Codon Evolution: Mechanisms and Models

Hardcover | March 9, 2012

EditorGina M. Cannarozzi, Adrian Schneider

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Codon-based models of evolution are a relatively new addition to the toolkit of computational biologists, and in recent years remarkable progress has been made in this area. The study of evolution at the codon level captures information contained in both amino acid and synonymous DNAsubstitutions. By combining these two types of information, codon analyses are more powerful than those of either amino acid or DNA evolution alone. This is a clear benefit for most evolutionary analyses, including phylogenetic reconstruction, detection of selection, ancestral sequencereconstruction, and alignment of coding DNA. Despite the theoretical advantages of codon based models, their relative complexity delayed their widespread use. Only in recent years, when large-scale sequencing projects produced sufficient genomic data and computational power increased, did theirusage become more common. In Codon Evolution, leading researchers in the field of molecular evolution provide the latest insights from codon-based analyses of genetic sequences. The first part of the book provides comprehensive coverage of the developments of various types of codon substitution models such as parametric andempirical models used in maximum likelihood as well as Bayesian frameworks. Subsequent chapters examine the use of codon models to infer selection and other applications of codon models to biological systems. The second part of the book focuses on codon usage bias. Both the underlying mechanisms aswell as current methods to analyse codon usage bias are presented.

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Codon-based models of evolution are a relatively new addition to the toolkit of computational biologists, and in recent years remarkable progress has been made in this area. The study of evolution at the codon level captures information contained in both amino acid and synonymous DNAsubstitutions. By combining these two types of inform...

Gina Cannarozzi was a Senior Scientific Researcher in the Computer Science Department at the ETH Zurich, Switzerland from 2000-2010 and currently holds the same position in the Biology Department at the University of Bern. She obtained her Ph.D. in Physical Chemistry from the University of California, San Diego in 1995 and has been in...

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Format:HardcoverDimensions:320 pages, 9.69 × 7.44 × 0.01 inPublished:March 9, 2012Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:019960116X

ISBN - 13:9780199601165

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Table of Contents

ForewordPrefacePART I: MODELING CODON EVOLUTION1. Adrian Schneider and Gina M. Cannarozzi: Background2. Maria Anisimova: Parametric Models of Codon Evolution3. Adrian Schneider and Gina M. Cannarozzi: Empirical and Semi-empirical Models of Codon Evolution4. Nicolas Rodrigue and Nicolas Lartillot: Monte Carlo Computational Approaches in Bayesian Codon Substitution Modeling5. Hong Gu, Katherine A. Dunn, and Joseph P. Bielawski: Likelihood Based Clustering (LiBaC) for Codon Models6. Maria Anisimova and David A. Liberles: Detecting and Understanding Natural Selection7. Jeffrey L. Thorne, Nicolas Lartillot, Nicolas Rodrigue, and Sang Chul Choi: Codon Models as a Vehicle for Reconciling Population Genetics with Interspecific Sequence Data8. Gavin A. Huttley and Von Bing Yap: Robust Estimation of Natural Selection Using Parametric Codon Models9. Miguel Arenas and David Posada: Simulation of Coding Sequence Evolution10. Steven A. Benner: Use of Codon Models in Molecular Dating and Functional Analysis11. Belinda S.W. Chang, Jingjing Du, Cameron J. Weadick, Johannes Muller, Constanze Bickelmann, D. David Yu, and James M. Morrow: The Future of Codon Models in Studies of Molecular Function: Ancestral Reconstruction, and Clade Models of Functional Divergence12. Gabriela Aguileta and Tatiana Giraud: Codon Models Applied to the Study of Fungal GenomesPART II: CODON USAGE BIAS13. Alexander Roth, Maria Anisimova, and Gina M. Cannarozzi: Measuring Codon Usage Bias14. Nimrod D. Rubinstein and Tal Pupko: Detection and Analysis of Conservation at Synonymous Sites15. Fran Supek and Tomislav Smuc: Distance Measures and Machine Learning Approaches for Codon Usage Analyses16. Kai Zeng: The Application of Population Genetics in the Study of Codon Usage Bias17. Maria do Ceu Santos and Manuel A. S. Santos: Structural and Molecular Features of Non-standard Genetic CodesIndex