Genomic Selection in Animals

The field of whole genome selection has quickly developed into the breeding methodology of the future. As efforts to map a wide variety of animal genomes have matured and full animal genomes are now available for many animal scientists and breeders are looking to apply these techniques to livestock production. Providing a comprehensive, forward-looking review of animal genomics, Genomic Selection in Animals provides coverage of genomic selection in a variety of economically important species including cattle, swine, and poultry. The historical foundations of genomic selection are followed by chapters that review and assess current techniques. The final chapter looks toward the future and what lies ahead for field as application of genomic selection becomes more widespread. A concise, useful summary of the field by one of the world’s leading researchers, Genomic Selection in Animals fills an important gap in the literature of animal breeding and genomics.

Table of Contents:
Preface: Welcome to the “Promised Land” xiii Chapter 1 Historical Overview 1 Introduction 1 The Mendelian Theory of Genetics 1 The Mendelian Basis of Quantitative Variation 2 Detection of QTL with Morphological and Biochemical Markers 2 DNA-Level Markers, 1974–1994 3 DNA-Level Markers Since 1995: SNPs and CNV 4 QTL Detection Prior to Genomic Selection 4 MAS Prior to Genomic Selection 5 Summary 6 Chapter 2 Types of Current Genetic Markers and Genotyping Methodologies 7 Introduction 7 From Biochemical Markers to DNA]Level Markers 7 DNA Microsatellites 8 Single Nucleotide Polymorphisms 8 Copy Number Variation 9 Complete Genome Sequencing 9 Summary 10 Chapter 3 Advanced Animal Breeding Programs Prior to Genomic Selection 11 Introduction 11 Within a Breed Selection: Basic Principles and Equations 11 Traditional Selection Schemes for Dairy Cattle 12 Crossbreeding Schemes: Advantages and Disadvantages 14 Summary 15 Chapter 4 Economic Evaluation of Genetic Breeding Programs 17 Introduction 17 National Economy versus Competition among Breeders 17 Criteria for Economic Evaluation: Profit Horizon, Interest Rate, and Return on Investment 18 Summary 20 Chapter 5 Least Squares, Maximum Likelihood, and Bayesian Parameter Estimation 21 Introduction 21 Least Squares Parameter Estimation 21 ML Estimation for a Single Parameter 22 ML Multiparameter Estimation 24 Methods to Maximize Likelihood Functions 26 Confidence Intervals and Hypothesis Testing for MLE 26 Bayesian Estimation 27 Parameter Estimation via the Gibbs Sampler 28 Summary 29 Chapter 6 Trait-Based Genetic Evaluation: The Mixed Model 31 Introduction 31 Principles of Selection Index 31 The Mixed Linear Model 34 The Mixed Model Equations 34 Solving the Mixed Model Equations 35 Important Properties of Mixed Model Solutions 36 Multivariate Mixed Model Analysis 37 The Individual Animal Model 38 Yield Deviations and Daughter Yield Deviations 39 Analysis of DYD as the Dependent Variable 40 Summary 41 Chapter 7 Maximum Likelihood and Bayesian Estimation of QTL Parameters with Random Effects Included in the Model 43 Introduction 43 Maximum Likelihood Estimation of QTL Effects with Random Effects Included in the Model, the Daughter Design 43 The Granddaughter Design 45 Determination of Prior Distributions of the QTL Parameters for the Granddaughter Design 46 Formula for Bayesian Estimation and Tests of Significance of a Segregating QTL in a Granddaughter Design 49 Summary 50 Chapter 8 Maximum Likelihood, Restricted Maximum Likelihood, and Bayesian Estimation for Mixed Models 51 Introduction 51 Derivation of Solutions to the Mixed Model Equations by Maximum Likelihood 51 Estimation of the Mixed Model Variance Components 52 Maximum Likelihood Estimation of Variance Components 52 Restricted Maximum Likelihood Estimation of Variance Components 54 Estimation