Building trees of algae: some advances in phylogenetic and evolutionary analysis

Abstract

Molecular phylogenetics has become a prominent aspect of algal systematics. The field of phylogenetic reconstruction is fast-evolving and novel techniques take time to penetrate taxonomic research. We highlight a selection of advances in phylogenetic inference and evolutionary analysis methods that could, in our opinion, benefit algal systematic studies. The focus of the paper is on model-based techniques. Following a brief introduction to maximum likelihood and Bayesian phylogenetic inference methods, we address model selection and partitioning strategies, and illustrate some issues concerning systematic error (phylogenetic bias), data saturation and tree rooting. We discuss the importance of experimental design (taxon and character sampling) and explore methods to test the reliability of phylogenetic results. Finally, we address methods for estimating ancestral states of discrete and continuous characters and techniques for dating phylogenetic trees. For each of these topics, we provide a brief circumscription, refer to the more specialized literature, and list a selection of software to carry out the analyses.

Keywords:

• ancestral state estimation
• Bayesian inference
• data saturation
• experimental design
• maximum likelihood
• model selection
• molecular clock
• molecular phylogenetics
• partitioning strategies
• systematic error
• topological uncertainty
• tree rooting

Acknowledgements

We thank Wytze Stam, Paul Lewis, Olivier De Clerck and Frederik Leliaert for commenting on previous versions of the manuscript. Funding was provided by FWO-Flanders (post-doctoral fellowship to HV). ET was supported by NSF EF 0629410, the Tony Institute, and the Jane and Roland Blumberg Centennial Professorship in Molecular Evolution.