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Although the use of adequate models of evolution should improve the accuracy of phylogenetic inference (Leitner, Kumar, and Albert 1997; Sullivan and Swofford 1997; Cunningham, Zhu, and Hillis 1998), computer simulation studies have shown that under certain circumstances, wrong models can recover the true tree with higher probability than the tree model employed to generate the data (Saitou and Nei 1987; Schöniger and von Haeseler 1993; Tajima and Takezaki 1994; Tateno, Takezaki, and Nei 1994; Yang 1997a; Takahashi and Nei 2000). These results have previously been attributed to the complexity of the topology estimation problem (Yang 1997a), but Bruno and Halpern (1999) have suggested that they could be better understood in terms of bias toward the true tree when the assumptions of the method are violated; in other words, getting the right answer for the wrong reason. There is no evidence of whether this ‘‘phylogenetic bias’’ actually occurs with real data. While there are empirical examples of ‘‘phylogenetic robustness’’ (complex models produce no better results than simpler ones) (Russo, Takezaki, and Nei 1996), we are not aware of cases in which the use of simpler models leads to a better phylogenetic estimate. We report here on an empirical example in which only the use of simpler, wrong models of evolution leads to the estimation of trees that are in agreement with biochemical and immunological evidence and with previous phylogenetic studies. DNA and amino acid sequences for the gag, pol, and env genes for 61–76 retroviral taxa were downloaded from GenBank. ClustalX (Thompson et al. 1997) was used for the alignment of the DNA and protein sequences. The best-fit model of DNA substitution for each data set was selected using Modeltest, version 1.05 (Posada and Crandall 1998). Neighbor-joining (NJ) trees (Saitou and Nei 1987) were constructed using uncorrected (NJp) and maximum-likelihood (NJml) distances for DNA and using mean character (5uncorrected) (NJmc) and maximum-likelihood (NJmlprot) distances for proteins. A heuristic search was carried out to find the most parsimonious (MP) tree(s). Unweighted (MPdna and MPprot) and weighted (MPstep, MPpars, and MPrice) MP trees were estimated. Three step matrices were used for the weighting. The DNAstep matrix was constructed in MacClade, version 3.07 (Maddison and Maddison 1994), on the NJ tree estimated using maximum-likelihood (ML) distances under the best-fitting model of nucleotide substitution

Simple (Wrong) Models for Complex Trees: A Case from Retroviridae