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| 5. |  | LEGARRA, A.; CHRISTENSEN, O. F.; VITEZICA, Z. G.; AGUILAR, I.; MISZTAL, I. Across-breeds ancestral relationships and metafounders for genomic evaluation. Volume Genetic Improvement Programs: Selection using molecular information, 075. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.075. Acknowledgements: This project has been financed by X-Gen and GenSSeq actions from SelGen metaprogram (INRA). We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees for providing computing resources.| Biblioteca(s): INIA Las Brujas. |
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| 6. | | ANTONIOS, S.; RODRÍGUEZ-RAMILO, S.T.; AGUILAR, I.; ASTRUC, J.M.; LEGARRA, A.; VITEZICA, Z. G. Genomic and pedigree estimation of inbreeding depression for semen traits in the Basco-Béarnaise dairy sheep breed. Journal of Dairy Science, 2021, volume 104, number 3, pages 3221-3230. doi: https://doi.org/10.3168/jds.2020-18761 Article history: Receibed: April 21, 2020 / Accepted: October 5, 2020 /First Publication: 23 Decembrer 2020.
Corresponding author: zulma.viterica@inrae.fr| Biblioteca(s): INIA Treinta y Tres. |
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| 8. | | FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; CANTET, R. J. C. Quality control of genotypes using heritability estimates of gene content at the marker. Genetics, 2015, v. 199, p. 675-681. OPEN ACCESS. Manuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015.| Biblioteca(s): INIA Las Brujas. |
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| 9. | | FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; CANTET, R.J.C.; MISZTAL, I. Quality control of genotypes using heritability estimates of gene content. Volume Genetic Improvement Programs: Selection using molecular information (Posters), 471. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.471.| Biblioteca(s): INIA Las Brujas. |
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| 10. | | WANG, H.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A.; FERNANDO, R.L.; VITEZICA, Z.; OKIMOTO, R.; WING, T.; HAWKEN, R.; MUIR, W.M. Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens. Frontiers in Genetics, 2014, v.5, p.1-10. OPEN ACCESS. Article history: Received 03 March 2014 // Paper pending published 04 April 2014 // Accepted 25 April 2014 // Published online: 20 May 2014.| Biblioteca(s): INIA Las Brujas. |
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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 : |
07/10/2014 |
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Actualizado : |
09/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
B - 1 |
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Autor : |
VITEZICA, Z.G.; AGUILAR, I.; MISZTAL, I.; LEGARRA, A. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Bias in genomic predictions for populations under selection. |
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Fecha de publicación : |
2011 |
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Fuente / Imprenta : |
Genetics Research, 2011, v.93 no.5, p.357-366. |
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ISSN : |
0016-6723 |
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DOI : |
10.1017/S001667231100022X |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 27 January 2011 / Revised 27 March 2011 / Published online 18 July 2011. |
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Contenido : |
ABSTRACT.
Prediction of genetic merit or disease risk using genetic marker information is becoming a common practice for selection of livestock and plant species. For the successful application of genome-wide marker-assisted selection (GWMAS), genomic predictions should be accurate and unbiased. The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities. Prediction of genetic values was by best-linear unbiased prediction (BLUP) using data either from relatives summarized in pseudodata for genotyped individuals (multiple-step method) or using all available data jointly (single-step method). The single-step method combined genomic- and pedigree-based relationship matrices. Predictions by the multiple-step method were biased. Predictions by a single-step method were less biased and more accurate but under strong selection were less accurate. When genomic relationships were shifted by a constant, the single-step method was unbiased and the most accurate. The value of that constant, which adjusts for non-random selection of genotyped individuals, can be derived analytically.
© 2011 Cambridge University Press. |
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Thesagro : |
DETECCIÓN DE QTLS; MARCADORES GENÉTICOS; MEJORAMIENTO GENÉTICO ANIMAL. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
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008 2011 bl uuuu u00u1 u #d
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100 1 $aVITEZICA, Z.G.
245 $aBias in genomic predictions for populations under selection.$h[electronic resource]
260 $c2011
500 $aArticle history: Received 27 January 2011 / Revised 27 March 2011 / Published online 18 July 2011.
520 $aABSTRACT. Prediction of genetic merit or disease risk using genetic marker information is becoming a common practice for selection of livestock and plant species. For the successful application of genome-wide marker-assisted selection (GWMAS), genomic predictions should be accurate and unbiased. The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities. Prediction of genetic values was by best-linear unbiased prediction (BLUP) using data either from relatives summarized in pseudodata for genotyped individuals (multiple-step method) or using all available data jointly (single-step method). The single-step method combined genomic- and pedigree-based relationship matrices. Predictions by the multiple-step method were biased. Predictions by a single-step method were less biased and more accurate but under strong selection were less accurate. When genomic relationships were shifted by a constant, the single-step method was unbiased and the most accurate. The value of that constant, which adjusts for non-random selection of genotyped individuals, can be derived analytically. © 2011 Cambridge University Press.
650 $aDETECCIÓN DE QTLS
650 $aMARCADORES GENÉTICOS
650 $aMEJORAMIENTO GENÉTICO ANIMAL
700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
700 1 $aLEGARRA, A.
773 $tGenetics Research, 2011$gv.93 no.5, p.357-366.
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