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| 1. |  | WANG, Y.J.; WANG, L.; SHEPHARD, D.; WANG, F.; PATINDOL, J. Properties and structures of flours and starches from whole, broken, and yelowed rice grains. ln: Norman, R.J.; Meullenet, J.F. B.R. Wells Rice research studies 2000. Fayetteville, Arkansas (USA): Arkansas Agricultural Experiment Station, 2001. p. 322-329 (AAES Research Series ; 485)| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 2. | | LOURENCO, D. A. L.; TSURUTA, S.; FRAGOMENI, B. O.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; BERTRAND, J. K.; AMEN, T. S.; WANG. L.; MOSER, D. W.; MISZTAL, I. Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*) Journal of Animal Science, 2015, v. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS. (*) This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI), and Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the U.S. Department of Agriculture?s...| Biblioteca(s): INIA Las Brujas. |
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| 3. | | GEORGE, T.S.; GILES, C.D.; MENEZES-BLACKBURN, D.; CONDRON, L.M.; GAMA-RODRIGUES, A.C.; JAISI, D.; LANG, F.; NEAL, A.L.; STUTTER, M.I.; ALMEIDA, D.S.; BOL, R.; CABUGAO, K.G.; CELI, L.; COTNER, J.B.; FENG, G.; GOLL, D.S.; HALLAMA, M.; KRUEGER, J.; PLASSARD, C.; ROSLING, A.; DARCH, T.; FRASER, T.; GIESLER, R.; RICHARDSON, A.E.; TAMBURINI, F.; SHAND, C.A.; LUMSDON, D.G.; ZHANG, H.; BLACKWEL, M.S.A.; WEARING, C.; MEZELI, M.M.; ALMÅS, Å.R.; AUDETTE, Y.; BERTRAND, I.; BEYHAUT, E.; BOITT, G.; BRADSHAW, N.; BREARLEY, C.A.; BRUULSEMA, T.W.; CIAIS, P.; COZZOLINO, V.; DURAN, P.C.; MORA, M.L.; DE MENEZES, A.B.; DODD, R.J.; DUNFIELD, K.; ENGL, C.; FRAZÃO, J.J.; GARLAND, G.; GONZÁLEZ JIMÉNEZ, J.L.; GRACA, J.; GRANGER, S.J.; HARRISON, A.F.; HEUCK, C.; HOU, E.Q.; JOHNES, P.J.; KAISER, K.; KJÆR. H.A.; KLUMPP, E.; LAMB, A.L.; MACINTOSH, K.A.A; MACKAY, E.B.; MCGRATH, J.; MCINTYRE, C.; MCLAREN, T.; MÉSZÁROS, E.; MISSONG, A.; MOOSHAMMER, M.; NEGRÓN, C.P.; NELSON, L.A.; PFAHLER, V.; POBLETE-GRANT, P.; RANDALL, M.; SEGUEL, A.; SETH, K.; SMITH, A.C.; SMITS, M.M.; SOBARZO, J.A.; SPOHN, M.; TAWARAYA, K.; TIBBETT, M.; VORONEY, V.; WALLANDER, H.; WANG, L.; WASAKI, J.; HAYGARTH, P.M. Organic phosphorus in the terrestrial environment: a perspective on the state of the art and future priorities. Plant and Soil, 1 June 2018, Volume 427, Issue 1-2, Pages 191-208. Article history: Received: 28 April 2017 /Accepted: 17 August 2017 / Published online: 6 October 2017.
Update notice: Correction to: Organic phosphorus in the terrestrial environment: a perspective on the state of the art and future...| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 3 | |
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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 : |
18/12/2017 |
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Actualizado : |
15/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
LOURENCO, D.A.L.; FRAGOMENI, B.O.; BRADFORD, H.L.; MENEZES I.R.; FERRAZ, J.B.S.; AGUILAR, I.; MISZTAL, I. |
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Afiliación : |
D.A.L. LOURENCO, Universidad de Georgia (UG); B.O. FRAGOMENI, Universidad de Georgia (UG); H.L. BRADFORD, Universidad de Georgia (UG); I.R. MENEZES, FZEA, University of Sao Paulo.; J.B.S. FERRAZ, FZEA, University of Sao Paulo.; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; I. MISZTAL, Universidad de Georgia (UG). |
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Título : |
Implications of SNP weighting on single-step genomic predictions for different reference population sizes. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2017, v. 134 (6), p. 463-471. |
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DOI : |
10.1111/jbg.12288 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 28 February 2017 / Accepted: 19 July 2017.
