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      Microbat paraphyly and the convergent evolution of a key innovation in Old World rhinolophoid microbats

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          Abstract

          Molecular phylogenies challenge the view that bats belong to the superordinal group Archonta, which also includes primates, tree shrews, and flying lemurs. Some molecular studies also challenge microbat monophyly and instead support an alliance between megabats and representative rhinolophoid microbats from the families Rhinolophidae (horseshoe bats, Old World leaf-nosed bats) and Megadermatidae (false vampire bats). Another molecular study ostensibly contradicts these results and supports traditional microbat monophyly, inclusive of representative rhinolophoids from the family Nycteridae (slit-faced bats). Resolution of the microbat paraphyly/monophyly issue is essential for reconstructing the temporal sequence and deployment of morphological character state changes associated with flight and echolocation in bats. If microbats are paraphyletic, then laryngeal echolocation either evolved more than once in different microbats or was lost in megabats after evolving in the ancestor of all living bats. To examine these issues, we used a 7.1-kb nuclear data set for nine outgroups and twenty bats, including representatives of all rhinolophoid families. Phylogenetic analyses and statistical tests rejected both Archonta and microbat monophyly. Instead, bats are in the superorder Laurasiatheria and microbats are paraphyletic. Further, the superfamily Rhinolophoidea is polyphyletic. The rhinolophoid families Rhinolophidae and Megadermatidae belong to the suborder Yinpterochiroptera along with rhinopomatids and megabats. The rhinolophoid family Nycteridae belongs to the suborder Yangochiroptera along with vespertilionoids, noctilionoids, and emballonuroids. These results resolve the apparent conflict between previous molecular studies that sampled different rhinolophoid families. An important implication of rhinolophoid polyphyly is independent evolution of key anatomical innovations associated with the nasal-emission of echolocation pulses.

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          Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea.

          A maximum likelihood method for inferring evolutionary trees from DNA sequence data was developed by Felsenstein (1981). In evaluating the extent to which the maximum likelihood tree is a significantly better representation of the true tree, it is important to estimate the variance of the difference between log likelihood of different tree topologies. Bootstrap resampling can be used for this purpose (Hasegawa et al. 1988; Hasegawa and Kishino 1989), but it imposes a great computation burden. To overcome this difficulty, we developed a new method for estimating the variance by expressing it explicitly. The method was applied to DNA sequence data from primates in order to evaluate the maximum likelihood branching order among Hominoidea. It was shown that, although the orangutan is convincingly placed as an outgroup of a human and African apes clade, the branching order among human, chimpanzee, and gorilla cannot be determined confidently from the DNA sequence data presently available when the evolutionary rate constancy is not assumed.
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            TESTING SIGNIFICANCE OF INCONGRUENCE

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              Likelihood-based tests of topologies in phylogenetics.

              Likelihood-based statistical tests of competing evolutionary hypotheses (tree topologies) have been available for approximately a decade. By far the most commonly used is the Kishino-Hasegawa test. However, the assumptions that have to be made to ensure the validity of the Kishino-Hasegawa test place important restrictions on its applicability. In particular, it is only valid when the topologies being compared are specified a priori. Unfortunately, this means that the Kishino-Hasegawa test may be severely biased in many cases in which it is now commonly used: for example, in any case in which one of the competing topologies has been selected for testing because it is the maximum likelihood topology for the data set at hand. We review the theory of the Kishino-Hasegawa test and contend that for the majority of popular applications this test should not be used. Previously published results from invalid applications of the Kishino-Hasegawa test should be treated extremely cautiously, and future applications should use appropriate alternative tests instead. We review such alternative tests, both nonparametric and parametric, and give two examples which illustrate the importance of our contentions.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                February 05 2002
                January 22 2002
                February 05 2002
                : 99
                : 3
                : 1431-1436
                Article
                10.1073/pnas.022477199
                122208
                11805285
                af3757a1-a4d1-49ba-8854-bf2d535cbb82
                © 2002
                History

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