Nature in Silico

Population Genetic Simulation and its Evolutionary Interpretation Using C++ and R
1. Auflage 2022
ISBN: 978-3-030-97380-3
Verlag: Springer International Publishing

Buch, Englisch, 313 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 664 g

Dramatic advances in computing power enable simulation of DNA sequences generated by complex microevolutionary scenarios that include mutation, population structure, natural selection, meiotic recombination, demographic change, and explicit spatial geographies. Although retrospective, coalescent simulation is computationally efficient—and covered here—the primary focus of this book is forward-in-time simulation, which frees us to simulate a wider variety of realistic microevolutionary models. The book walks the reader through the development of a forward-in-time evolutionary simulator dubbed FORward Time simUlatioN Application (FORTUNA). The capacity of FORTUNA grows with each chapter through the addition of a new evolutionary factor to its code. Each chapter also reviews the relevant theory and links simulation results to key evolutionary insights. The book addresses visualization of results through development of R code and reference to more than 100 figures. All code discussedin the book is freely available, which the reader may use directly or modify to better suit his or her own research needs. Advanced undergraduate students, graduate students, and professional researchers will all benefit from this introduction to the increasingly important skill of population genetic simulation. 

Zielgruppe

Graduate

Autoren/Hrsg.

Haasl, Ryan J.

Fachgebiete

• Naturwissenschaften Biowissenschaften Botanik Pflanzenreproduktion, Verbreitung, Genetik
• Naturwissenschaften Biowissenschaften Tierkunde / Zoologie Tiergenetik, Reproduktion
• Naturwissenschaften Biowissenschaften Biowissenschaften Evolutionsbiologie
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Naturwissenschaften Biowissenschaften Biowissenschaften Ökologie

Inhaltsverzeichnis

Introduction and relevance.- Retrospective and prospective simulation.- Data structures and computational efficiency.- Mutation.- Population size and genetic drift.- Migration and population structure.- Meiotic recombination.- Natural selection.- Implementing all five factors simultaneously.- Modeling different life histories.- Spatially-explicit simulation.- Calculating summary statistics and visualization.- Approximate Bayesian computation: preliminaries.- Approximate Bayesian computation: implementation.- Comparing simulated genetic data to 1000 Genomes data.- The spread of the invasive species Japanese hops in the Upper Midwest, USA.

Über Autor(innen)

Ryan J. Haasl is an Associate Professor of Biology at the University of Wisconsin-Platteville. He holds an M.A. in Entomology from the University of Kansas and a Ph.D. in Genetics from the University of Wisconsin-Madison. His research focuses on the use of simulation and statistical computing to explore favorite topics such as natural selection targeting microsatellites, phylogenomics, and the consolidation of microevolutionary dynamics and macroevolutionary pattern. He is passionate about teaching genetics and evolutionary biology to undergraduate students and fostering public literacy in the biological sciences through outreach.