Molecular systematics of Salmonidae: combined nuclear data yields a robust phylogeny
Introduction
The family Salmonidae comprises three subfamilies, Coregoninae (whitefish and ciscoes), Thymallinae (grayling), and Salmoninae (char, trout, and salmon). The most speciose of these, Salmoninae, includes five genera distributed throughout the Northern Hemisphere, Brachymystax (lenok), Hucho (huchen and taimen), Oncorhynchus (Pacific trout and salmon), Salmo (Atlantic salmon and brown trout), and Salvelinus (char) (Hart, 1973; Hendry and Stearns, 2003; Scott and Crossman, 1973). Salmonid fishes have long been of great interest due to the commercial and recreational value of some species, and they are becoming increasingly important as model systems for addressing a wide range of evolutionary and ecological questions (Elliot, 1994; Groot and Margolis, 1991; Hendry and Stearns, 2003). Inference of a robust phylogeny for this group is important for comparative analyses of salmonid adaptations (e.g., Crespi and Teo, 2002; Fleming, 1998), comparative genomics (e.g., Woram et al., 2003), studies involving inference of ancestral states (e.g., McDowall, 1997; McLennan, 1994; Stearley, 1992), and evaluation of conservation priorities (Crandall et al., 2000).
Despite the importance of salmonids to humans, and to terrestrial and marine ecosystems, their evolutionary history has remained a matter of considerable dispute for many years (e.g., Domanico et al., 1997; McKay et al., 1996; McPhail, 1997; Norden, 1961; Oakley and Phillips, 1999; Phillips and Oakley, 1997; Phillips and Pleyte, 1991; Regan, 1914; Utter et al., 1973; Utter and Allendorf, 1994). Previous species-level and genus-level phylogenetic research on salmonid fishes have provided insights into some relationships, but numerous questions remain, most notably the among-genus divergences, and species-level relationships within Oncorhynchus and Salvelinus.
The lack of a comprehensive, well-resolved and well-supported phylogeny for Salmonidae can be largely attributed to previous studies using relatively small subsets of extant salmonid diversity, and only one or at most several genes or other character sets (e.g., morphology or karyology). To overcome these limitations, we have assembled and analyzed all available DNA-sequence data for the species in this family. The main goals of our study are twofold: (1) to use these data to infer the best tree for the family as a whole, and for particular lineages; and (2) to assess what additional data (i.e., sequence from which genes) are needed to achieve a species-level tree for the entire group.
Section snippets
Data set
We compiled all of the available sequence data for salmonid fishes and one outgroup (Plecoglossus altivelis) (Salmoniformes: Osmeridae), which comprised 269 sequences of mitochondrial DNA (from 16 genes) and nuclear DNA (from 9 genes) for 31 species (Table 1). The bulk of these data were from Genbank, with several additional sequences graciously provided to us by T. Oakley and R. Phillips. Some species for which very little data were available (e.g., only one or several genes) were not
Phylogenetic analyses of individual and combined data
Bootstrap majority-rule consensus trees from analyses using maximum parsimony and maximum likelihood, and a posteriori clade support values from Bayesian analysis, are shown in Fig. 1 for each of the individual genes, and Fig. 2 shows maximum-parsimony bootstraps and Bayesian support for the combined data sets. The individual-gene trees differ considerably in the species included and the degree of support for various relationships. We assessed the degree of support for the main phylogenetic
Discussion
This is the first study of salmonid phylogenetics that uses virtually all of the DNA sequence data currently available. Our analyses of the data from each gene separately, followed by combined analyses of the mitochondrial data, the nuclear data, and the full combined data set, showed that the mitochondrial data yielded levels of resolution and support that were substantially lower than the nuclear data, and that the nuclear data showed higher levels of resolution and support than did the
Acknowledgements
We are grateful to Robert Behnke, Ian Fleming, Andrew Hendry, Todd Oakley, Ruth Phillips, Jerry Smith, Eric Taylor, John Taylor, Kyle Young, and two anonymous reviewers for helpful comments and discussion, and the Natural Sciences and Engineering Research Council of Canada for financial support.
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