MAFFT: Iterative Refinement and Additional Methods

  • Kazutaka Katoh
  • Daron M. Standley
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1079)

Abstract

This chapter outlines several methods implemented in the MAFFT package. MAFFT is a popular multiple sequence alignment (MSA) program with various options for the progressive method, the iterative refinement method and other methods. We first outline basic usage of MAFFT and then describe recent practical extensions, such as dot plot and adjustment of direction in DNA alignment. We also refer to MUSCLE, another high-performance MSA program.

Key words

Multiple sequence alignment Iterative refinement Fast Fourier transform Metagenome Protein structure 

References

  1. 1.
    Katoh K, Misawa K, Kuma K, Miyata T (2002) MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res 30:3059–3066PubMedCrossRefGoogle Scholar
  2. 2.
    Nuin PA, Wang Z, Tillier ER (2006) The accuracy of several multiple sequence alignment programs for proteins. BMC Bioinformatics 7:471PubMedCrossRefGoogle Scholar
  3. 3.
    Dessimoz C, Gil M (2010) Phylogenetic assessment of alignments reveals neglected tree signal in gaps. Genome Biol 11:R37PubMedCrossRefGoogle Scholar
  4. 4.
    Letsch HO, Kuck P, Stocsits RR, Misof B (2010) The impact of rRNA secondary structure consideration in alignment and tree reconstruction: simulated data and a case study on the phylogeny of hexapods. Mol Biol Evol 27:2507–2521PubMedCrossRefGoogle Scholar
  5. 5.
    Sahraeian SM, Yoon BJ (2011) PicXAA-R: efficient structural alignment of multiple RNA sequences using a greedy approach. BMC Bioinformatics 12(Suppl 1):S38PubMedCrossRefGoogle Scholar
  6. 6.
    Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Soding J, Thompson JD, Higgins DG (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 7:539PubMedCrossRefGoogle Scholar
  7. 7.
    Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797PubMedCrossRefGoogle Scholar
  8. 8.
    Edgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113PubMedCrossRefGoogle Scholar
  9. 9.
    Feng DF, Doolittle RF (1987) Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J Mol Evol 25:351–360PubMedCrossRefGoogle Scholar
  10. 10.
    Higgins DG, Sharp PM (1988) CLUSTAL: a package for performing multiple sequence alignment on a microcomputer. Gene 73:237–244PubMedCrossRefGoogle Scholar
  11. 11.
    Wilbur WJ, Lipman DJ (1983) Rapid similarity searches of nucleic acid and protein data banks. Proc Natl Acad Sci USA 80:726–730PubMedCrossRefGoogle Scholar
  12. 12.
    Loytynoja A, Goldman N (2008) Phylogeny-aware gap placement prevents errors in sequence alignment and evolutionary analysis. Science 320:1632–1635PubMedCrossRefGoogle Scholar
  13. 13.
    Lassmann T, Sonnhammer EL (2005) Kalign—an accurate and fast multiple sequence alignment algorithm. BMC Bioinformatics 6:298PubMedCrossRefGoogle Scholar
  14. 14.
    Barton GJ, Sternberg MJ (1987) A strategy for the rapid multiple alignment of protein sequences. Confidence levels from tertiary structure comparisons. J Mol Biol 198:327–337Google Scholar
  15. 15.
    Berger MP, Munson PJ (1991) A novel randomized iterative strategy for aligning multiple protein sequences. Comput Appl Biosci 7:479–484PubMedGoogle Scholar
  16. 16.
    Gotoh O (1993) Optimal alignment between groups of sequences and its application to multiple sequence alignment. Comput Appl Biosci 9:361–370PubMedGoogle Scholar
  17. 17.
    Gotoh O (1995) A weighting system and algorithm for aligning many phylogenetically related sequences. Comput Appl Biosci 11:543–551PubMedGoogle Scholar
  18. 18.
    Ishikawa M, Toya T, Hoshida M, Nitta K, Ogiwara A, Kanehisa M (1993) Multiple sequence alignment by parallel simulated annealing. Comput Appl Biosci 9:267–273PubMedGoogle Scholar
