A DNA sequence evolution analysis generalized by simulation and the Markov chain Monte Carlo method implicates strand slippage in a majority of insertions and deletions

Journal of Molecular Evolution

Volumn 55, Issue 6, 2002, Pages 706-717

  Nishizawa, Manami ^a   Nishizawa, Kazuhisa ^a  

^a TEIKYO UNIVERSITY SCHOOL OF MEDICINE   (Japan)

Author keywords

Markov chain Monte Carlo; Microsatellite; Replication slippage; Triplet repeat

Indexed keywords

DNA;

ARTICLE; DNA REPLICATION; DNA SEQUENCE; MOLECULAR EVOLUTION; MONTE CARLO METHOD; NUCLEOTIDE REPEAT; NUCLEOTIDE SEQUENCE; PROBABILITY;

MURIDAE;

BASE SEQUENCE; DNA; EVOLUTION, MOLECULAR; MONTE CARLO METHOD; PROBABILITY; SEQUENCE ANALYSIS, DNA;

EID: 0036893298     PISSN: 00222844     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00239-002-2366-5     Document Type: Article

References (33)

1. Allison L, Wallace CS (1994) The posterior probability distribution of alignments and its application to parameter estimation of evolutionary trees and to optimization of multiple alignments. J Mol Evol 39:418-430
2. Bell GI, Jurka J (1997) The length distribution of perfect dimer repetitive DNA is consistent with its evolution by an unbiased single-step mutation process. J Mol Evol 44:414-421
3. Besag JE (1989) A candidate's formula: A curious result in Bayesian prediction. Biometrika 76:183
4. Bishop MJ, Thompson EA (1986) Maximum likelihood alignment of DNA sequences. J Mol Biol 190:159-165
5. Felsenstein J (1981) Evolutionary trees from DNA sequences: A maximum likelihood approach. J Mol Evol 17:368-376
6. Gelman A, Carlin J, Stern H, Rubin D (1995) Bayesian Data Analysis. Chapman and Hall, London
7. Goldstein DB, Pollock DD (1997) Launching microsatellites: A review of mutation processes and methods of phylogenetic interference. J Hered 88:335-342
8. Gotoh O (1982) An improved algorithm for matching biological sequences. J Mol Biol 162:705-708
9. Gu X, Li W-H (1995) The size distribution of insertions and deletions in human and rodent pseudogenes suggests the logarithmic gap penalty for sequence alignment. J Mol Evol 40:464-473
10. Hankock JM (1995) The contribution of slippage-like processes to genome evolution. J Mol Evol 41:1038-1047
11. 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
12. Hastings WK (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57:97-109
13. Kimura M (1980) A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16:111-120
14. Kruglyak S, Durrett R, Schug MD, Aquadro CF (1998) Equilibrium distributions of microsatellite repeat length resulting from a balance between slippage events and point mutations. Proc Natl Acad Sci USA 95:10774-10778
15. Larget B, Simon DL (1999) Markov chain Monte Carlo algorithms for the Baysesian analysis of phylogenetic trees. Mol Biol Evol 16:750-759
16. Li W-H (1997) Molecular Evolution. Sinauer, Sunderland, MA, pp 91-97
17. Needleman SB, Wunsch CD (1970) A general method applicable to the search for similarities in the amino acid sequence of two proteins. J Mol Biol 48:443-453
18. Nishizawa M, Nishizawa K (2000) Amino acid and nucleotide recurrence in aligned sequences: Synonymous substitution patterns in association with global and local base compositions. Nucleic Acids Res 28:3801-3810
19. Nishizawa K, Nishizawa M, Kim KS (1999) Tendency for local repetitiveness in amino acid usages in modern proteins. J Mol Biol 294:937-953
20. Ophir R, Graur D (1997) Patterns and rates of indel evolution in processed pseudogenes from humans and murids. Gene 205:191-202
21. Ophir R, Itoh T, Graur D. Gojobori T (1999) A simple method for estimating the intensity of purifying selection in protein-coding genes. Mol Biol Evol 16:49-53
22. Ponte I, Monsalves C, Cabanas M, Martinez P, Suau P (1996) Sequence simplicity and evolution of the 3′ untranslated region of the histone H10 gene. J Mol Evol 43:125-134
23. Pupko T, Graur D (1999) Evolution of microsatellites in the yeast Saccharomyces cerevisiae: Role of length and number of repeated units. J Mol Evol 48:313-316
24. Raftery AE (1996) Hypothesis Testing and Model Selection. Markov Chain Monte Carlo in Practice. In: WR Gilks, S Richardson, DJ Spieghelhalter (eds) Chapman Hall/CRC, London, pp 163-187
25. Sellers PH (1974) On the theory and computation of evolutionary distances. SIAM J Appl Math 26:787-793
26. Smith TF, Waterman MS (1981) Identification of common molecular subsequences. J Mol Biol 147:195-197
27. Tautz D (1989) Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Res 17:6463-6471
28. Thorne JL, Kishinmo H, Felsenstein J (1991) Inching toward reality: An improved likelihood model of sequence evolution. J Mol Evol 33:114-124
29. Thorne JL, Kishino H, Felsenstein J (1992) An evolutionary model for maximum likelihood alignment of DNA sequences. J Mol Evol 34:3-16
30. 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
31. Yang Z, Rannala B (1997) Bayesian phylogenetic inference using DNA sequences: A Markov chain Monte Carlo method. Mol Biol Evol 14:717-724
32. Yang Z, Roberts D (1995) On the use of nucleic acid sequences to infer early branchings in the tree of life. Mol Biol Evol 12:451-458
33. Zhu Y, Strassmann JE, Queller DC (2000) Insertions, substitutions, and the origin of microsatellites. Genet Res 76:227-236