively, led to significantly shorter branches. The application of mixed RNA/DNA models in the hexapod analyses delivered partly implausible relationships. This can be interpreted as a stronger sensitivity of mixed model setups to nonphylogenetic signal. Secondary structure consideration clearly influenced sequence alignment and tree reconstruction of ribosomal genes. Although sequence alignment quality can considerably be improved by the use of secondary structure information, the application of mixed models in tree reconstructions needs further studies to understand the observed effects.
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