  19. 19.
    Notredame C, Higgins DG (1996) Saga: sequence alignment by genetic algorithm. Nucleic Acids Res 24:1515–1524PubMedCrossRefGoogle Scholar
  20. 20.
    Gotoh O (1996) Significant improvement in accuracy of multiple protein sequence alignments by iterative refinement as assessed by reference to structural alignments. J Mol Biol 264:823–838PubMedCrossRefGoogle Scholar
  21. 21.
    Hirosawa M, Totoki Y, Hoshida M, Ishikawa M (1995) Comprehensive study on iterative algorithms of multiple sequence alignment. Comput Appl Biosci 11:13–18PubMedGoogle Scholar
  22. 22.
    Vingron M, Argos P (1989) A fast and sensitive multiple sequence alignment algorithm. Comput Appl Biosci 5:115–121PubMedGoogle Scholar
  23. 23.
    Gotoh O (1990) Consistency of optimal sequence alignments. Bull Math Biol 52:509–525PubMedGoogle Scholar
  24. 24.
    Notredame C, Holm L, Higgins DG (1998) COFFEE: an objective function for multiple sequence alignments. Bioinformatics 14:407–422PubMedCrossRefGoogle Scholar
  25. 25.
    Notredame C, Higgins DG, Heringa J (2000) T-Coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 302:205–217PubMedCrossRefGoogle Scholar
  26. 26.
    Do CB, Mahabhashyam MS, Brudno M, Batzoglou S (2005) ProbCons: probabilistic consistency-based multiple sequence alignment. Genome Res 15:330–340PubMedCrossRefGoogle Scholar
  27. 27.
    Roshan U, Livesay DR (2006) Probalign: multiple sequence alignment using partition function posterior probabilities. Bioinformatics 22:2715–2721PubMedCrossRefGoogle Scholar
  28. 28.
    Pei J, Grishin NV (2007) PROMALS: towards accurate multiple sequence alignments of distantly related proteins. Bioinformatics 23:802–808PubMedCrossRefGoogle Scholar
  29. 29.
    Liu Y, Schmidt B, Maskell DL (2010) MSAProbs: multiple sequence alignment based on pair hidden markov models and partition function posterior probabilities. Bioinformatics 26:1958–1964PubMedCrossRefGoogle Scholar
  30. 30.
    Katoh K, Toh H (2008) Recent developments in the MAFFT multiple sequence alignment program. Brief Bioinform 9:286–298PubMedCrossRefGoogle Scholar
  31. 31.
    Katoh K, Toh H (2008) Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework. BMC Bioinformatics 9:212PubMedCrossRefGoogle Scholar
  32. 32.
    McCaskill JS (1990) The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 29:1105–1119PubMedCrossRefGoogle Scholar
  33. 33.
    Tabei Y, Tsuda K, Kin T, Asai K (2006) SCARNA: fast and accurate structural alignment of rna sequences by matching fixed-length stem fragments. Bioinformatics 22:1723–1729PubMedCrossRefGoogle Scholar
  34. 34.
    Hofacker IL, Fekete M, Stadler PF (2002) Secondary structure prediction for aligned RNA sequences. J Mol Biol 319:1059–1066PubMedCrossRefGoogle Scholar
  35. 35.
    Tabei Y, Kiryu H, Kin T, Asai K (2008) A fast structural multiple alignment method for long RNA sequences. BMC Bioinformatics 9:33PubMedCrossRefGoogle Scholar
  36. 36.
    Hamada M, Sato K, Kiryu H, Mituyama T, Asai K (2009) CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score. Bioinformatics 25:3236–3243PubMedCrossRefGoogle Scholar
  37. 37.
    Wilm A, Higgins DG, Notredame C (2008) R-Coffee: a method for multiple alignment of non-coding RNA. Nucleic Acids Res 36:e52PubMedCrossRefGoogle Scholar
  38. 38.
    Katoh K, Frith MC (2012) Adding unaligned sequences into an existing alignment using MAFFT and LAST. Bioinformatics 28:3144–3146Google Scholar
  39. 39.
    Katoh K, Toh H (2007) PartTree: an algorithm to build an approximate tree from a large number of unaligned sequences. Bioinformatics 23:372–374PubMedCrossRefGoogle Scholar
  40. 40.
