320 pages, 50 b/w illustrations
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 DNA substitutions. 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 sequence reconstruction, 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 their usage 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 and empirical 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 as well as current methods to analyse codon usage bias are presented.
PART I: MODELING CODON EVOLUTION
1: Adrian Schneider and Gina M. Cannarozzi: Background
2: Maria Anisimova: Parametric Models of Codon Evolution
3: Adrian Schneider and Gina M. Cannarozzi: Empirical and Semi-empirical Models of Codon Evolution
4: Nicolas Rodrigue and Nicolas Lartillot: Monte Carlo Computational Approaches in Bayesian Codon Substitution Modeling
5: Hong Gu, Katherine A. Dunn, and Joseph P. Bielawski: Likelihood Based Clustering (LiBaC) for Codon Models
6: Maria Anisimova and David A. Liberles: Detecting and Understanding Natural Selection
7: Jeffrey L. Thorne, Nicolas Lartillot, Nicolas Rodrigue, and Sang Chul Choi: Codon Models as a Vehicle for Reconciling Population Genetics with Interspecific Sequence Data
8: Gavin A. Huttley and Von Bing Yap: Robust Estimation of Natural Selection Using Parametric Codon Models
9: Miguel Arenas and David Posada: Simulation of Coding Sequence Evolution
10: Steven A. Benner: Use of Codon Models in Molecular Dating and Functional Analysis
11: 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 Divergence
12: Gabriela Aguileta and Tatiana Giraud: Codon Models Applied to the Study of Fungal Genomes
PART II: CODON USAGE BIAS
13: Alexander Roth, Maria Anisimova, and Gina M. Cannarozzi: Measuring Codon Usage Bias
14: Nimrod D. Rubinstein and Tal Pupko: Detection and Analysis of Conservation at Synonymous Sites
15: Fran Supek and Tomislav Smuc: Distance Measures and Machine Learning Approaches for Codon Usage Analyses
16: Kai Zeng: The Application of Population Genetics in the Study of Codon Usage Bias
17: Maria do Ceu Santos and Manuel A. S. Santos: Structural and Molecular Features of Non-standard Genetic Codes
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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 interested in molecular evolution, protein structure and the origins of life since working with Prof. Steven A. Benner at the University of Florida in 1996-1998. Her current research focuses are: codon models of evolution, codon bias as well as phylogeny and ancestral reconstruction. She is on the Editorial Board of "Trends in Evolutionary Biology".
Adrian Schneider received his Ph.D. in 2009 from the ETH Zurich, Switzerland for his thesis on codon-based models of evolution and Mammalian phylogeny. Afterwards, he worked as a post-doctoral researcher at the Institute of Evolutionary Biology at the University of Edinburgh, Scotland and is currently a post-doctoral researcher at the University of Utrecht, Netherlands. His current work includes the development of new semi-empirical codon models.