of Variance Components via the Gibbs Sampler 55 Summary 58 Chapter 9 Distribution of Genetic Effects, Theory, and Results 59 Introduction 59 Modeling the Polygenic Variance 59 The Effective Number of QTL 61 The Case of the Missing Heritability 61 Methods for Determination of Causative Mutations for QTL in Animals and Humans 62 Determination of QTN in Dairy Cattle 63 Estimating the Number of Segregating QTL Based on Linkage Mapping Studies 64 Results of Genome Scans of Dairy Cattle by Granddaughter Designs 65 Results of Genome]Wide Association Studies in Dairy Cattle by SNP Chips 66 Summary 66 Chapter 10 The Multiple Comparison Problem 69 Introduction 69 Multiple Markers and Whole Genome Scans 69 QTL Detection by Permutation Tests 71 QTL Detection Based on the False Discovery Rate 71 A Priori Determination of the Proportion of False Positives 74 Biases with Estimation of Multiple QTL 75 Bayesian Estimation of QTL from Whole Genome Scans: Theory 76 Bayes A and Bayes B Models 77 Bayesian Estimation of QTL from Whole Genome Scans: Simulation Results 79 Summary 80 Chapter 11 Linkage Mapping of QTL 81 Introduction 81 Interval Mapping by Nonlinear Regression: The Backcross Design 81 Interval Mapping for Daughter and Granddaughter Designs 83 Computation of Confidence Intervals 84 Simulation Studies of CIs 85 Empirical Methods to Estimate CIs, Parametric and Nonparametric Bootstrap, and Jackknife Methods 86 Summary 87 Chapter 12 Linkage Disequilibrium Mapping of QTL 89 Introduction 89 Estimation of Linkage Disequilibrium in Animal Populations 89 Linkage Disequilibrium QTL Mapping: Basic Principles 90 Joint Linkage and Linkage Disequilibrium Mapping 92 Multitrait and Multiple QTL LD Mapping 93 Summary 93 Chapter 13 Marker-Assisted Selection: Basic Strategies 95 Introduction 95 Situations in Which Selection Index is Inefficient 95 Potential Contribution of MAS for Selection within a Breed: General Considerations 96 Phenotypic Selection versus MAS for Individual Selection 97 MAS for Sex-Limited Traits 98 MAS Including Marker and Phenotypic Information on Relatives 99 Maximum Selection Efficiency of MAS with All QTL Known, Relative to Trait-Based Selection, and the Reduction in RSE Due to Sampling Variance 99 Marker Information in Segregating Populations 100 Inclusion of Marker Information in “Animal Model” Genetic Evaluations 100 Predicted Genetic Gains with Genomic Estimated Breeding Values: Results of Simulation Studies 101 Summary 102 Chapter 14 Genetic Evaluation Based on Dense Marker Maps: Basic Strategies 103 Introduction 103 The Basic Steps in Genomic Evaluation 103 Evaluation of Genomic Estimated Breeding Values 104 Sources of Bias in Genomic Evaluation 104 Marker Effects Fixed or Random? 105 Individual Markers versus Haplotypes 106 Total Markers versus Usable Markers 106 Deviation of Genotype Frequencies from Their Expectations 107 Inclusion of All Markers versus Selection of Markers with Significant Effects 107 The Genomic Relationship Matrix 108 Summary 109 Chapter 15 Genetic Evaluation Based on Analysis of Genetic Evaluations or Daughter-Yield Evaluations 111 Introduction 111 Comparison of Single]Step and Multistep Models 111 Derivation and Properties of Daughter Yields and DYD 112 Computation of “Deregressed” Genetic Evaluations 113 Analysis of DYD as the Dependent Variable with All Markers Included as Random Effects 114 Computation of Reliabilities for Genomic Estimated Breeding Values 116 Bayesian Weighting of Marker Effects 116 Additional Bayesian Methods for Genomic Evaluation 117 Summary 117 Chapter 16 Genomic Evaluation Based on Analysis of Production Records 119 Introduction 119 Single-Step Methodologies: The Basic Strategy 119 Computation of the Modified Relationship Matrix when only a Fraction of the Animals are Genotyped: The Problem 120 Criteria for Valid Genetic