Genetic Data Analysis for Plant and Animal Breeding

1. Front Matter

   Pages i-xvii

   PDF

2. Introduction to ASReml Software

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 1-48

3. A Review of Linear Mixed Models

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 49-86

4. Variance Modeling in ASReml

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 87-106

5. Breeding Values

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 107-140

6. Genetic Values

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 141-163

7. Multivariate Models

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 165-201

8. Spatial Analysis

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 203-226

9. Multi Environmental Trials

   • Fikret Isik, James Holland, Christian Maltecca

   Pages 227-262

10. Exploratory Marker Data Analysis

    • Fikret Isik, James Holland, Christian Maltecca

    Pages 263-285

11. Imputing Missing Genotypes

    • Fikret Isik, James Holland, Christian Maltecca

    Pages 287-309

12. Genomic Relationships and GBLUP

    • Fikret Isik, James Holland, Christian Maltecca

    Pages 311-354

13. Genomic Selection

    • Fikret Isik, James Holland, Christian Maltecca

    Pages 355-384

14. Back Matter

    Pages 385-400

    PDF

This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods or statistical packages covered here may not be available or they might be out of date in a few years. Ultimately the book is intended for professional breeders interested in utilizing these tools and approaches in their breeding programs. Lastly, we anticipate the usage of this volume for advanced level graduate courses in agricultural and breeding courses.

• Associate genetics
• Genomic selection
• Mixed models
• Plant and animal breeding
• Quantitative genetics

• Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, USA

  Fikret Isik

• United States Department of Agriculture – Agricultural Research Service, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, USA

  James Holland

• Department of Animal Science, North Carolina State University, Raleigh, USA

  Christian Maltecca

Fikret Isik is a Professor of quantitative genetics in the Department of Forestry and Environmental Resources and the Associate Director of the Tree Improvement Program at North Carolina State University.

Jim Holland is a research geneticist with the United States Department of Agriculture - Agriculture Research Service, and a Professor in the Department of Crop and Soil Sciences at North Carolina State University. 

Christian Maltecca is an Associate Professor of quantitative genetics and breeding in the Animal Science department at North Carolina State University.

Policies and ethics