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Open AccessJournal ArticleDOI

Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

Theo H E Meuwissen, +2 more
- 01 Apr 2001 - 
- Vol. 157, Iss: 4, pp 1819-1829
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TLDR
It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
Abstract
Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of ∼50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size (Ne = 100), the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.

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Citations
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Journal ArticleDOI

Genome-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens.

TL;DR: Genomic prediction model Bayes-B was used to identify genomic regions associated with the mean and standard deviation of egg weight at three ages in a commercial brown egg layer line and a novel approach using the posterior distribution of window variances from the Monte Carlo Markov Chain samples were used to describe genetic architecture.
Journal ArticleDOI

Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle

TL;DR: Using BEAGLE for pre-phasing and IMPUTE2 for imputation is a fast and accurate strategy to increase the size of the reference data and in turn the accuracy of imputation when only few animals are available.
Book ChapterDOI

Implementing a QTL detection study (GWAS) using genomic prediction methodology.

TL;DR: How to make inferences from commonly used Bayesian methods for genomic prediction about genome-wide association study results is described and how to interpret the results is commented on.
Journal ArticleDOI

Prospects for Genomic Selection in Cassava Breeding

TL;DR: Prospects for GS in cassava are good and improving, with accuracy generally similar across breeding populations, and data sharing across programs improves predictions in some circumstances.
References
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Book

Introduction to quantitative genetics

TL;DR: The genetic constitution of a population: Hardy-Weinberg equilibrium and changes in gene frequency: migration mutation, changes of variance, and heritability are studied.
BookDOI

Markov Chain Monte Carlo in Practice

TL;DR: The Markov Chain Monte Carlo Implementation Results Summary and Discussion MEDICAL MONITORING Introduction Modelling Medical Monitoring Computing Posterior Distributions Forecasting Model Criticism Illustrative Application Discussion MCMC for NONLINEAR HIERARCHICAL MODELS.
Book

Genetics and Analysis of Quantitative Traits

Michael Lynch, +1 more
TL;DR: This book discusses the genetic Basis of Quantitative Variation, Properties of Distributions, Covariance, Regression, and Correlation, and Properties of Single Loci, and Sources of Genetic Variation for Multilocus Traits.
Journal ArticleDOI

An Introduction to Population Genetics Theory

James F. Crow, +1 more
- 01 Sep 1971 - 
TL;DR: An introduction to population genetics theory, An introduction to Population Genetics Theory, Population Genetics theory, Population genetics theory as discussed by the authors, Population genetics, population genetics, and population genetics theories, Population Genetic Theory
Book

An introduction to population genetics theory

TL;DR: An introduction to population genetics theory, An introduction to Population Genetics theory, and more.
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