Quantitative Genetic Variation describes some of the experimental approaches to quantitative genetic variation, along with their potential applications and limitations. It considers one of the most widely applicable tools, i.e., biometrical analysis, as well as individual polygenic effects, specific components of a quantitative genetic trait, and artificial selection, and it shows how selection experiments can address specific developmental and genetic questions. Organized into four sections encompassing 17 chapters, this volume begins with a historical overview of the study of quantitative genetic variation, along with genetic variation in fungi and Drosophila. It then discusses the biometrical approach to quantitative variation, selection theory and analysis, uses and limitations of polygene mapping, and computer simulation of the breeding program for polygene location. The reader is also introduced to genes affecting quantitative aspects of physiology in rodents, as well as cytological markers and quantitative variation in wheat. This book will be extremely useful to students, researchers, and geneticists.

The impetus for this book arose out of my previous book, The Evolution of Life Histories (Roff, 1992). In that book I presented a single chapter on quanti tative genetic theory. However, as the book was concerned with the evolution of life histories and traits connected to this, the presence of quantitative genetic variation was an underlying theme throughout. Much of the focus was placed on optimality theory, for it is this approach that has proven to be extremely successful in the analysis of life history variation. But quantitative genetics cannot be ig nored, because there are some questions for which optimality approaches are inappropriate; for example, although optimality modeling can address the ques tion of the maintenance of phenotypic variation, it cannot say anything about genetic variation, on which further evolution clearly depends. The present book is, thus, a natural extension of the first. I have approached the problem not from the point of view of an animal or plant breeder but from that of one interested in understanding the evolution of quantitative traits in wild populations. The subject is large with a considerable body of theory: I generally present the assumptions underlying the analysis and the results, giving the relevant references for those interested in the intervening mathematics. My interest is in what quantitative genetics tells me about evolutionary processes; therefore, I have concentrated on areas of research most relevant to field studies.

Professors Lynch and Walsh bring together the diverse array of theoretical and empirical applications of quantitative genetics in a work that is comprehensive and accessible to anyone with a rudimentary understanding of statistics and genetics.

This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.

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.

Taken together, these studies document both the benefits and pitfalls of quantitative genetics.

This book gathers the expertise of 30 evolutionary biologists from around the globe to highlight how applying the field of quantitative genetics - the analysis of the genetic basis of complex traits - aids in the study of wild populations.