The vast majority of character traits show continuous variation. Quantitative genetics could therefore be central to numerous approaches in both and applied evolution and ecology. To date, however, quantitative genetics theory is divided among disparate and unreconciled disciplines, and can be quite intimidating mathematically. In this book, that authors attempt to bring together the theoretical framework, empirical results, and contemporary statistical techniques from the diverse fields of plant and animal breeding, evolutionary biology, and human genetics into a comprehensive and approachable guide. It covers the basic biology, theory and methods of analysis of quantitative characters. A second book (not yet published) will cover the evolutionary dynamics of quantitative traits.
The book is separated into three sections. The first section reviews the history of quantitative genetics and develops a comprehensive linear model for quantitative traits from single-locus theory. This shows both the theoretical potential for a unified theory of quantitative genetics and the practical problems of decomposing underlying mechanisms. The second section describes methods for identification of major loci regulating quantitative traits (primarily a combination of molecular marker techniques and mapping and characterization using inbred line crosses and outbred populations). The third section deals with practical procedures for estimating the variance components of quantitative traits; the pros and cons of parent-offspring regression, sib analysis, twins and clones, as well as character correlations, cross-classified designs, genotype X environment interaction, maternal effects, sex linkage, breeding values, and complex pedigrees. For the less quantitative reader, other chapters and appendixes cover statistical and mathematical techniques over an impressively broad scope, and are much more extensive than most population genetics textbooks.
Each topic is covered comprehensively, and text is absolutely teeming with cornerstone and contemporary literature references (about four thousand in total). Nonetheless, any of the chapters could easily be expanded to explain ideas more thoroughly. The primary audience will likely be limited to quantitative-minded graduate students and researchers. Thus, Lynch and Walsh succeed in bringing together disparate aspects of quantitative genetics theory. They do not make quantitative genetics easily accessible, but this may be a necessary tradeoff. Even thought it may not reach all of its intended audience, this volume provides a comprehensive resource that will no doubt become the standard reference in the field.