Genetics and Analysis of Quantitative Traits Foundations

Almost every trait in nature shows variation, both within populations and between populations and species. The field of quantitative genetics is the very broad umbrella that attempts to separate environmental from genetic sources of variation. As a result, it has powerful applications in animal and plant breeding, evolution, ecology, medicine, anthropology, behaviour, population genetics, conservation biology, genomics, and statistics.

This second edition of Genetics and Analysis of Quantitative Traits is a fully rewritten and greatly expanded revision of the first edition, published in 1998, which provided the first, modern, unified treatment of quantitative genetics. In the past two decades, there have been massive advancements in the field coupled with explosive growth in new quantitative methods; those developments are covered in this new edition.

The book weaves important biological applications with a full development of the theory and appropriate statistical tools. There are extensive discussions of important linear-algebra tools, linear and mixed models, likelihood and Bayesian estimation, as well as false discovery rates, multiple comparisons, and meta-analysis. More than 100 worked examples (ranging from microbes to humans) illustrate the key concepts using real-world applications.

This extensive reference will be suitable for graduate-level students and professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to applied evolutionary biologists working in breed improvement for agriculture, human geneticists, and statisticians.

Bruce Walsh, Professor, Ecology & Evolutionary Biology, University of Arizona, USA,Peter M. Visscher, Professor of Quantitative Genetics, University of Oxford, UK,Michael Lynch, Director, Center for Mechanisms of Evolution, Arizona State University, USA

Bruce Walsh obtained a BS in Mathematical Population Biology of UC Davis and a PhD in Genetics from the University of Washington. Following a short post-doc at the University of Chicago, in 1986 he joined the Dept of Ecology and Evolutionary Biology at the University of Arizona, where he is currently a Professor, with adjunct appointments in multiple departments (Plant Science, Animal Science, Molecular and Cellular Biology, Public Health, Applied Mathematics). His work focuses on mathematical models of evolution and statistical methods in quantitative genetics. He has a special interest in education, having taught over 15,000 undergraduates at Arizona and has taught short courses in over 25 countries on various aspects of genetics, statistics, and evolution.

Peter Martin Visscher FRS is a Dutch-Australian-British geneticist. He is professor of Quantitative Genetics at the University of Oxford and the University of Queensland. After an undergraduate degree in the Netherlands, Visscher undertook postgraduate study at the University of Edinburgh in animal genetics. He is married to Professor Naomi R. Wray FAA, a fellow geneticist who holds the Michael Davys Professorship in Neuroscience at the University of Oxford. Visscher has held Faculty positions at the University of Edinburgh and the University of Queensland, and Honorary or Affiliate positions at UMCG Groningen and the Karolinska Institute.

Michael Lynch is Regents Professor and the Director of the Biodesign Center for Mechanisms of Evolution, Arizona State University. A member of the US National Academy of Sciences and of the American Academy of Arts and Sciences, and past president of the Society for Molecular Biology and Evolution, the Genetics Society of America, the Society for the Study of Evolution, and the American Genetics Association. Recent awards include the Thomas Hunt Morgan Medal from the Genetics Society of America and the Lifetime Achievement Award from the Society for Molecular Biology and Evolution.

PrefaceI. Foundations of Quantitative Genetics1. An overview of quantitative genetics2. Properties of distributions3. Covariance, regression, and correlation4. Properties of single loci5. Sources of genetic variation for multilocus traits6. Sources of environmental variation7. Resemblance between relatives8. Marker-based estimation of relatedness9. Introduction to linear models and matrix algebra10. Linear and mixed models11. Analysis of line crosses12. Inbreeding depression13. Heterosis and outbreeding depression14. Matters of scaleII. Quantiative trait loci15. Polygenes and polygenic mutation16. Detecting major genes17. Principles of marker-based mapping18. Linkage mapping and characterizing QTLS: inbred line crosses19. Linkage mapping and characterizing QTLS: outbred populations of relatives20. Association mapping21. Quantitative genomics and probing the nature of quantitative genetic variationIII. AppendicesA1. Expectations, variances, and covariances of compound variablesA2. Path, network, and causality analysisA3. Further topics in matrix algebra and linear modelsA4. Maximum likelihood estimation and likelihood-ratio testsA5. Computing the power of statistical testsA6. Multiple comparisons: bonferroni corrections, false-discovery rates, and meta-analysisA7. Introduction to bayesian analysisA8. Markov chain monte carlo and gibbs samplingA9. Experimental Design