Rooting phylogenetic trees with distant outgroups: a case study from the commelinoid monocots

• Published in: Molecular biology and evolution 2002-10, Vol.19 (10), p.1769-1781
• Main Authors: Graham, Sean W, Olmstead, Richard G, Barrett, Spencer C H
• Format: Article
• Language: English
• Subjects: DNA, Chloroplast - genetics; Evolution, Molecular; Genes, Plant; Magnoliopsida - classification; Magnoliopsida - genetics; Models, Genetic; Phylogeny; Pontederiaceae - classification; Pontederiaceae - genetics
• ISSN: 0737-4038; 1537-1719
• DOI: 10.1093/oxfordjournals.molbev.a003999

Phylogenetic rooting experiments demonstrate that two chloroplast genes from commelinoid monocot taxa that represent the closest living relatives of the pickerelweed family, Pontederiaceae, retain measurable signals regarding the position of that family's root. The rooting preferences of the chloroplast sequences were compared with those for artificial sequences that correspond to outgroups so divergent that their signal has been lost completely. These random sequences prefer the three longest branches in the unrooted ingroup topology and do not preferentially root on the branches favored by real outgroup sequences. However, the rooting behavior of the artificial sequences is not a simple function of branch length. The random outgroups preferentially root on long terminal ingroup branches, but many ingroup branches comparable in length to those favored by random sequences attract no or few hits. Nonterminal ingroup branches are generally avoided, regardless of their length. Comparisons of the ease of forcing sequences onto suboptimal roots indicate that real outgroups require a substantially greater rooting penalty than random outgroups for around half of the least-parsimonious candidate roots. Although this supports the existence of nonrandomized signal in the real outgroups, it also indicates that there is little power to choose among the optimal and nearly optimal rooting possibilities. A likelihood-based test rejects the hypothesis that all rootings of the subtree using real outgroup sequences are equally good explanations of the data and also eliminates around half of the least optimal candidate roots. Adding genes or outgroups can improve the ability to discriminate among different root locations. Rooting discriminatory power is shown to be stronger, in general, for more closely related outgroups and is highly correlated among different real outgroups, genes, and optimality criteria.