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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
04/10/2014 |
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Actualizado : |
10/02/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
FORNI, S.; AGUILAR, I.; MISZTAL, I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information. |
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Fecha de publicación : |
2011 |
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Fuente / Imprenta : |
Genetics Selection Evolution, 2011, v.43, no.1, p.443-447. |
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ISSN : |
0999-193X |
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DOI : |
10.1186/1297-9686-43-1 |
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Idioma : |
Inglés |
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Notas : |
ARTICULO OPEN ACCESS. |
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Contenido : |
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.
© 2011 Forni et al; licensee BioMed Central Ltd. MenosBACKGROUND:
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 ped... Presentar Todo |
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Thesagro : |
CERDOS; GENOTIPOS; MEJORAMIENTO GENÉTICO ANIMAL. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/3441/1/Aguilar-I.-2011.-GSE-v.431-OPEN-ACCESS.pdf
http://www.biomedcentral.com/content/pdf/1297-9686-43-1.pdf
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Marc : |
LEADER 03070naa a2200217 a 4500
001 1050906
005 2020-02-10
008 2011 bl uuuu u00u1 u #d
022 $a0999-193X
024 7 $a10.1186/1297-9686-43-1$2DOI
100 1 $aFORNI, S.
245 $aDifferent genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information.$h[electronic resource]
260 $c2011
500 $aARTICULO OPEN ACCESS.
520 $aBACKGROUND: 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. © 2011 Forni et al; licensee BioMed Central Ltd.
650 $aCERDOS
650 $aGENOTIPOS
650 $aMEJORAMIENTO GENÉTICO ANIMAL
700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
773 $tGenetics Selection Evolution, 2011$gv.43, no.1, p.443-447.
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