    Blackshields G, Sievers F, Shi W, Wilm A, Higgins DG (2010) Sequence embedding for fast construction of guide trees for multiple sequence alignment. Algorithms Mol Biol 5:21PubMedCrossRefGoogle Scholar
  41. 41.
    Kiełbasa SM, Wan R, Sato K, Horton P, Frith MC (2011) Adaptive seeds tame genomic sequence comparison. Genome Res 21:487–493PubMedCrossRefGoogle Scholar
  42. 42.
    Katoh K, Toh H (2010) Parallelization of the MAFFT multiple sequence alignment program. Bioinformatics 26:1899–1900PubMedCrossRefGoogle Scholar
  43. 43.
    Punta M, Coggill PC, Eberhardt RY, Mistry J, Tate J, Boursnell C, Pang N, Forslund K, Ceric G, Clements J, Heger A, Holm L, Sonnhammer EL, Eddy SR, Bateman A, Finn RD (2012) The Pfam protein families database. Nucleic Acids Res 40:D290–D301PubMedCrossRefGoogle Scholar
  44. 44.
    Sigrist CJ, Cerutti L, deCastro E, Langendijk-Genevaux PS, Bulliard V, Bairoch A, Hulo N (2010) PROSITE, a protein domain database for functional characterization and annotation. Nucleic Acids Res 38:D161–D166PubMedCrossRefGoogle Scholar
  45. 45.
    Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM (2009) The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 37:D141–D145PubMedCrossRefGoogle Scholar
  46. 46.
    Berger SA, Stamatakis A (2011) Aligning short reads to reference alignments and trees. Bioinformatics 27:2068–2075PubMedCrossRefGoogle Scholar
  47. 47.
    Sun H, Buhler JD (2012) PhyLAT: a phylogenetic local alignment tool. Bioinformatics 28:1336–1344PubMedCrossRefGoogle Scholar
  48. 48.
    Löytynoja A, Vilella AJ, Goldman N (2012) Accurate extension of multiple sequence alignments using a phylogeny-aware graph algorithm. Bioinformatics 28:1684–1691PubMedCrossRefGoogle Scholar
  49. 49.
    Mirarab S, Nguyen N, Warnow T (2012) SEPP: SATé-Enabled phylogenetic placement. Pac Symp Biocomput 17:247–258Google Scholar
  50. 50.
    Cannone JJ, Subramanian S, Schnare MN, Collett JR, D’Souza LM, Du Y, Feng B, Lin N, Madabusi LV, Muller KM, Pande N, Shang Z, Yu N, Gutell RR (2002) The comparative RNA web (CRW) site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs. BMC Bioinformatics 3:2PubMedCrossRefGoogle Scholar
  51. 51.
    O’Sullivan O, Suhre K, Abergel C, Higgins DG, Notredame C (2004) 3DCoffee: combining protein sequences and structures within multiple sequence alignments. J Mol Biol 340:385–395PubMedCrossRefGoogle Scholar
  52. 52.
    Pei J, Kim BH, Grishin NV (2008) PROMALS3D: a tool for multiple protein sequence and structure alignments. Nucleic Acids Res 36:2295–2300PubMedCrossRefGoogle Scholar
  53. 53.
    Standley DM, Toh H, Nakamura H (2004) Detecting local structural similarity in proteins by maximizing number of equivalent residues. Proteins 57:381–391PubMedCrossRefGoogle Scholar
  54. 54.
    Taylor WR, Orengo CA (1989) Protein structure alignment. J Mol Biol 208:1–22PubMedCrossRefGoogle Scholar
  55. 55.
    Orengo CA, Taylor WR (1993) A local alignment method for protein structure motifs. J Mol Biol 233:488–497PubMedCrossRefGoogle Scholar
  56. 56.
    Toh H (1997) Introduction of a distance cut-off into structural alignment by the double dynamic programming algorithm. Comput Appl Biosci 13:387–396PubMedGoogle Scholar
  57. 57.
    Katoh K, Asimenos G, Toh H (2009) Multiple alignment of DNA sequences with MAFFT. Methods Mol Biol 537:39–64PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2014

Authors and Affiliations

  • Kazutaka Katoh
    • 1
    • 2
  • Daron M. Standley
    • 1
  1. 1.Immunology Frontier Research CenterOsaka UniversitySuitaJapan
  2. 2.Computational Biology Research CenterThe National Institute of Advanced Industrial Science and Technology (AIST)TokyoJapan

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