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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.
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 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.
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
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.
Evolutionary quantitative genetics (EQG) provides a formal theoretical foundation for quantitatively linking natural selection and genetic variation to the rate and expanse of adaptive evolution. It has become the dominant conceptual framework for interpreting the evolution of quantitative traits in terms of elementary forces (mutation, inheritance, selection, and drift). Despite this success, the relevance of EQG to many biological scenarios remains relatively unappreciated, with numerous fields yet to fully embrace its approach. Part of the reason for this lag is that conceptual advances in EQG have not yet been fully synthesized and made accessible to a wider academic audience. A comprehensive, accessible overview is therefore now timely, and Evolutionary Quantitative Genetics provides this much-needed synthesis. The central argument of the book is that an adaptive landscape concept can be used to understand both evolutionary process within lineages and the pattern of adaptive radiations. In particular, it provides a convincing argument that models with a moving adaptive peak carry us further than any other conceptual approach yet devised. Although additive theory holds center stage, the book mentions and references departures from additivity including non-Gaussian distributions of allelic effects, dominance, epistasis, maternal effects and phenotypic plasticity. This accessible, advanced textbook is aimed principally at students (from senior undergraduate to postgraduate) as well as practising scientists in the fields of evolutionary biology, ecology, physiology, functional morphology, developmental biology, comparative biology, paleontology, and beyond who are interested in how adaptive radiations are produced by evolutionary and ecological processes.
Taken together, these studies document both the benefits and pitfalls of quantitative genetics.
This new textbook for students taking courses in evolution is addressed to one of the most difficult questions evolutionary biology, that of selection. Covering both artificial and natural selection, the author has written a short, readable text that will appeal to students and professionals alike. how the nature of the process determines the nature of evolutionary change.
One of the holy grails in biology is the ability to predict functional characteristics from an organism's genetic sequence. Despite decades of research since the first sequencing of an organism in 1995, scientists still do not understand exactly how the information in genes is converted into an organism's phenotype, its physical characteristics. Functional genomics attempts to make use of the vast wealth of data from "-omics" screens and projects to describe gene and protein functions and interactions. A February 2020 workshop was held to determine research needs to advance the field of functional genomics over the next 10-20 years. Speakers and participants discussed goals, strategies, and technical needs to allow functional genomics to contribute to the advancement of basic knowledge and its applications that would benefit society. This publication summarizes the presentations and discussions from the workshop.
Nonhuman primates have played critical roles in biomedical research, and they are among the few animals whose use in research continues to increase. The scienti?c value of nonhuman primates derives from their close phylogenetic proximity to man and their consequent anatomic, physiologic, and genetic similarities to man. Only nonhuman primates can provide adequate models for many complex physiological and disease processes of humans. The baboon is a relative newcomer to the repertoire of nonhuman primates used in biomedical research. However, in less than 50 years since its ?rst use in the U. S. , it has become one of the most popular laboratory primate species. It is larger than the other widely used monkey species, making it advantageous for many types of experiments and technological developments. It is extraordinarily hardy and highly fecund in captivity. It closely resembles humans in a variety of physiological and disease processes, such as cholesterol metabolism, early stages of atherosclerosis, and alcoholic liver disease. Its chromosomes closely resemble those of humans, and many genes of the two species lie in the same chromosomal order. Among all primates, baboons are the most widely used models for the genetics of susceptibility to complex diseases and they are the ?rst nonhuman primate for which a framework genetic linkage map was established. In addition, the baboon genome is currently being sequenced, and as a result the utility of this species for biomedical research will be dramatically increased.