Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations

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Fil: García Baccino, Carolina Andrea. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina.

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Autores principales: García Baccino, Carolina Andrea, Legarra, Andres, Christensen, O. F., Misztal, Ignacy, Pocrnic, I., Vitezica, Zulma Gladis, Cantet, Rodolfo Juan Carlos
Formato: Artículo publishedVersion
Lenguaje:Inglés
Publicado: 2017
Acceso en línea:http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2017garciabaccino1
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FAUBA Digital - Facultad de Agronomía (UBA) de Universidad de Buenos Aires
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spelling snrd:2017garciabaccino12021-10-15T16:56:07Z García Baccino, Carolina Andrea Legarra, Andres Christensen, O. F. Misztal, Ignacy Pocrnic, I. Vitezica, Zulma Gladis Cantet, Rodolfo Juan Carlos 2017 Fil: García Baccino, Carolina Andrea. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. Fil: Legarra, Andres. Université de Toulouse. GenPhySE, INRA, INPT, ENVT. Tolosan, France. Fil: Christensen, O. F. Aarhus University. Department of Molecular Biology and Genetics. Center for Quantitative Genetics and Genomics. Tjele, Denmark. Fil: Misztal, Ignacy. University of Georgia. Animal and Dairy Science. Athens, USA. Fil: Pocrnic, I. University of Georgia. Animal and Dairy Science. Athens, USA. Fil: Vitezica, Zulma Gladis. Université de Toulouse. GenPhySE, INRA, INPT, ENVT. Tolosan, France. Fil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. Metafounders are pseudo-individuals that encapsulate genetic heterozygosity and relationships within and across base pedigree populations, i.e. ancestral populations. This work addresses the estimation and usefulness of metafounder relationships in single-step genomic best linear unbiased prediction (ssGBLUP). We show that ancestral relationship parameters are proportional to standardized covariances of base allelic frequencies across populations, such as Fst fixation indexes. These covariances of base allelic frequencies can be estimated from marker genotypes of related recent individuals and pedigree. Simple methods for their estimation include naïve computation of allele frequencies from marker genotypes or a method of moments that equates average pedigree-based and marker-based relationships. Complex methods include generalized least squares (best linear unbiased estimator (BLUE) or maximum likelihood based on pedigree relationships. To our knowledge, methods to infer Fst coefficients from marker data have not been developed for related individuals. We derived a genomic relationship matrix, compatible with pedigree relationships, that is constructed as a cross-product of (−1,0,1)codes and that is equivalent (apart from scale factors) to an identity-by-state relationship matrix at genome-wide markers. Using a simulation with a single population under selection in which only males and youngest animals are genotyped, we observed that generalized least squares or maximum likelihood gave accurate and unbiased estimates of the ancestral relationship parameter (true value: 0.40) whereas the naïve method and the method of moments were biased (average estimates of 0.43 and 0.35). We also observed that genomic evaluation by ssGBLUP using metafounders was less biased in terms of estimates of genetic trend (bias of 0.01 instead of 0.12), resulted in less overdispersed (0.94 instead of 0.99) and as accurate (0.74) estimates of breeding values than ssGBLUP without metafounders and provided consistent estimates of heritability. Estimation of metafounder relationships can be achieved using BLUP-like methods with pedigree and markers. Inclusion of metafounder relationships reduces bias of genomic predictions with no loss in accuracy. tbls., grafs. application/pdf 10.1186/s12711-017-0309-2 0999-193X http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2017garciabaccino1 eng info:eu-repo/semantics/openAccess openAccess http://ri.agro.uba.ar/greenstone3/library/page/biblioteca#section4 Genetics selection evolution Vol.49, no.1 1-14 http://www.biomedcentral.com/ Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations info:eu-repo/semantics/article info:ar-repo/semantics/artículo publishedVersion info:eu-repo/semantics/publishedVersion
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-140
collection FAUBA Digital - Facultad de Agronomía (UBA)
language Inglés
orig_language_str_mv eng
description Fil: García Baccino, Carolina Andrea. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina.
format Artículo
Artículo
publishedVersion
publishedVersion
author García Baccino, Carolina Andrea
Legarra, Andres
Christensen, O. F.
Misztal, Ignacy
Pocrnic, I.
Vitezica, Zulma Gladis
Cantet, Rodolfo Juan Carlos
spellingShingle García Baccino, Carolina Andrea
Legarra, Andres
Christensen, O. F.
Misztal, Ignacy
Pocrnic, I.
Vitezica, Zulma Gladis
Cantet, Rodolfo Juan Carlos
Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations
author_facet García Baccino, Carolina Andrea
Legarra, Andres
Christensen, O. F.
Misztal, Ignacy
Pocrnic, I.
Vitezica, Zulma Gladis
Cantet, Rodolfo Juan Carlos
author_sort García Baccino, Carolina Andrea
title Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations
title_short Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations
title_full Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations
title_fullStr Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations
title_full_unstemmed Metafounders are related to Fst fixation indices and reduce bias in single - step genomic evaluations
title_sort metafounders are related to fst fixation indices and reduce bias in single - step genomic evaluations
publishDate 2017
url http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2017garciabaccino1
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