Skip to main content
SpringerLink
Log in

Phylogenetic Reconstruction Methods: An Overview

  • Protocol
  • First Online:
Molecular Plant Taxonomy

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1115))

Abstract

Initially designed to infer evolutionary relationships based on morphological and physiological characters, phylogenetic reconstruction methods have greatly benefited from recent developments in molecular biology and sequencing technologies with a number of powerful methods having been developed specifically to infer phylogenies from macromolecular data. This chapter, while presenting an overview of basic concepts and methods used in phylogenetic reconstruction, is primarily intended as a simplified step-by-step guide to the construction of phylogenetic trees from nucleotide sequences using fairly up-to-date maximum likelihood methods implemented in freely available computer programs. While the analysis of chloroplast sequences from various Vanilla species is used as an illustrative example, the techniques covered here are relevant to the comparative analysis of homologous sequences datasets sampled from any group of organisms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Darlu P, Tassy P (1993) La reconstruction phylogénétique. Concepts et Méthodes. Masson

    Google Scholar 

  2. Groves C (1986) Systematics of the great apes. In: Swindler DR, Erwin J (eds) Comparative primate biology: systematics, evolution and anatomy, vol 1. Liss AR, New York, pp 187–217

    Google Scholar 

  3. Hemsley AR, Poole I (2004) The evolution of plant physiology. From whole plants to ecosystems. Elsevier Academic Press, Amsterdam

    Google Scholar 

  4. Caputo P (1997) DNA and phylogeny in plants: history and new perspectives. Lagascalia 19:331–344

    Google Scholar 

  5. Zuckerkandl E, Pauling L (1965) Molecules as documents of evolutionary history. J Theor Biol 8:357–366

    Article  CAS  PubMed  Google Scholar 

  6. Nei M, Kumar S (2000) Molecular evolution and phylogenetics. Oxford University Press, New York

    Google Scholar 

  7. Van de Peer Y (2009) Phylogeny inference based on distance methods. In: Salemmi M, Vandamme AM (eds) The phylogenetic handbook, a practical approach to DNA and protein phylogeny. Cambridge University Press, New York, pp 101–135

    Google Scholar 

  8. Michener CD, Sokal RR (1956) A quantitative approach to a problem in classification. Evolution 11:130–162

    Article  Google Scholar 

  9. Fitch WM, Margoliash E (1967) Construction of phylogenetic trees. Science 155:279–284

    Article  CAS  PubMed  Google Scholar 

  10. Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425

    CAS  PubMed  Google Scholar 

  11. Gascuel O (1997) BIONJ: an improved version of the NJ algorithm based on a simple model of sequence data. Mol Biol Evol 14: 685–695

    Article  CAS  PubMed  Google Scholar 

  12. Steel MA, Hendy MD, Penny D (1988) Loss of information in genetic distances. Nature 336:118

    Article  CAS  PubMed  Google Scholar 

  13. Felsenstein J (2004) Inferring phylogenies. Sinauer Associates, Sunderland

    Google Scholar 

  14. Sober E (1988) Reconstructing the past: parsimony, evolution, and inference. MIT Press, Cambridge

    Google Scholar 

  15. Edwards AWF, Cavalli-Sforza LL (1964) Reconstruction of evolutionary trees. In: Heywood VH, McNeill J (eds) Phenetic and phylogenetic classification: a symposium. Systematics Association, London, pp 67–76

    Google Scholar 

  16. Cavalli-Sforza LL, Edwards AWF (1967) Phylogenetic analysis: models and estimation procedures. Evolution 32:550–570

    Article  Google Scholar 

  17. Felsenstein J (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 17:368–376

    Article  CAS  PubMed  Google Scholar 

  18. Farris JS (1970) Methods for computing Wagner trees. Syst Zool 19:83–92

    Article  Google Scholar 

  19. Fitch WM (1971) Towards defining the course of evolution: minimum change for a specific tree topology. Syst Zool 20:406–416

