Genomic selection in animals. ([2016])

• Record Type: Book
• Further Information: Note: Joel Weller, Institute of Animal Sciences, Agricultural Research Organization, Bet Dagan, Israel.
• Authors: Weller, Joel Ira
• Contents: Preface: Welcome to the “promised land” Chapter 1: Historical overview 1.1 Introduction 1.2 The Mendelian theory of genetics 1.3 The Mendelian basis of quantitative variation 1.4 Detection of QTL with morphological and biochemical markers 1.5 DNA-level markers, 1974-1994 1.6 DNA-level markers since 1995, SNPs and CNV 1.7 QTL detection prior to genomic selection 1.8 Marker-assisted selection prior to genomic selection 1.9 Summary Chapter 2: Types of current genetic markers and genotyping methodologies 2.1 Introduction 2.2 From biochemical markers to DNA-level markers 2.3 DNA microsatellites 2.4 Single nucleotide polymorphisms 2.5 Copy Number variation 2.6 Summary Chapter 3: Advanced animal breeding programs prior to genomic selection 3.1 Introduction 3.2 Within a breed selection, . basic principles and equations 3.3 Traditional selection schemes for dairy cattle 3.4 Crossbreeding schemes, advantages and disadvantages 3.5 Summary Chapter 4: Economic evaluation of genetic breeding programs 4.1 Introduction 4.2 National economy, vs. . competition among breeders 4.3 Criteria for economic evaluation, profit horizon, interest rate, return on investment. 4.4 Summary Chapter 5: Least squares, maximum likelihood and Bayesian parameter estimation 5.1 Introduction 5.2 Least squares parameter estimation 5.3 Maximum likelihood estimation for a single parameter 5.4 Maximum likelihood multi-parameter estimation 5.5 Confidence intervals and hypothesis testing for MLE 5.6 Methods to maximize likelihood functions 5.7 Bayesian estimation 5.8 Parameter estimation via the Gibbs sampler 5.9 Summary Chapter 6: Trait-based genetic evaluation, . the mixed model 6.1 Introduction 6.2 Principles of selection index 6.3 The mixed linear model 6.4 The mixed model equations 6.5 Solving the mixed model equations 6.6 Important properties of mixed model solutions 6.7 Multivariate mixed model analysis 6.8 The individual animal model 6.9 Yield deviations and daughter yield deviations 6.10 Analysis of DYD as the dependent variable 6.11 Summary Chapter 7: Maximum likelihood and Bayesian estimation of QTL parameters with random effects included in the model 7.1 Introduction 7.2 Maximum likelihood estimation of QTL effects with random effects included in the model, . the daughter design 7.3 The granddaughter design 7.4 Determination of prior distributions of the QTL parameters for the granddaughter design 7.5 Formula for Bayesian estimation and tests of significance of a segregating QTL in a granddaughter design 7.6 Summary Chapter 8: Maximum likelihood, restricted maximum likelihoodand Bayesian estimation for mixed models 8.1 Introduction 8.2 Derivation of solutions to the mixed model equations by maximum likelihood 8.3 Estimation of the mixed model variance components 8.4 Maximum likelihood estimation of variance components 8.5 Restricted maximum likelihood estimation of variance components 8.6 Estimation of variance components via the Gibbs sampler 8.7 Summary Chapter 9: Distribution of genetic effects, . theory and results 9.1 Introduction 9.2 Modeling the polygenic variance 9.3 The effective number of QTL 9.4 The case of the missing heritability 9.5 Methods for determination of causative mutations for QTL in animals and humans 9.6 Determination of QTN in dairy cattle 9.7 Estimating the number of segregating QTL based on linkage mapping studies 9.8 Results of genome scans of dairy cattle by granddaughter designs 9.9 Results of genome-wise association studies (GWAS) in dairy cattle by SNP chips 9.10Summary Chapter 10: The multiple comparison problem 10.1 Introduction 10.2 Multiple markers and whole genome scans 10.3 QTL detection by permutation tests 10.4 A priori determination of the proportion of false positives 10.5 Biases with estimation of multiple QTL 10.6 Bayesian estimation of QTL from whole genome scans, . theory 10.7 Bayes-A and Bayes-B models 10.8 Bayesian estimation of QTL from whole genome scans, simulation results 10.9 Summary Chapter 11: Linkage mapping of QTL 11.1 Introduction 11.2 Interval mapping by nonlinear regression, the backcross design 11.3 Interval mapping for daughter and granddaughter designs 11.4 Computation of confidence intervals 11.5 Simulation studies of confidence intervals 11.6 Summary Chapter 12: Linkage disequilibrium mapping of QTL 12.1 Introduction 12.2 Estimation of linkage disequilibrium in animal populations 12.3 Linkage disequilibrium mapping QTL mapping, basic principles 12.4 Joint linkage and linkage disequilibrium mapping 12.5 Multi-trait and multiple QTL LD mapping 12.6 Summary Chapter 13: Marker assisted selection, . basic strategies 13.1 Introduction 13.2 Situations in which selection index is inefficient 13.3 Potential contribution of MAS for selection within a breed - general considerations 13.4 Phenotypic selection vs. . MAS for individual selection 13.5 MAS for sex-limited traits 13.6 MAS including marker and phenotypic information on relatives 13.7 Maximum selection efficiency of MAS with all QTL known, relative to trait-based selection, and the reduction in RSE due to sampling variance 13.8 Marker information in segregating populations 13.9 Inclusion of marker information in “animal model” genetic evaluations 13.10 Predicted genetic gains with genomic evaluations, results of simulation studies 13.11 Summary Chapter 14: Genetic evaluation based on dense marker maps, basic strategies 14.1 Introduction 14.2 The basic steps in genomic evaluation 14.3 Evaluation of genomic estimated breeding values 14.4 Sources of bias in genomic evaluation 14.5 Marker effects fixed or random? 14.6 Individual markers vs. haplotypes 14.7 Total markers vs. . usable markers 14.8 Deviation of genotype frequencies from their expectations 14.9 Inclusion of all markers vs. . selection of markers with significant effects 14.10 The genomic relationship matrix 14.11 Summary Chapter 15: Genetic evaluation based on analysis of genetic evaluations or daughter-yield evaluations 15.1 Introduction 15.2 Comparison of single-stage and multi-stage models 15.3 Derivation and properties of daughter yields and DYD 15.4 Computation of "deregressed" genetic evaluations 15.5 Analysis of DYD as the dependent variable with all markers included as random effects 15.6 Computation of reliabilities for genomic estimated breeding values 15.7 Bayesian weighting of marker effects 15.8 Additional Bayesian methods for genomic evaluation 15.9 Summary Chapter 16: Genomic evaluation based on analysis of production records 16.1 Introduction 16.2 Single-stage methodologies, . the basic strategy 16.3 Computation of the modified relationship matrix when only a fraction of the animals are genotyped, the problem 16.4 Criteria for valid genetic relationship matrices 16.5 Computation of the modified relationship matrix when only a fraction of the animals are genotyped, the solution 16.6 Solving the mixed model equations without inverting H 16.7 Inverting the genomic relationship matrix 16.8 Estimation of.
• Publisher Details: Hoboken, New Jersey : Wiley Blackwell
• Publication Date: 2016
• Extent: 1 online resource, illustrations (black and white, and colour)
• Subjects: 636.0821; Animal genetics; Animal genetics -- Statistical methods; Animal genetics -- Mathematical models; Genetic markers
• Languages: English
• ISBNs: 9781119213635
• Related ISBNs: 9780470960073
• Notes: Note: Includes bibliographical references and index.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.