Simulation of genome-wide evolution under heterogeneous substitution models and complex multispecies coalescent histories

Molecular Biology and Evolution

Volumn 31, Issue 5, 2014, Pages 1295-1301

  Arenas, Miguel ^a   Posada, David ^b  

^a CSIC   (Spain)

^b UNIVERSITY OF VIGO   (Spain)

Author keywords

Heterogeneous substitution models; Molecular adaptation; Molecular evolution; Multispecies coalescent

Indexed keywords

ARTICLE; CODON; GENETIC RECOMBINATION; GENETIC VARIABILITY; GENOME; MODEL; MOLECULAR EVOLUTION; PHYLOGENY; POPULATION MIGRATION; SIMULATION;

HETEROGENEOUS SUBSTITUTION MODELS; MOLECULAR ADAPTATION; MOLECULAR EVOLUTION; MULTISPECIES COALESCENT;

CODON; COMPUTER SIMULATION; EVOLUTION, MOLECULAR; GENOME; MODELS, GENETIC; SEQUENCE ALIGNMENT; SOFTWARE;

EID: 84899584297     PISSN: 07374038     EISSN: 15371719     Source Type: Journal    
DOI: 10.1093/molbev/msu078     Document Type: Article

References (53)

1. Abascal F, Zardoya R, Posada D. 2005. ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21:2104-2105.
2. Anisimova M, Bielawski JP, Yang Z. 2001. Accuracy and power of the likelihood ratio test in detecting adaptive molecular evolution. Mol Biol Evol. 18:1585-1592.
3. Arbiza L, Patricio M, Dopazo H, Posada D. 2011. Genome-wide heterogeneity of nucleotide substitution model fit. Genome Biol Evol. 3: 896-908.
4. Arenas M. 2012. Simulation of molecular data under diverse evolutionary scenarios. PLoS Comput Biol. 8:e1002495.
5. Arenas M, Dos Santos HG, Posada D, Bastolla U. 2013. Protein evolution along phylogenetic histories under structurally constrained substitution models. Bioinformatics 29:3020-3028.
6. Arenas M, Posada D. 2007. Recodon: coalescent simulation of coding DNA sequences with recombination, migration and demography. BMC Bioinformatics 8:458.
7. Arenas M, Posada D. 2010. Coalescent simulation of intracodon recombination. Genetics 184:429-437.
8. Beaumont MA. 2010. Approximate Bayesian computation in evolution and ecology. Annu Rev Ecol Evol Syst. 41:379-405.
9. Beiko RG, Charlebois RL. 2007. A simulation test bed for hypotheses of genome evolution. Bioinformatics 23:825-831.
10. Bruno WJ. 1996. Modeling residue usage in aligned protein sequences via maximum likelihood. Mol Biol Evol. 13:1368-1374.
11. Carvajal-Rodriguez A. 2008. GENOMEPOP: a program to simulate genomes in populations. BMC Bioinformatics 9:223.
12. Carvajal-Rodriguez A, Crandall KA, Posada D. 2006. Recombination estimation under complex evolutionary models with the coalescent composite-likelihood method. Mol Biol Evol. 23:817-827.
13. Dalquen DA, Anisimova M, Gonnet GH, Dessimoz C. 2012. ALF-a simulation framework for genome evolution. Mol Biol Evol. 29: 1115-1123.
14. Drummond AJ, Nicholls GK, Rodrigo AG, Solomon W. 2002. Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data. Genetics 161: 1307-1320.
15. Excoffier L, Foll M. 2011. fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios. Bioinformatics 27:1332-1334.
16. Excoffier L, Novembre J, Schneider S. 2000. SIMCOAL: a general coalescent program for the simulation of molecular data in interconnected populations with arbitrary demography. J Hered. 91:506-509.
17. Fletcher W, Yang Z. 2009. INDELible: a flexible simulator of biological sequence evolution. Mol Biol Evol. 26:1879-1888.
18. Gharib WH, Robinson-Rechavi M. 2013. The branch-site test of positive selection is surprisingly robust but lacks power under synonymous substitution saturation and variation in GC. Mol Biol Evol. 30: 1675-1686.
19. Gibbs RA, Rogers J, Katze MG, Bumgarner R,Weinstock GM, Mardis ER, Remington KA, Strausberg RL, Venter JC, Wilson RK, et al. 2007. Evolutionary and biomedical insights from the rhesus macaque genome. Science 316:222-234.
20. Goldman N, Thorne JL, Jones DT. 1998. Assessing the impact of secondary structure and solvent accessibility on protein evolution. Genetics 149:445-458.
21. Guindon S, Gascuel O. 2003. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 52: 696-704.
22. Halpern AL, Bruno WJ. 1998. Evolutionary distances for protein-coding sequences: modeling site-specific residue frequencies. Mol Biol Evol. 15:910-917.
23. Hoban S, Bertorelle G, Gaggiotti OE. 2012. Computer simulations: tools for population and evolutionary genetics. Nat Rev Genet. 13: 110-122.
