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Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information

BACKGROUND: The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic, pedigree and genomic information simultaneously. In such a single-step procedure, genomic and pedigree-based relationships have to be compatible. As...

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Autores principales: Forni, Selma, Aguilar, Ignacio, Misztal, Ignacy
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3022661/
https://www.ncbi.nlm.nih.gov/pubmed/21208445
http://dx.doi.org/10.1186/1297-9686-43-1
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author Forni, Selma
Aguilar, Ignacio
Misztal, Ignacy
author_facet Forni, Selma
Aguilar, Ignacio
Misztal, Ignacy
author_sort Forni, Selma
collection PubMed
description BACKGROUND: The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic, pedigree and genomic information simultaneously. In such a single-step procedure, genomic and pedigree-based relationships have to be compatible. As there are many options to create genomic relationships, there is a question of which is optimal and what the effects of deviations from optimality are. METHODS: Data of litter size (total number born per litter) for 338,346 sows were analyzed. Illumina PorcineSNP60 BeadChip genotypes were available for 1,989. Analyses were carried out with the complete data set and with a subset of genotyped animals and three generations pedigree (5,090 animals). A single-trait animal model was used to estimate variance components and breeding values. Genomic relationship matrices were constructed using allele frequencies equal to 0.5 (G05), equal to the average minor allele frequency (GMF), or equal to observed frequencies (GOF). A genomic matrix considering random ascertainment of allele frequencies was also used (GOF*). A normalized matrix (GN) was obtained to have average diagonal coefficients equal to 1. The genomic matrices were combined with the numerator relationship matrix creating H matrices. RESULTS: In G05 and GMF, both diagonal and off-diagonal elements were on average greater than the pedigree-based coefficients. In GOF and GOF*, the average diagonal elements were smaller than pedigree-based coefficients. The mean of off-diagonal coefficients was zero in GOF and GOF*. Choices of G with average diagonal coefficients different from 1 led to greater estimates of additive variance in the smaller data set. The correlation between EBV and genomic EBV (n = 1,989) were: 0.79 using G05, 0.79 using GMF, 0.78 using GOF, 0.79 using GOF*, and 0.78 using GN. Accuracies calculated by inversion increased with all genomic matrices. The accuracies of genomic-assisted EBV were inflated in all cases except when GN was used. CONCLUSIONS: Parameter estimates may be biased if the genomic relationship coefficients are in a different scale than pedigree-based coefficients. A reasonable scaling may be obtained by using observed allele frequencies and re-scaling the genomic relationship matrix to obtain average diagonal elements of 1.
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spelling pubmed-30226612011-01-20 Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information Forni, Selma Aguilar, Ignacio Misztal, Ignacy Genet Sel Evol Research BACKGROUND: The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic, pedigree and genomic information simultaneously. In such a single-step procedure, genomic and pedigree-based relationships have to be compatible. As there are many options to create genomic relationships, there is a question of which is optimal and what the effects of deviations from optimality are. METHODS: Data of litter size (total number born per litter) for 338,346 sows were analyzed. Illumina PorcineSNP60 BeadChip genotypes were available for 1,989. Analyses were carried out with the complete data set and with a subset of genotyped animals and three generations pedigree (5,090 animals). A single-trait animal model was used to estimate variance components and breeding values. Genomic relationship matrices were constructed using allele frequencies equal to 0.5 (G05), equal to the average minor allele frequency (GMF), or equal to observed frequencies (GOF). A genomic matrix considering random ascertainment of allele frequencies was also used (GOF*). A normalized matrix (GN) was obtained to have average diagonal coefficients equal to 1. The genomic matrices were combined with the numerator relationship matrix creating H matrices. RESULTS: In G05 and GMF, both diagonal and off-diagonal elements were on average greater than the pedigree-based coefficients. In GOF and GOF*, the average diagonal elements were smaller than pedigree-based coefficients. The mean of off-diagonal coefficients was zero in GOF and GOF*. Choices of G with average diagonal coefficients different from 1 led to greater estimates of additive variance in the smaller data set. The correlation between EBV and genomic EBV (n = 1,989) were: 0.79 using G05, 0.79 using GMF, 0.78 using GOF, 0.79 using GOF*, and 0.78 using GN. Accuracies calculated by inversion increased with all genomic matrices. The accuracies of genomic-assisted EBV were inflated in all cases except when GN was used. CONCLUSIONS: Parameter estimates may be biased if the genomic relationship coefficients are in a different scale than pedigree-based coefficients. A reasonable scaling may be obtained by using observed allele frequencies and re-scaling the genomic relationship matrix to obtain average diagonal elements of 1. BioMed Central 2011-01-05 /pmc/articles/PMC3022661/ /pubmed/21208445 http://dx.doi.org/10.1186/1297-9686-43-1 Text en Copyright ©2011 Forni et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Forni, Selma
Aguilar, Ignacio
Misztal, Ignacy
Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
title Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
title_full Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
title_fullStr Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
title_full_unstemmed Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
title_short Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
title_sort different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3022661/
https://www.ncbi.nlm.nih.gov/pubmed/21208445
http://dx.doi.org/10.1186/1297-9686-43-1
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