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Genomic Selection in Animals [Kõva köide]

  • Formaat: Hardback, 192 pages, kõrgus x laius x paksus: 252x178x15 mm, kaal: 499 g
  • Ilmumisaeg: 04-Mar-2016
  • Kirjastus: Wiley-Blackwell
  • ISBN-10: 0470960078
  • ISBN-13: 9780470960073
Teised raamatud teemal:
Genomic Selection in AnimalsSuurem pilt
  • Formaat: Hardback, 192 pages, kõrgus x laius x paksus: 252x178x15 mm, kaal: 499 g
  • Ilmumisaeg: 04-Mar-2016
  • Kirjastus: Wiley-Blackwell
  • ISBN-10: 0470960078
  • ISBN-13: 9780470960073
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780470960073.html
Märksõnad:

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.

Arvustused

"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)

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