Journal of Molecular Evolution

, Volume 62, Issue 6, pp 785–792 | Cite as

Relaxed Neighbor Joining: A Fast Distance-Based Phylogenetic Tree Construction Method

Article

Abstract

Our ability to construct very large phylogenetic trees is becoming more important as vast amounts of sequence data are becoming readily available. Neighbor joining (NJ) is a widely used distance-based phylogenetic tree construction method that has historically been considered fast, but it is prohibitively slow for building trees from increasingly large datasets. We developed a fast variant of NJ called relaxed neighbor joining (RNJ) and performed experiments to measure the speed improvement over NJ. Since repeated runs of the RNJ algorithm generate a superset of the trees that repeated NJ runs generate, we also assessed tree quality. RNJ is dramatically faster than NJ, and the quality of resulting trees is very similar for the two algorithms. The results indicate that RNJ is a reasonable alternative to NJ and that it is especially well suited for uses that involve large numbers of taxa or highly repetitive procedures such as bootstrapping.

Keywords

Phylogenetic tree construction Neighbor joining Distance method 

References

  1. Bruno WJ, Socci ND, Halpern AL (2000) Weighted neighbor joining: a likelihood-based approach to distance-based phylogeny reconstruction. Mol Biol Evol 17:189–197PubMedGoogle Scholar
  2. Chase MW, Soltis DE, Olmstead RG, Morgan D, Les DH, Mishler BD, Duvall MR, Price RA, Hills HG, Qiu YL, Kron KA, Rettig JH, Conti E, Palmer JD, Manhart JR, Sytsma KJ, Michaels HJ, Kress WJ, Karol KG, Clark WD, Hédren MH, Gaut BS, Jansen RK, Kim KJ, Wimpee CF, Smith JF, Furnier GR, Strauss SH, Xiang QY, Plunkett GM, Soltis PS, Swensen SM, Williams SE, Gadek PA, Quinn CJ, Equiarte LE, Dolenberg E, Learn Jr GH, Graham SW, Barrett SCH, Dayandan S, Albert VA (1993) Phylogenetics of seed plants: An analysis of nucleotide sequences from the plastid gene rbcL. Ann Mo Bot 80:528–580Google Scholar
  3. Felsenstein J (2004) PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author, Department of Genome Sciences, University of Washington, SeattleGoogle Scholar
  4. Felsenstein J, Churchill GA (1996) A hidden Markov Model approach to variation among sites in rate of evolution. Mol Biol Evol 13:93–104PubMedGoogle Scholar
  5. Gascuel O (1997) BIONJ: an improved version of the NJ algorithm based on a simple model of sequence data. Mol Biol Evol 14:685–695PubMedGoogle Scholar
  6. Howe K, Bateman A, Durbin R (2002) QuickTree: Building huge neighbour-joining trees of protein sequences. Bioinformatics 18:1546–1547PubMedCrossRefGoogle Scholar
  7. Kimura M (1980) A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16:111–120PubMedCrossRefGoogle Scholar
  8. Kishino H, Hasegawa M (1989) Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. J Mol Evol 19:170–179CrossRefGoogle Scholar
  9. Kuhner MK, Felsenstein J (1994) A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates. Mol Biol Evol 11:459–468PubMedGoogle Scholar
  10. Mailund T, Pedersen CNS (2004) QuickJoin—Fast neighbour-joining tree reconstruction. Bioinformatics 20:3261–3262PubMedCrossRefGoogle Scholar
  11. Moret BME, Nakhleh L, Warnow T, Linder CR, Tholse A, Padolina A, Sun J, Timme R (2004) Phylogenetic networks: modeling, reconstructibility, and accuracy. IEEE/ACM Trans Comput Biol Bioinform 1:13–23CrossRefGoogle Scholar
  12. Robinson DF, Foulds LR (1981) Comparison of phylogenetic trees. Math Bioscie 53:131–147CrossRefGoogle Scholar
  13. Saitou N, Imanishi T (1989) Relative efficiencies of the Fitch-Margoliash, maximum-parsimony, maximum-likelihood, minimum-evolution, and neighbor-joining methods of phylogenetic tree construction in obtaining the correct tree. Mol Biol Evol 6:514–525Google Scholar
  14. Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425PubMedGoogle Scholar
  15. Stoye J, Evers D, Meyer F (1998) Rose: generating sequence families. Bioinformatics 14:157–163PubMedCrossRefGoogle Scholar
  16. Studier JA, Keppler KJ (1988) A note on the neighbor-joining algorithm of Saitou and Nei. Mol Biol Evol 5:729–731PubMedGoogle Scholar
  17. 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 22:4673–4680PubMedGoogle Scholar
  18. Waterman MS, Smith TF, Singh M, Beyer WA (1977) Additive evolutionary trees. J Theor Biol 64:199–213PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Department of Biological SciencesUniversity of IdahoMoscowUSA

Personalised recommendations