Cargando…

Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals

As crossbreeding is extensively used in some livestock species, we aimed to evaluate the performance of single-step GBLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) methods to predict Genomic Estimated Breeding Values (GEBVs) of crossbred animals. Different training population scenarios were evaluate...

Descripción completa

Detalles Bibliográficos
Autores principales: Alvarenga, Amanda B., Veroneze, Renata, Oliveira, Hinayah R., Marques, Daniele B. D., Lopes, Paulo S., Silva, Fabyano F., Brito, Luiz F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162606/
https://www.ncbi.nlm.nih.gov/pubmed/32328083
http://dx.doi.org/10.3389/fgene.2020.00263
_version_ 1783523063544938496
author Alvarenga, Amanda B.
Veroneze, Renata
Oliveira, Hinayah R.
Marques, Daniele B. D.
Lopes, Paulo S.
Silva, Fabyano F.
Brito, Luiz F.
author_facet Alvarenga, Amanda B.
Veroneze, Renata
Oliveira, Hinayah R.
Marques, Daniele B. D.
Lopes, Paulo S.
Silva, Fabyano F.
Brito, Luiz F.
author_sort Alvarenga, Amanda B.
collection PubMed
description As crossbreeding is extensively used in some livestock species, we aimed to evaluate the performance of single-step GBLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) methods to predict Genomic Estimated Breeding Values (GEBVs) of crossbred animals. Different training population scenarios were evaluated: (SC1) ssGBLUP based on a single-trait model considering purebred and crossbred animals in a joint training population; (SC2) ssGBLUP based on a multiple-trait model to enable considering phenotypes recorded in purebred and crossbred training animals as different traits; (SC3) WssGBLUP based on a single-trait model considering purebred and crossbred animals jointly in the training population (both populations were used for SNP weights' estimation); (SC4) WssGBLUP based on a single-trait model considering only purebred animals in the training population (crossbred population only used for SNP weights' estimation); (SC5) WssGBLUP based on a single-trait model and the training population characterized by purebred animals (purebred population used for SNP weights' estimation). A complex trait was simulated assuming alternative genetic architectures. Different scaling factors to blend the inverse of the genomic (G(−1)) and pedigree ([Formula: see text]) relationship matrices were also tested. The predictive performance of each scenario was evaluated based on the validation accuracy and regression coefficient. The genetic correlations across simulated populations in the different scenarios ranged from moderate to high (0.71–0.99). The scenario mimicking a completely polygenic trait ([Formula: see text] 0) yielded the lowest validation accuracy (0.12; for SC3 and SC4). The simulated scenarios assuming 4,500 QTLs affecting the trait and [Formula: see text] resulted in the greatest GEBV accuracies (0.47; for SC1 and SC2). The regression coefficients ranged from 0.28 (for SC3 assuming polygenic effect) to 1.27 (for SC2 considering 4,500 QTLs). In general, SC3 and SC5 resulted in inflated GEBVs, whereas other scenarios yielded deflated GEBVs. The scaling factors used to combine G(−1) and [Formula: see text] had a small influence on the validation accuracies, but a greater effect on the regression coefficients. Due to the complexity of multiple-trait models and WssGBLUP analyses, and a similar predictive performance across the methods evaluated, SC1 is recommended for genomic evaluation in crossbred populations with similar genetic structures [moderate-to-high (0.71–0.99) genetic correlations between purebred and crossbred populations].
format Online
Article
Text
id pubmed-7162606
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-71626062020-04-23 Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals Alvarenga, Amanda B. Veroneze, Renata Oliveira, Hinayah R. Marques, Daniele B. D. Lopes, Paulo S. Silva, Fabyano F. Brito, Luiz F. Front Genet Genetics As crossbreeding is extensively used in some livestock species, we aimed to evaluate the performance of single-step GBLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) methods to predict Genomic Estimated Breeding Values (GEBVs) of crossbred animals. Different training population scenarios were evaluated: (SC1) ssGBLUP based on a single-trait model considering purebred and crossbred animals in a joint training population; (SC2) ssGBLUP based on a multiple-trait model to enable considering phenotypes recorded in purebred and crossbred training animals as different traits; (SC3) WssGBLUP based on a single-trait model considering purebred and crossbred animals jointly in the training population (both populations were used for SNP weights' estimation); (SC4) WssGBLUP based on a single-trait model considering only purebred animals in the training population (crossbred population only used for SNP weights' estimation); (SC5) WssGBLUP based on a single-trait model and the training population characterized by purebred animals (purebred population used for SNP weights' estimation). A complex trait was simulated assuming alternative genetic architectures. Different scaling factors to blend the inverse of the genomic (G(−1)) and pedigree ([Formula: see text]) relationship matrices were also tested. The predictive performance of each scenario was evaluated based on the validation accuracy and regression coefficient. The genetic correlations across simulated populations in the different scenarios ranged from moderate to high (0.71–0.99). The scenario mimicking a completely polygenic trait ([Formula: see text] 0) yielded the lowest validation accuracy (0.12; for SC3 and SC4). The simulated scenarios assuming 4,500 QTLs affecting the trait and [Formula: see text] resulted in the greatest GEBV accuracies (0.47; for SC1 and SC2). The regression coefficients ranged from 0.28 (for SC3 assuming polygenic effect) to 1.27 (for SC2 considering 4,500 QTLs). In general, SC3 and SC5 resulted in inflated GEBVs, whereas other scenarios yielded deflated GEBVs. The scaling factors used to combine G(−1) and [Formula: see text] had a small influence on the validation accuracies, but a greater effect on the regression coefficients. Due to the complexity of multiple-trait models and WssGBLUP analyses, and a similar predictive performance across the methods evaluated, SC1 is recommended for genomic evaluation in crossbred populations with similar genetic structures [moderate-to-high (0.71–0.99) genetic correlations between purebred and crossbred populations]. Frontiers Media S.A. 2020-04-09 /pmc/articles/PMC7162606/ /pubmed/32328083 http://dx.doi.org/10.3389/fgene.2020.00263 Text en Copyright © 2020 Alvarenga, Veroneze, Oliveira, Marques, Lopes, Silva and Brito. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Alvarenga, Amanda B.
Veroneze, Renata
Oliveira, Hinayah R.
Marques, Daniele B. D.
Lopes, Paulo S.
Silva, Fabyano F.
Brito, Luiz F.
Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals
title Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals
title_full Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals
title_fullStr Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals
title_full_unstemmed Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals
title_short Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals
title_sort comparing alternative single-step gblup approaches and training population designs for genomic evaluation of crossbred animals
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162606/
https://www.ncbi.nlm.nih.gov/pubmed/32328083
http://dx.doi.org/10.3389/fgene.2020.00263
work_keys_str_mv AT alvarengaamandab comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals
AT veronezerenata comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals
AT oliveirahinayahr comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals
AT marquesdanielebd comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals
AT lopespaulos comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals
AT silvafabyanof comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals
AT britoluizf comparingalternativesinglestepgblupapproachesandtrainingpopulationdesignsforgenomicevaluationofcrossbredanimals