    Article  Google Scholar 

  20. Kluge AG, Farris JS (1969) Quantitative phyletics and the evolution of anurans. Syst Zool 18:1–32

    Article  Google Scholar 

  21. Harrison CJ, Langdale JA (2006) A step by step guide to phylogeny reconstruction. Plant J 45:561–572

    Article  CAS  PubMed  Google Scholar 

  22. Aldrich J (1997) R. A. Fisher and the making of maximum likelihood 1912–1922. Statist Sci 12:162–176

    Article  Google Scholar 

  23. Felsenstein J (1973) Maximum-likelihood estimation of evolutionary trees from continuous characters. Am J Hum Genet 25:471–492

    CAS  PubMed Central  PubMed  Google Scholar 

  24. Schmidt HA, von Haeseler A (2009) Phylogenetic inference using maximum likelihood methods. In: Salemmi M, Vandamme AM (eds) The phylogenetic handbook, a practical approach to DNA and protein phylogeny. Cambridge University Press, New York, pp 181–209

    Chapter  Google Scholar 

  25. Hendy MD, Penny D (1982) Branch and bound algorithms to determine minimal evolutionary trees. Math Biosci 59:277–290

    Article  Google Scholar 

  26. Swofford DL, Sullivan J (2003) Phylogeny inference based on parsimony and other methods using Paup*. In: Salemmi M, Vandamme AM (eds) The phylogenetic handbook, a practical approach to DNA and protein phylogeny. Cambridge University Press, New York, pp 267–312

    Google Scholar 

  27. Swofford DL, Olsen GJ (1990) Phylogeny reconstruction. In: Hillis DM, Moritz C, Mable BK (eds) Molecular systematics. Sinauer Associates, Sunderland, pp 411–501

    Google Scholar 

  28. Swofford DL et al (1996) Phylogenetic inference. In: Hillis DM, Moritz C, Mable BK (eds) Molecular systematics. Sinauer Associates, Sunderland, pp 407–514

    Google Scholar 

  29. Ronquist F, van der Mark P, Huelsenbeck JP (2009) Bayesian phylogenetic analysis using MrBayes. In: Salemmi M, Vandamme AM (eds) The phylogenetic handbook, a practical approach to DNA and protein phylogeny. Cambridge University Press, New York, pp 210–266

    Chapter  Google Scholar 

  30. Tamura K et al (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28:2731–2739

    Article  CAS  PubMed  Google Scholar 

  31. Posada D (2008) jModelTest: phylogenetic model averaging. Mol Biol Evol 25: 1253–1256

    Article  CAS  PubMed  Google Scholar 

  32. Guindon S et al (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59:307–321

    Article  CAS  PubMed  Google Scholar 

  33. Morariu V et al (2008) Automatic online tuning for fast Gaussian summation. Advances in Neural Information Processing Systems (NIPS) 1–8

    Google Scholar 

  34. Hall BG (2007) Phylogenetic trees made easy: a how-to manual, 3rd edn. Sinauer Associates, Sunderland

    Google Scholar 

  35. Benson DA et al (1994) GenBank. Nucleic Acids Res 22:3441–3444

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  36. Cochrane G et al (2009) Petabyte-scale innovations at the European Nucleotide Archive. Nucleic Acids Res 37:D19–D25

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  37. Tateno Y et al (2002) DNA Data Bank of Japan (DDBJ) for genome scale research in life science. Nucleic Acids Res 30:27–30

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. Bouetard A et al (2010) Evidence of transoceanic dispersion of the genus Vanilla based on plastid DNA phylogenetic analysis. Mol Phyl Evol 55:621–630

    Article  CAS  Google Scholar 

  39. Altschul SF et al (1990) Basic local alignment tool. J Mol Biol 215:403–410

    CAS  PubMed  Google Scholar 

  40. Maddison WP, Donoghue MJ, Maddison DR (1984) Outgroup analysis and parsimony. Syst Zool 33:83–103

    Article  Google Scholar 

  41. Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  43. Posada D, Crandall KA (1998) Model test: testing the model of substitution. Bioinformatics 14:817–818

