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Linear models for joint association and linkage QTL mapping

BACKGROUND: Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice...

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Detalles Bibliográficos
Autores principales: Legarra, Andrés, Fernando, Rohan L
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764561/
https://www.ncbi.nlm.nih.gov/pubmed/19788745
http://dx.doi.org/10.1186/1297-9686-41-43
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author Legarra, Andrés
Fernando, Rohan L
author_facet Legarra, Andrés
Fernando, Rohan L
author_sort Legarra, Andrés
collection PubMed
description BACKGROUND: Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure. RESULTS: We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission) average of the substitution effects of founders' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component) model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided. CONCLUSION: The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward.
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spelling pubmed-27645612009-10-21 Linear models for joint association and linkage QTL mapping Legarra, Andrés Fernando, Rohan L Genet Sel Evol Research BACKGROUND: Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure. RESULTS: We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission) average of the substitution effects of founders' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component) model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided. CONCLUSION: The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward. BioMed Central 2009-09-29 /pmc/articles/PMC2764561/ /pubmed/19788745 http://dx.doi.org/10.1186/1297-9686-41-43 Text en Copyright ©2009 Legarra and Fernando; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Legarra, Andrés
Fernando, Rohan L
Linear models for joint association and linkage QTL mapping
title Linear models for joint association and linkage QTL mapping
title_full Linear models for joint association and linkage QTL mapping
title_fullStr Linear models for joint association and linkage QTL mapping
title_full_unstemmed Linear models for joint association and linkage QTL mapping
title_short Linear models for joint association and linkage QTL mapping
title_sort linear models for joint association and linkage qtl mapping
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764561/
https://www.ncbi.nlm.nih.gov/pubmed/19788745
http://dx.doi.org/10.1186/1297-9686-41-43
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