All Title Author
Keywords Abstract

PLOS ONE  2007 

Dating Phylogenies with Hybrid Local Molecular Clocks

DOI: 10.1371/journal.pone.0000879

Full-Text   Cite this paper   Add to My Lib


Background Because rates of evolution and species divergence times cannot be estimated directly from molecular data, all current dating methods require that specific assumptions be made before inferring any divergence time. These assumptions typically bear either on rates of molecular evolution (molecular clock hypothesis, local clocks models) or on both rates and times (penalized likelihood, Bayesian methods). However, most of these assumptions can affect estimated dates, oftentimes because they underestimate large amounts of rate change. Principal Findings A significant modification to a recently proposed ad hoc rate-smoothing algorithm is described, in which local molecular clocks are automatically placed on a phylogeny. This modification makes use of hybrid approaches that borrow from recent theoretical developments in microarray data analysis. An ad hoc integration of phylogenetic uncertainty under these local clock models is also described. The performance and accuracy of the new methods are evaluated by reanalyzing three published data sets. Conclusions It is shown that the new maximum likelihood hybrid methods can perform better than penalized likelihood and almost as well as uncorrelated Bayesian models. However, the new methods still tend to underestimate the actual amount of rate change. This work demonstrates the difficulty of estimating divergence times using local molecular clocks.