This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI) and by Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the US Department of Agriculture's National Institute of Food and Agriculture. We gratefully acknowledge the very helpful comments by the two anonymous reviewers, and we thank Andra H. Nelson for assisting with data analysis. |
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Contenido : |
ABSTRACT.
We investigated the importance of SNP weighting in populations with 2,000 to 25,000 genotyped animals. Populations were simulated with two effective sizes (20 or 100) and three numbers of QTL (10, 50 or 500). Pedigree information was available for six generations; phenotypes were recorded for the four middle generations. Animals from the last three generations were genotyped for 45,000 SNP. Single-step genomic BLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used to estimate genomic EBV using a genomic relationship matrix (G). The WssGBLUP performed better in small genotyped populations; however, any advantage for WssGBLUP was reduced or eliminated when more animals were genotyped. WssGBLUP had greater resolution for genome-wide association (GWA) as did increasing the number of genotyped animals. For few QTL, accuracy was greater for WssGBLUP than ssGBLUP; however, for many QTL, accuracy was the same for both methods. The largest genotyped set was used to assess the dimensionality of genomic information (number of effective SNP). The number of effective SNP was considerably less in weighted G than in unweighted G. Once the number of independent SNP is well represented in the genotyped population, the impact of SNP weighting becomes less important.
© 2017 Blackwell Verlag GmbH |
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Palabras claves : |
ACCURAY; BAYES B; SNP WEIGHTING; VARIABLE SELECTION; WEIGTED SSGBLUP. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 02612naa a2200277 a 4500
001 1057902
005 2019-10-15
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1111/jbg.12288$2DOI
100 1 $aLOURENCO, D.A.L.
245 $aImplications of SNP weighting on single-step genomic predictions for different reference population sizes.$h[electronic resource]
260 $c2017
500 $aArticle history: Received: 28 February 2017 / Accepted: 19 July 2017. This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI) and by Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the US Department of Agriculture's National Institute of Food and Agriculture. We gratefully acknowledge the very helpful comments by the two anonymous reviewers, and we thank Andra H. Nelson for assisting with data analysis.
520 $aABSTRACT. We investigated the importance of SNP weighting in populations with 2,000 to 25,000 genotyped animals. Populations were simulated with two effective sizes (20 or 100) and three numbers of QTL (10, 50 or 500). Pedigree information was available for six generations; phenotypes were recorded for the four middle generations. Animals from the last three generations were genotyped for 45,000 SNP. Single-step genomic BLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used to estimate genomic EBV using a genomic relationship matrix (G). The WssGBLUP performed better in small genotyped populations; however, any advantage for WssGBLUP was reduced or eliminated when more animals were genotyped. WssGBLUP had greater resolution for genome-wide association (GWA) as did increasing the number of genotyped animals. For few QTL, accuracy was greater for WssGBLUP than ssGBLUP; however, for many QTL, accuracy was the same for both methods. The largest genotyped set was used to assess the dimensionality of genomic information (number of effective SNP). The number of effective SNP was considerably less in weighted G than in unweighted G. Once the number of independent SNP is well represented in the genotyped population, the impact of SNP weighting becomes less important. © 2017 Blackwell Verlag GmbH
653 $aACCURAY
653 $aBAYES B
653 $aSNP WEIGHTING
653 $aVARIABLE SELECTION
653 $aWEIGTED SSGBLUP
700 1 $aFRAGOMENI, B.O.
700 1 $aBRADFORD, H.L.
700 1 $aMENEZES I.R.
700 1 $aFERRAZ, J.B.S.
700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
773 $tJournal of Animal Breeding and Genetics, 2017$gv. 134 (6), p. 463-471.
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