Species tree inference in the age of genomics

Abstract

Species trees are an essential tool in conservation and evolutionary biology. In phylogenomics, not only is data choice (e.g.usingunlinked orthologs rather than paralogs) animportant systematic consideration, but thechoice of phylogenetic algorithm is also important. Since individual gene phylogenies candiffer from the true species phylogeny, newmethods have been proposed for species treeestimation using multiple unlinked genes.Improvements in genome sequencing technologies have increased the amount of dataavailable to researchers and this has increasedthe utility of multilocus species tree inferencemethods. The Bayesian methods BEST and*BEAST that incorporate a coalescent model toaccount for gene tree and species tree conflictoffer promising advances in species tree inference directly from DNA sequences. Methodsthat infer species trees from gene trees ratherthan directly from sequence data such as STAR, STEAC, NJ st and the likelihood method STEM have been recently developed as computationally efficient alternatives. Bayesian concordance analysis, which has been shown toperform well when horizontal gene transfer isthe cause of gene tree and species tree conflict, is also discussed. Furthermore, methodsfor species delimitation including a non-para-metric species tree inference method that doesnot require a priorispecies assignments canremove subjectivity from species delimitation.Here, I review the assumptions, requiredinputs, and the performance of these methodsunder simulation and in recent empirical studies. Researchers in many disciplines shouldunderstand the methods available for phylogenomic species tree inference in order toenhance evolutionary and conservation studies. © Copyright N.V. Whelan, 2011.