Structural partitioning, paired-sites models and evolution of the ITS transcript in Syzygium and Myrtaceae

Biffin, E., Harrington, M.G., Crisp, M.D., Craven, L.A., and Gadek, P.A. (2007) Structural partitioning, paired-sites models and evolution of the ITS transcript in Syzygium and Myrtaceae. Molecular Phylogenetics and Evolution, 43 (1). pp. 124-139.

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Abstract

The internal transcribed spacers (ITS) of nuclear ribosomal DNA are widely used for phylogenetic inference. Several characteristics, including the influence of RNA secondary structure on the mutational dynamics of ITS, may impact on the accuracy of phylogenies estimated from these regions. Here, we develop RNA secondary structure predictions for representatives of the angiosperm family Myrtaceae. On this basis, we assess the utility of structural (stem vs. loop) partitioning, and RNA-specific (paired-sites) models for a 76 taxon Syzygium alignment, and for a broader, family-wide Myrtaceae ITS data set. We use a permutation approach to demonstrate that structural partitioning significantly improves the likelihood of the data. Similarly, models that account for the non-independence of stem-pairs in RNA structure have a higher likelihood than those that do not. The best-fit RNA models for ITS are those that exclude simultaneous double substitutions in stem-pairs, which suggests an absence of strong selection against non-canonical (G•U/U•G) base-pairs at a high proportion of stem-paired sites. We apply the RNA-specific models to the phylogeny of Syzygium and Myrtaceae and contrast these with hypotheses derived using standard 4-state models. There is little practical difference amongst relationships inferred for Syzygium although for Myrtaceae, there are several differences. The RNA-specific approach finds topologies that are less resolved but are more consistent with conventional views of myrtaceous relationships, compared with the 4-state models.

Item ID: 2164
Item Type: Article (Refereed Research - C1)
Keywords: ITS1; ITS2; secondary structure; stems; loops; mutational dynamics; RNA-specific models; model selection; maximum likelihood; Bayesian analysis
ISSN: 1095-9513
Date Deposited: 20 May 2009 06:12
FoR Codes: 06 BIOLOGICAL SCIENCES > 0604 Genetics > 060409 Molecular Evolution @ 50%
06 BIOLOGICAL SCIENCES > 0603 Evolutionary Biology > 060399 Evolutionary Biology not elsewhere classified @ 50%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 100%
Citation Count from Web of Science Web of Science 27
Downloads: Total: 4
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