[1]  Zuckerkandl E, Pauling L, Bryson V, Vogel HJ (1965) Evolutionary divergence and convergence in proteins. Evolving genes and proteins. New York: Academic Press. pp. 97–166.
[2]  Felsenstein J (2003) Inferring phylogenies. Sunderland, Massachusets: Sinauer.
[3]  Bromham L, Penny D (2003) The modern molecular clock. Nat Rev Genet 4: 216–224.
[4]  Kishino H, Hasegawa M (1990) Converting distance to time: application to human evolution. Method Enzymol 183: 550–570.
[5]  Rambaut A, Bromham L (1998) Estimating divergence dates from molecular sequences. Mol Biol Evol 15: 442–448.
[6]  Yoder AD, Yang Z (2000) Estimation of primate speciation dates using local molecular clocks. Mol Biol Evol 17: 1081–1090.
[7]  Yang Z, Yoder AD (2003) Comparison of likelihood and Bayesian methods for estimating divergence times using multiple gene loci and calibration points, with application to a radiation of cute-looking mouse lemur species. Syst Biol 52: 705–716.
[8]  Sanderson MJ (1997) A nonparametric approach to estimating divergence times in the absence of rate constancy. Mol Biol Evol 14: 1218–1232.
[9]  Sanderson MJ (2002) Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Mol Biol Evol 19: 101–109.
[10]  Hastie T, Tibshirani R, Friedman JH (2001) The elements of statistical learning. New York: Springer-Verlag.
[11]  Thorne JL, Kishino H, Painter IS (1998) Estimating the rate of evolution of the rate of molecular evolution. Mol Biol Evol 15: 1647–1657.
[12]  Ho SY, Phillips MJ, Drummond AJ, Cooper A (2005) Accuracy of rate estimation using relaxed-clock models with a critical focus on the early metazoan radiation. Mol Biol Evol 22: 1355–1363.
[13]  Drummond AJ, Ho SY, Phillips MJ, Rambaut A (2006) Relaxed phylogenetics and dating with confidence. PLoS Biol 4: e88.
[14]  Huelsenbeck JP, Larget B, Swofford DL (2000) A compound Poisson process for relaxing the molecular clock. Genetics 154: 1879–1892.
[15]  Rannala B (2002) Identifiability of parameters in MCMC Bayesian inference of phylogeny. Syst Biol 51: 754–760.
[16]  Aris-Brosou S, Yang Z (2003) Bayesian models of episodic evolution support a late precambrian explosive diversification of the metazoa. Mol Biol Evol 20: 1947–1954.
[17]  Welch JJ, Fontanillas E, Bromham L (2005) Molecular dates for the “cambrian explosion”: the influence of prior assumptions. Syst Biol 54: 672–678.
[18]  Won H, Renner S (2006) Dating dispersal and radiation in the Gymnosperm Gnetum (Gnetales)? clock calibration when outgroup relationships are uncertain. Syst Biol 55: 610–622.
[19]  Yang Z (2004) A heuristic rate smoothing procedure for maximum likelihood estimation of species divergence times. Acta Zool Sinica 50: 645–656.
[20]  Yang Z (2006) Computational molecular evolution. Oxford: Oxford University Press.
[21]  Edwards AW (1992) Likelihood. Baltimore and London: John Hopkins University Press.
[22]  Kishino H, Thorne JL, Bruno WJ (2001) Performance of a divergence time estimation method under a probabilistic model of rate evolution. Mol Biol Evol 18: 352–361.
[23]  Yang Z (1997) PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci 13: 555–556.
[24]  Hartigan JA, Wong MA (1979) A K-means clustering algorithm. Appl Stat 28: 100–108.
[25]  Kaufman L, Rousseeuw PJ (1990) Finding groups in data : an introduction to cluster analysis. New York: Wiley.
[26]  Tibshirani R, Walther G, Hastie T (2001) Estimating the number of clusters in a data set via the gap statistic. J Roy Stat Soc B 63: 411–423.
[27]  Pollard KS, van der Laan MJ (2002) Statistical inference for simultaneous clustering of gene expression data. Math Biosci 176: 99–121.
[28]  van der Laan M, Pollard KS (2003) A new algorithm for hybrid hierarchical clustering with visualization and the bootstrap. J Stat Plan Infer 117: 275–303.
[29]  Pagel M, Meade A, Barker D (2004) Bayesian estimation of ancestral character states on phylogenies. Syst Biol 53: 673–684.
[30]  Prud'homme B, Gompel N, Rokas A, Kassner VA, Williams TM, et al. (2006) Repeated morphological evolution through cis-regulatory changes in a pleiotropic gene. Nature 440: 1050–1053.
[31]  Ronquist F, Huelsenbeck JP (2003) MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 1572–1574.
[32]  Goldman N, Yang Z (1994) A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol Biol Evol 11: 725–736.
[33]  Smith AB, Pisani D, Mackenzie-Dodds JA, Stockley B, Webster BL, et al. (2006) Testing the molecular clock: Molecular and paleontological estimates of divergence times in the Echinoidea (Echinodermata). Mol Biol Evol 23: 1832–1851.
[34]  Tavare S (1986) Some probabilistic and statistical problems in the analysis of DNA sequences. Lectures on Mathematics in the Life Sciences 17: 57–86.
[35]  Yang Z (1994) Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. J Mol Evol 39: 306–314.
[36]  Hasegawa M, Kishino H, Yano T (1985) Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol 22: 160–174.
[37]  Amrine-Madsen H, Scally M, Westerman M, Stanhope MJ, Krajewski C, et al. (2003) Nuclear gene sequences provide evidence for the monophyly of australidelphian marsupials. Mol Phylogenet Evol 28: 186–196.
[38]  Aris-Brosou S, Bielawski JP (2006) Large-scale analyses of synonymous substitution rates can be sensitive to assumptions about the process of mutation. Gene 378: 58–64.
[39]  Aris-Brosou S (2006) Identifying sites under positive selection with uncertain parameter estimates. Genome 49: 767–776.
[40]  Sanderson MJ (2003) r8s: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock. Bioinformatics 19: 301–302.
[41]  Seiffert ER, Simons EL, Attia Y (2003) Fossil evidence for an ancient divergence of lorises and galagos. Nature 422: 421–424.
[42]  Yang Z, Wong WS, Nielsen R (2005) Bayes empirical Bayes inference of amino acid sites under positive selection. Mol Biol Evol 22: 1107–1118.


comments powered by Disqus

Contact Us


微信:OALib Journal