• 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.

  • 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

  • Joel Ira Weller, Ph.D. (Researcher)

    Department of Ruminant Science
    Institute of Animal Sciences
    Agricultural Research Organization,
    The Volcani Center
    68 HaMaccabim Road, P.O.B 15159
    Rishon LeZion 7505101 Israel

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