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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
11/09/2014 |
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Actualizado : |
24/06/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 2 |
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Autor : |
MISZTAL, I.; VITEZICA, Z.G.; LEGARRA, A.; AGUILAR, I.; SWAN, A.A. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Unknown-parent groups in single-step genomic evaluation. |
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Fecha de publicación : |
2013 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2013, v.130, no.4, p.252-258. |
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ISSN : |
0931-2668 |
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DOI : |
http://dx.doi.org/10.1111/jbg.12025 |
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Idioma : |
Inglés |
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Contenido : |
SUMMARY:.
In single-step genomic evaluation using best linear unbiased prediction (ssGBLUP), genomic predictions are calculated with a relationship matrix that combines pedigree and genomic information. For missing pedigrees, unknown selection processes, or inclusion of several populations, a BLUP model can include unknown-parent groups (UPG) in the animal effect. For ssGBLUP, UPG equations also involve contributions from genomic relationships. When those contributions are ignored, UPG solutions and genetic predictions can be biased. Options to eliminate or reduce such bias are presented. First, mixed model equations can be modified to include contributions to UPG elements from genomic relationships (greater software complexity). Second, UPG can be implemented as separate effects (higher cost of computing and data processing). Third, contributions can be ignored when they are relatively small, but they may be small only after refinements to UPG definitions. Fourth, contributions may approximately cancel out when genomic and pedigree relationships are constructed for compatibility; however, different construction steps are required for unknown parents from the same or different populations. Finally, an additional polygenic effect that also includes UPG can be added to the model.
© 2013 Blackwell Verlag GmbH. |
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Palabras claves : |
BLUP (BEST LINEAR UNBIASED PREDICTION). |
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Thesagro : |
EVALUACIÓN GENÉTICA; GENÉTICA ANIMAL. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
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008 2013 bl uuuu u00u1 u #d
022 $a0931-2668
024 7 $ahttp://dx.doi.org/10.1111/jbg.12025$2DOI
100 1 $aMISZTAL, I.
245 $aUnknown-parent groups in single-step genomic evaluation.$h[electronic resource]
260 $c2013
520 $aSUMMARY:. In single-step genomic evaluation using best linear unbiased prediction (ssGBLUP), genomic predictions are calculated with a relationship matrix that combines pedigree and genomic information. For missing pedigrees, unknown selection processes, or inclusion of several populations, a BLUP model can include unknown-parent groups (UPG) in the animal effect. For ssGBLUP, UPG equations also involve contributions from genomic relationships. When those contributions are ignored, UPG solutions and genetic predictions can be biased. Options to eliminate or reduce such bias are presented. First, mixed model equations can be modified to include contributions to UPG elements from genomic relationships (greater software complexity). Second, UPG can be implemented as separate effects (higher cost of computing and data processing). Third, contributions can be ignored when they are relatively small, but they may be small only after refinements to UPG definitions. Fourth, contributions may approximately cancel out when genomic and pedigree relationships are constructed for compatibility; however, different construction steps are required for unknown parents from the same or different populations. Finally, an additional polygenic effect that also includes UPG can be added to the model. © 2013 Blackwell Verlag GmbH.
650 $aEVALUACIÓN GENÉTICA
650 $aGENÉTICA ANIMAL
653 $aBLUP (BEST LINEAR UNBIASED PREDICTION)
700 1 $aVITEZICA, Z.G.
700 1 $aLEGARRA, A.
700 1 $aAGUILAR, I.
700 1 $aSWAN, A.A.
773 $tJournal of Animal Breeding and Genetics, 2013$gv.130, no.4, p.252-258.
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