Relationship Matrices 120 Computation of the Modified Relationship Matrix when only a Fraction of the Animals are Genotyped, the Solution 121 Solving the Mixed Model Equations without Inverting H 121 Inverting the Genomic Relationship Matrix 122 Estimation of Reliabilities for Genomic Breeding Values Derived by Single]Step Methodologies 122 Single-Step Computation of Genomic Evaluations with Unequally Weighted Marker Effects 123 Summary 124 Chapter 17 Validation of Methods for Genomic Estimated Breeding Values 125 Introduction 125 Criteria for Evaluation of Estimated Genetic Values 125 Methods Used to Validate Genomic Genetic Evaluations 126 Evaluation of Two-Step Methodology Based on Simulated Dairy Cattle Data 127 Evaluation of Multistep Methodology Based on Actual Dairy Cattle Data 127 Evaluation of Single-Step Methodologies Based on Actual Dairy Cattle Data 128 Evaluation of Single- and Multistep Methodologies Based on Actual Poultry Data 129 Evaluation of Single- and Multistep Methodologies Based on Actual Swine Data 130 Evaluation of GEBV for Plants Based on Actual Data 130 Summary 131 Chapter 18 By-Products of Genomic Analysis: Pedigree Validation and Determination 133 Introduction 133 The Effects of Incorrect Parentage Identification on Breeding Programs 133 Principles of Parentage Verification and Identification with Genetic Markers 134 Paternity Validation Prior to High]Density SNP Chips 135 Paternity Validation and Determination with SNP Chips 135 Validation of More Distant Relationships 136 Pedigree Reconstruction with High]Density Genetic Markers 137 Summary 137 Chapter 19 Imputation of Missing Genotypes: Methodologies, Accuracies, and Effects on Genomic Evaluations 139 Introduction 139 Determination of Haplotypes for Imputation 139 Imputation in Humans versus Imputation in Farm Animals 140 Algorithms Proposed for Imputation in Human and Animal Populations 141 Comparisons of Accuracy and Speed of Imputation Methods 142 Effect of Imputation on Genomic Genetic Evaluations 143 Summary 144 Chapter 20 Detection and Validation of Quantitative Trait Nucleotides 145 Introduction 145 GWAS for Economic Traits in Commercial Animals 146 Detection of QTN: Is It Worth the Effort? 146 QTN Determination in Farm Animals: What Constitutes Proof? 147 Concordance between DNA-Level Genotypes and QTL Status 148 Determination of Concordance by the “APGD” 148 Determination of Phase for Grandsires Heterozygous for the QTL 149 Determination of Recessive Lethal Genes by GWAS and Effects Associated with Heterozygotes 150 Verification of QTN by Statistical and Biological Methods 150 Summary 151 Chapter 21 Future Directions and Conclusions 153 Introduction 153 More Markers versus More Individuals with Genotypes 153 Computation of Genomic Evaluations for Cow and Female Calves 154 Improvement of Genomic Evaluation Methods 154 Long-Term Considerations 155 Weighting Evaluations of Old versus Young Bulls 156 Direct Genetic Manipulation in Farm Animals 156 Velogenetics: The Synergistic Use of MAS and Germ-Line Manipulation 157 Summary 157 References 159 Index 171

About the Author :
Joel Ira Weller is a Research Scientist at the Institute of Animal Sciences, ARO, The Volcani Center in Bet Dagan, Israel.

Review :
"Genomic Selection in Animals is a well-written book by a leading animal quantitative geneticist...This book will be particularly useful for graduate students in animal breeding and genetics, and more broadly for professionals with an interest in understanding how genomic information is being incorporated into breeding programs...Overall, this book is a readable summary of the concepts and current methods underlying genomic selection and a useful reference that I recommend for those with an interest in this rapidly evolving field." (Journal of the American Veterinary Medical Association 15/03/2017)