Evolution and Selection of Quantitative Traits

Quantitative traits-be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene-usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important.

Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences.

Bruce Walsh, Professor, Department of Ecology and Evolutionary Biology, The University of Arizona, USA,Michael Lynch, Professor and Director, Biodesign Center for Mechanisms of Evolution, Arizona State University, USA

Bruce Walsh is Professor of Ecology and Evolutionary Biology at the University of Arizona. He has taught advanced classes on quantitative genetics in 25 different countries and his research interests are at the interface of biology, genetics, mathematical modelling, and statistics. He is also an avid lepidopterist, having described over two dozen species of new moths and has three species named after him.

Michael Lynch is Professor in the Schoool of Life Sciences at Arizona State University and is Center Director of the Biodesign Center for Mechanims of Evolution. His research is focused on mechanisms of evolution at the gene, genomic, cellular, and phenotypic levels, with special attention being given to the roles of mutation, random genetic drift, and recombination. He is a member of the US National Academy of Sciences, and a fellow of the American Academy of Arts and Sciences.

Preface
I
Introduction
1. Changes in quantitative traits over time
II
Evolution at one and two loci
2. Neutral evolution in one- and two-locus systems
3. The genetic effective size of a population
4. The nonadaptive forces of evolution
5. The population genetics of selection
6. Theorems of natural selection: Results of Price, Fisher, and Robertson
7. Interaction of selection, mutation, and drift
8. Hitchhiking and selective sweeps
9. Using molecular data to detect selection: Signatures from recent single events
10. Using molecular data to detect selection: Signatures from multiple historical events
III
Drift and quantitative traits
11. Changes in genetic variance induced by drift
12. The neutral divergence of quantitative traits
IV
Short-term response on a single character
13. Short-term changes in the mean: 1. The breeder's equation
14. Short-term changes in the mean: 2. Truncation and threshold selection
15. Short-term changes in the mean: 3. Permanent versus transient response
16. Short-term changes in the variance: 1. Changes in the additive variance
17. Short-term changes in the variance: 2. Changes in environmental variance
18. Analysis of short-term selection experiments: 1. Least-squares approaches
19. Analysis of short-term selection experiments: 2. Mixed-model and bayesian approaches
20. Selection response in natural populations
V
Selection in structured populations
21. Family-based selection
22. Associative effects: Competition, social interactions, group and kin selection
23. Selection under inbreeding
VI
Population-genetic models of trait response
24. The infinitesimal model and its extensions
25. Long-term response: 1. Deterministic aspects
26. Long-term response: 2. Finite population size and mutation
27. Long-term response: 3. Adaptive walks
28. Maintenance of quantitative genetic variation
VII
Measuring selection on traits
29. Individual fitness and the measurement of univariate selecton
30. Measuring multivariate selection
VIII
Appendices
A1. Diffusion theory
A2. Introduction to Bayesian Analysis
A3. Markov Chain Monte Carlo and Gibbs sampling
A4. Multiple comparisons: Bonferroni corrections, false-discovery rates, and meta-analysis
A5. The geometry of vectors and matrices: Eigenvalues and eigenvectors
A6. Derivatives of vectors and vector-valued functions
Literature Cited
Author Index
Organism and Trait Index
Subject Index