Does direct optimization produce more accurate alignments and topologies? POY vs. ClustalW+PAUP*

—Direct optimization frameworks for simultaneously estimating alignments and phylogenies have recently been developed. One such method, implemented in the program POY, is becoming more common for analyses of variable length sequences (e.g., analyses using ribosomal genes) and for combined evidence analyses (morphology + multiple genes). Simulation of sequences containing insertion and deletion events was performed in order to directly compare a widely used method of multiple sequence alignment (ClustalW) and subsequent parsimony analysis in PAUP* with direct optimization via POY. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (clocklike, non-clocklike, and ultrametric). Alignment accuracy scores for the implied alignments from POY and the multiple sequence alignments from ClustalW were calculated and compared. In almost all cases (99.95%), ClustalW produced more accurate alignments than POY-implied alignments, judged by the proportion of correctly identified homologous sites. Topological accuracy (distance to the true tree) for POY topologies and topologies generated under parsimony in PAUP* from the ClustalW alignments were also compared. In 44.94% of the cases, Clustal alignment tree reconstructions via PAUP* were more accurate than POY, whereas in 16.71% of the cases POY reconstructions were more topologically accurate (38.38% of the time they were equally accurate). Comparisons between POY hypothesized alignments and the true alignments indicated that, on average, as alignment error increased, topological accuracy decreased. [ClustalW; direct optimization; multiple sequence alignment; parsimony; phylogenetics; POY; sensitivity analysis; simulation; tree reconstruction. ] There are many approaches available for phylogenetic analysis of DNA sequence information. Traditionally, most analyses proceed as a two-step process, first moving from raw sequence data to a multiple sequence alignment and then, secondarily, using the multiple sequence alignment to estimate a phylogeny. For the first step, there are dozens of programs and algorithms available that will perform multiple sequence alignment. Once the multiple sequence alignment (data matrix) is created, the data are analyzed by tree building methodologies resulting in hypothesized trees that are used to infer the evolution of the sequences (and ultimately the organisms themselves). Among the most widely used tree reconstruction approaches are neighbor joining, parsimony, maximum likelihood, and Bayesian approaches. Recently, however, other approaches have surfaced that can analyze DNA sequence data in a different framework. Direct optimization (DO) is an alternative approach for phylogenetic analysis in which no prior multiple sequence alignment is required. This idea has attracted much attention due to the fact that empirically derived phylogenies may be more dependent upon the alignment method than on the mode of phylogenetic reconstruction (Cammarano et al., 1999; Hwang et al., 1998; Kjer, 1995, 2004; Lake, 1991; Morrison and Ellis, 1997; Mugridge et al., 2000; Ogden and Whiting, 2003; Thorne and Kishino, 1992; Titus and Frost, 1996; Xia et al., 2003). Although some related ideas concerning optimization heuristics for raw sequence data existed prior to DO (Hein, 1989a, 1989b; Hogeweg and Hesper, 1984; Sankoff, 1975; Thorne et al., 1991), Wheeler (1996) developed an automated cladistic or parsimony approach. DO, formerly known as optimization alignment, was devised to counter the lack of interaction between topology and putative homology (Wheeler, 2001) and to assess directly the transformations, indels, or other evolutionary events simultaneously in a topological framework without the use of multiple sequence alignment (Wheeler, 1996). The strategy is implemented in the program POY (Wheeler et al., 2003), which can invoke both parsimony and likelihood as optimality criteria (Wheeler, 2006). Recently, a number of similar approaches to DO that implement Bayesian or likelihood models in a combined analysis framework have also been proposed (Fleissner et al., 2005; Lunter et al., 2005; Redelings and Suchard, 2005). DO is a novel theoretical approach to phylogenetic estimation that attempts to avoid the problems of alignment by generalizing phylogenetic character analysis to include insertion/deletion events. Although theoretical arguments for and against DO, and POY in particular, exist (Giribet, 2001, 2005; Kjer, 2004; Ogden et al., 2005; Phillips et al., 2000; Simmons, 2004; Simmons and Ochoterena, 2000; Wheeler, 2001, 2003), there have been no accuracy comparative analyses performed to evaluate “alternative phylogenetic methods or models” (de Queiroz and Poe, 2001), although some studies have used other forms of comparison (for example, ILD and likelihood scores) to examine the performance of POY versus other alignment methods (Terry and Whiting, 2005; Whiting et al., 2006). During revision of this paper we became aware of an accepted paper that investigates a comparison of POY versus structural alignment (Kjer et al., 2007). We were interested in using simulation to directly compare ClustalW and subsequent parsimony analysis in PAUP* with DO via POY. Many studies have used simulated fixed data sets (usually with no insertions or deletions) to examine topological accuracy of phylogenetic reconstruction methods (e.g., Hillis, 1995; Huelsenbeck and Rannala, 2004; Nei, 1996; Rosenberg and Kumar, 2003; Takahashi and Nei, 2000,