PHYLOGENETIC INFERENCE FROM RESTRICTION ENDONUCLEASE CLEAVAGE SITE MAPS WITH PARTICULAR REFERENCE TO THE EVOLUTION OF HUMANS AND THE APES.

Abstract

Recombinant DNA technology provides evolutionary biologists with another tool for making phylogenetic inference through contrasts of restriction endounuclease cleavage site maps or DNA sequences between homologous DNA segments found in different groups. This paper is limited to the problem of making phylogenetic inference from restriction site maps. Several methods for making such inference have already been used or proposed (Avise et al., 1979a, 1979b;NeiandLi, 1979; Ferris et al., 1981), but all these methods depend upon the assumption that shared restriction sites reflect common evolutionary origins and are not the result of convergent evolution. Unfortunately, convergent evolution occurs with high probability for this type of data (Templeton, 1983). In addition, data from several different restriction enzymes are generally pooled in these analyses. Recently, Adams and Rothman (1982) have examined the distributions of cleavage sites and related sequences for 54 restriction endonucleases. They concluded 1) that cleavage sites and related sequences are distributed non-randomly in most DNA sequences, 2) that there is considerable heterogeneity between different restriction enzymes (even those with recognition sequences of the same length) with respect to the number and distribution of their respective cleavage sites and related sequences, and 3) that inference of phylogenetic relationship based on distances will be biased. In addition, Brown et al. (1982) sequenced 896 base pairs of the mitochondrial DNA from humans and apes and concluded that about 90% of the substitutions were transitions. The predominance of transitions over transversions increases the probability of convergence over that expected when all base substitutions are assumed to be equally likely (Templeton, 1983). Therefore, a need exists for an algorithm of phylogenetic inference that deals more directly with the problem of convergent evolution and statistical inhomogeneity between different restriction enzymes. In this paper, I propose such an algorithm. After discussing the problem of estimation of a phylogenetic tree, the task of statistical testing is then addressed. First, I present a non-parametric statistical framework for testing the fit of one hypothesized phylogeny versus an alternative phylogeny. Second, non-parametric statistical procedures are presented for testing hypotheses about relative rates of evolution among the various lineages.