Quantitative Genetics

ISBN-13: 9783030839390 / Angielski / Twarda / 2022 / 340 str.

Shizhong Xu

Spis treści

Preface

Introduction

Chapters 1-4:

Introduce quantitative genetics and provide review material for Mendelian genetics, population genetics, and statistics

Chapters 5-8:

Define genetic effects and genetic variances and introduce statistical tools to estimate the effects and variances

Chapters 9-12:

Introduce genetic relatedness between relatives and describe how to use the genetic relatedness to estimate heritability of a quantitative trait

Chapters 13-17:

Introduce the concept of artificial selection and describe various ways to perform artificial selection for maximum genetic gain

Chapters 18-20:

Introduce advanced quantitative genetics that incorporates molecular data, i.e., genetic mapping for quantitative trait loci

Appendix of Tables and Methods

GlossaryDefinitions

References for Further Reading

Index

O autorze

Shizhong Xu is Professor of Genetics and Statistics at University of California Riverside. He earned a BS degree in Animal Sciences at Shenyang Agricultural University (China), a MS degree in Quantitative Genetics at Northeast Agricultural University (China) and a PhD in Quantitative Genetics at Purdue University. He teaches two courses at UCR: Statistics for Life Sciences (STAT231B) and Quantitative Genetics (BPSC148). His research covers theoretical quantitative genetics, biostatistics and statistical genomics. He specializes in linear mixed models, generalized linear mixed models and Bayesian analysis. He published about 170 technical journal articles and two textbooks (including this one). He served as associate editors for journals of Heredity, Genetic Research, Molecular Biology and Evolution, and International Journal of Plant Genomics. He currently serves as associate editors for The Crop Journal and Forestry Research.

Blurb

The intended audience of this textbook are plant and animal breeders, upper-level undergraduate and graduate students in biological and agricultural science majors. Statisticians who are interested in understanding how statistical methods are applied to genetics and agriculture can benefit substantially by reading this book. One characteristic of this textbook is represented by three chapters of technical reviews for Mendelian genetics, population genetics and preliminary statistics, which are prerequisites for studying quantitative genetics. Numerous examples are provided to illustrate different methods of data analysis and estimation of genetic parameters. Along with each example of data analyses is the program code of SAS (statistical analysis system).