Molecular Evolution and PhylogeneticsDuring the last ten years, remarkable progress has occurred in the study of molecular evolution. Among the most important factors that are responsible for this progress are the development of new statistical methods and advances in computational technology. In particular, phylogenetic analysis of DNA or protein sequences has become a powerful tool for studying molecular evolution. Along with this developing technology, the application of the new statistical and computational methods has become more complicated and there is no comprehensive volume that treats these methods in depth. Molecular Evolution and Phylogenetics fills this gap and present various statistical methods that are easily accessible to general biologists as well as biochemists, bioinformatists and graduate students. The text covers measurement of sequence divergence, construction of phylogenetic trees, statistical tests for detection of positive Darwinian selection, inference of ancestral amino acid sequences, construction of linearized trees, and analysis of allele frequency data. Emphasis is given to practical methods of data analysis, and methods can be learned by working through numerical examples using the computer program MEGA2 that is provided. |
Contents
3 | |
17 | |
3 Evolutionary Change of DNA Sequences | 33 |
4 Synonymous and Nonsynonymous Nucleotide Substitutions | 51 |
5 Phylogenetic Trees | 73 |
Distance Methods | 87 |
Maximum Parsimony Methods | 115 |
Maximum Likelihood Methods | 147 |
10 Molecular Clocks and Linearized Trees | 187 |
11 Ancestral Nucleotide and Amino Acid Sequences | 207 |
12 Genetic Polymorphism and Evolution | 231 |
13 Population Trees from Genetic Markers | 265 |
14 Perspectives | 291 |
Appendices | 297 |
301 | |
329 | |
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Common terms and phrases
algorithm allele frequencies amino acid sequences amino acid substitution assumption bootstrap test branch length estimates chimpanzees cleotide codon usage bias computer simulation consensus tree consider constructed convergent evolution correct topology data set distance measures DNA sequences Equation evolution evolutionary example expected number Figure Fºr gamma distance genetic genome given heterozygosity human i-th inferred interior branch intron Kimura model large number lineages loci locus matrix mitochondrial ML method model tree molecular clock MP tree mutation NJ tree node nonsynonymous nucleotide or amino nucleotide sequences nucleotide substitution null hypothesis number of nucleotide number of sequences number of substitutions numbers of synonymous onymous opsins Orangutan pair parameters parsimony phylogenetic tree polymorphism population protein quences realized tree Rzhetsky sequence data species subpopulations substitution matrix substitution model synonymous substitutions taxa taxon tion topology total number tree length tree obtained tree topology tree-building methods true tree UPGMA variance