24. Holder MT, Zwickl DJ, Dessimoz C. 2008. Evaluating the robustness of phylogenetic methods to among-site variability in substitution processes. Philos Trans R Soc Lond B Biol Sci. 363:4013-4021.
25. Hudson RR. 1998. Island models and the coalescent process. Mol Ecol. 7: 413-418.
26. Hudson RR. 2002. Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics 18:337-338.
27. Hudson RR, Kaplan NL. 1988. The coalescent process in models with selection and recombination. Genetics 120:831-840.
28. Kimura M, Weiss GH. 1964. The stepping stone model of population structure and the decrease of genetic correlation with distance. Genetics 49:561-576.
29. Kjeldsen KU, Bataillon T, Pinel N, De Mita S, Lund MB, Panitz F, Bendixen C, Stahl DA, Schramm A. 2012. Purifying selection and molecular adaptation in the genome of Verminephrobacter, the heritable symbiotic bacteria of earthworms. Genome Biol Evol. 4: 307-315.
30. Korber B. 2000. HIV signature and sequence variation analysis. In: Rodrigo AG, Learn GH, editors. Computational analysis of HIV molecular sequences. Dordrecht (The Netherlands): Kluwer Academic Publishers. p. 55-72.
31. Kosakovsky Pond SL, Frost SD, Muse SV. 2005. HYPHY: hypothesis testing using phylogenies. Bioinformatics 21:676-679.
32. Kosiol C, Holmes I, Goldman N. 2007. An empirical codon model for protein sequence evolution. Mol Biol Evol. 24:1464-1479.
33. Lartillot N, Philippe H. 2004. A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process. Mol Biol Evol. 21:1095-1109.
34. Lemmon AR, Moriarty EC. 2004. The importance of proper model assumption in bayesian phylogenetics. Syst Biol. 53:265-277.
35. Liberles DA, Teichmann SA, Bahar I, Bastolla U, Bloom J, Bornberg-Bauer E, Colwell LJ, de Koning AP, Dokholyan NV, Echave J, et al. 2012. The interface of protein structure, protein biophysics, and molecular evolution. Protein Sci. 21:769-785.
36. Lio P, Goldman N. 1999. Using protein structural information in evolutionary inference: transmembrane proteins. Mol Biol Evol. 16: 1696-1710.
37. Lopes JS, Arenas M, Posada D, Beaumont MA. 2014. Coestimation of Recombination, Substitution and Molecular Adaptation rates by approximate Bayesian computation. Heredity 112:255-264.
38. Metzger KJ, Thomas MA. 2010. Evidence of positive selection at codon sites localized in extracellular domains of mammalian CC motif chemokine receptor proteins. BMC Evol Biol. 10:139.
39. Muse SV, Gaut BS. 1994. A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome. Mol Biol Evol. 11: 715-724.
40. Oleksyk TK, Smith MW, O'Brien SJ. 2010. Genome-wide scans for footprints of natural selection. Philos Trans R Soc Lond B Biol Sci. 365: 185-205.
41. Pagel M, Meade A. 2004. A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data. Syst Biol. 53:571-581.
42. Posada D. 2008. jModelTest: phylogenetic model averaging. Mol Biol Evol. 25:1253-1256.
43. Schneider A, Cannarozzi GM, Gonnet GH. 2005. Empirical codon substitution matrix. BMC Bioinformatics 6:134.
44. Smith LM, McWhorter AR, Shellam GR, Redwood AJ. 2013. The genome of murine cytomegalovirus is shaped by purifying selection and extensive recombination. Virology 435:258-268.
45. Tamura K. 1992. Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G+C content biases. Mol Biol Evol. 9:678-687.
46. Tavaré S. 1986. Some probabilistic and statistical problems in the analysis of DNA sequences. In: Miura RM, editor. Some mathematical questions in biology-DNA sequence analysis. Providence (RI): Amer Math Soc. p. 57-86.
47. Varadarajan A, Bradley RK, Holmes IH. 2008. Tools for simulating evolution of aligned genomic regions with integrated parameter estimation. Genome Biol. 9:R147.
48. Wiuf C, Posada D. 2003. A coalescent model of recombination hotspots. Genetics 164:407-417.
49. Wright S. 1931. Evolution inMendelian populations. Genetics 16:97-159.
50. Yang Z. 1994. Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. J Mol Evol. 39:306-314.
51. Yang Z. 2007. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 24:1586-1591.
52. Yang Z, Nielsen R. 2000. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models.Mol Biol Evol. 17:32-43.
53. Yang Z, Nielsen R, Goldman N, Pedersen A-MK. 2000. Codon-substitution models for heterogeneous selection pressure at amino acid sites. Genetics 155:431-449.