    Article  CAS  PubMed  Google Scholar 

  44. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723

    Article  Google Scholar 

  45. Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464

    Article  Google Scholar 

  46. Minin V et al (2003) Performance-based selection of likelihood models for phylogeny estimation. Syst Biol 52:674–683

    Article  PubMed  Google Scholar 

  47. Luo A et al (2010) Performance of criteria for selecting evolutionary models in phylogenetics: a comprehensive study based on simulated datasets. BMC Evol Biol 10:242

    Article  PubMed Central  PubMed  Google Scholar 

  48. Ripplinger J, Sullivan J (2008) Does choice in model selection affect maximum likelihood analysis? Syst Biol 57:76–85

    Article  PubMed  Google Scholar 

  49. Jukes TH, Cantor CR (1969) Evolution of protein molecules. In: Munro HN (ed) Mammalian protein metabolism. Academic, New York, pp 21–132

    Chapter  Google Scholar 

  50. Tavaré S (1986) Some probabilistic and statistical problems in the analysis of DNA sequences. Lect Math Life Sci (Am Math Soc) 17:57–86

    Google Scholar 

  51. 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

    Article  CAS  PubMed  Google Scholar 

  52. Felsenstein J (1985) Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39:783–791

    Article  Google Scholar 

  53. Anisimova M, Gascuel O (2006) Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst Biol 55:539–552

    Article  PubMed  Google Scholar 

  54. Anisimova M et al (2011) Survey of branch support methods demonstrates accuracy, power, and robustness of fast likelihood-based approximation schemes. Syst Biol 60:685–699

    Article  PubMed  Google Scholar 

  55. Darriba D et al (2011) ProtTest3: fast selection of best-fit models of protein evolution. Bioinformatics 27:1164–1165

    Article  CAS  PubMed  Google Scholar 

  56. Ruths D, Nakhleh L (2005) Recombination and phylogeny: effects and detection. Int J Bioinform Res Appl 1:202–212

    Article  CAS  PubMed  Google Scholar 

  57. Posada D, Crandall KA (2002) The effect of recombination on the accuracy of phylogeny estimation. J Mol Evol 54:396–402

    CAS  PubMed  Google Scholar 

  58. Ronquist F, Huelsenbeck JP (2003) MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19:1572–1574

    Article  CAS  PubMed  Google Scholar 

  59. Drummond AJ et al (2012) Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol 29:1969–1973. doi:10.1093/molbev/mss075

    Article  CAS  PubMed  Google Scholar 

  60. Rannala B, Yang Z (1996) Probability distribution of molecular evolutionary trees: a new method of phylogenetic inference. J Mol Evol 43:304–311

    Article  CAS  PubMed  Google Scholar 

  61. Mau B, Newton M, Larget B (1999) Bayesian phylogenetic inference via Markov chain Monte Carlo methods. Biometrics 55:1–12

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

ADB is supported by the Conseil Général de La Réunion and CIRAD. DPM is supported by the Wellcome Trust. PL is supported by CIRAD and Conseil Régional de La Réunion and European Union (FEDER). The authors wish to thank Dr. Jean-Michel Lett for his helpful comments.

Author information

Authors and Affiliations

  1. Pôle de Protection des Plantes, CIRAD, UMR PVBMT, Université de la Réunion, Saint-Pierre, France

    Alexandre De Bruyn & Pierre Lefeuvre

  2. Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa

    Darren P. Martin

Authors
  1. Alexandre De Bruyn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Darren P. Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pierre Lefeuvre
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. UMR C53 PVBMT Université de la Réunion-Cirad, Université de la Réunion, Ile de la Réunion, France

    Pascale Besse

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer New York

About this protocol

Cite this protocol

De Bruyn, A., Martin, D.P., Lefeuvre, P. (2014). Phylogenetic Reconstruction Methods: An Overview. In: Besse, P. (eds) Molecular Plant Taxonomy. Methods in Molecular Biology, vol 1115. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-767-9_13

Download citation

  • DOI: https://doi.org/10.1007/978-1-62703-767-9_13

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-766-2

  • Online ISBN: 978-1-62703-767-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation