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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
11/12/2018 |
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Actualizado : |
06/02/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
MOTA, R. R.; LOPES, P. S.; TEMPELMAN, R. J.; SILVA, F. F.; AGUILAR, I.; GOMES, C. C. G.; CARDOSO, F. F. |
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Afiliación : |
R. R. MOTA, Animal Science Department, Federal University of Viçosa, Brazil; P. S. LOPES, Animal Science Department, Federal University of Viçosa, Viçosa, Brazil; R. J. TEMPELMAN, Animal Science Department, Michigan State University, United States; F. F. SILVA, Animal Science Department, Federal University of Viçosa, Brazil; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; C. C. G. GOMES, Embrapa South Livestock, Brazil; F. F. CARDOSO, eAnimal Science Department, Federal University of Pelotas, Brazil. |
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Título : |
Genome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models. |
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Fecha de publicación : |
2016 |
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Fuente / Imprenta : |
Journal of Animal Science, May 2016, Volume 94, Issue 5, Pages 1834 - 1843. |
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ISSN : |
0021-8812 |
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DOI : |
10.2527/jas.2015-0194 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received December 11, 2015. // Accepted March 10, 2016. |
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Contenido : |
ABSTRACT.
Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold K-means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02), 0.67 (SE 0.02), and 0.66 (SE 0.02) for ABLUP, HBLUP, HLRNM, and ALRNM, respectively. For 5-fold random partitioning, HLRNM (0.71 ± 0.01) was statistically different from ABLUP (0.67 ± 0.01). However, no statistical significance was reported when considering HBLUP (0.70 ± 0.01) and ALRNM (0.70 ± 0.01). Our results suggest that SNP marker information does not lead to higher prediction accuracies in reaction norm models. Furthermore, these accuracies decreased as the tick infestation level increased and as the relationship between animals in training and validation data sets decreased.
© 2016 American Society of Animal Science. All rights reserved. MenosABSTRACT.
Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold K-means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02)... Presentar Todo |
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Palabras claves : |
ACCURACY; CROSS-VALIDATION; GENETIC CORRELATION; HERITABILITY. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12162/1/mota2016.pdf
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Marc : |
LEADER 03053naa a2200277 a 4500
001 1059370
005 2019-02-06
008 2016 bl uuuu u00u1 u #d
022 $a0021-8812
024 7 $a10.2527/jas.2015-0194$2DOI
100 1 $aMOTA, R. R.
245 $aGenome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models.$h[electronic resource]
260 $c2016
500 $aArticle history: Received December 11, 2015. // Accepted March 10, 2016.
520 $aABSTRACT. Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold K-means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02), 0.67 (SE 0.02), and 0.66 (SE 0.02) for ABLUP, HBLUP, HLRNM, and ALRNM, respectively. For 5-fold random partitioning, HLRNM (0.71 ± 0.01) was statistically different from ABLUP (0.67 ± 0.01). However, no statistical significance was reported when considering HBLUP (0.70 ± 0.01) and ALRNM (0.70 ± 0.01). Our results suggest that SNP marker information does not lead to higher prediction accuracies in reaction norm models. Furthermore, these accuracies decreased as the tick infestation level increased and as the relationship between animals in training and validation data sets decreased. © 2016 American Society of Animal Science. All rights reserved.
653 $aACCURACY
653 $aCROSS-VALIDATION
653 $aGENETIC CORRELATION
653 $aHERITABILITY
700 1 $aLOPES, P. S.
700 1 $aTEMPELMAN, R. J.
700 1 $aSILVA, F. F.
700 1 $aAGUILAR, I.
700 1 $aGOMES, C. C. G.
700 1 $aCARDOSO, F. F.
773 $tJournal of Animal Science, May 2016, Volume 94, Issue 5, Pages 1834 - 1843.
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Registro original : |
INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
05/11/2014 |
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Actualizado : |
29/08/2017 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
CUITIÑO, M.J.; REBUFFO, M.; ALZUGARAY, R. |
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Afiliación : |
MARIA JOSE CUITIÑO DE VEGA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MONICA IRENE REBUFFO GFELLER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA DEL ROSARIO ALZUGARAY DUHALDE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Genetic diversity of Trifolium pratense L. for antixenosis to blue aphid (Acyrthosiphon kondoi Shinji). |
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Fecha de publicación : |
2010 |
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Fuente / Imprenta : |
In: INTERNATIONAL SYMPOSIUM ON THE MOLECULAR BREEDING OF FORAGE AND TURF, 6., 2010. Buenos Aires, AR: INTA, 2010. |
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Páginas : |
p. 116. |
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Idioma : |
Inglés |
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Palabras claves : |
ACYRTHOSIPHON KONDOI; ANTIXENOSIS; PULGÓN AZUL; RESISTENCIA GENÉTICA. |
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Thesagro : |
PULGONES; RESISTENCIA A LAS PLAGAS; TRÉBOL ROJO; TRIFOLIUM PRATENSE. |
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Asunto categoría : |
H10 Plagas de las plantas |
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Marc : |
LEADER 00769nam a2200229 a 4500
001 1051519
005 2017-08-29
008 2010 bl uuuu u01u1 u #d
100 1 $aCUITIÑO, M.J.
245 $aGenetic diversity of Trifolium pratense L. for antixenosis to blue aphid (Acyrthosiphon kondoi Shinji).$h[electronic resource]
260 $aIn: INTERNATIONAL SYMPOSIUM ON THE MOLECULAR BREEDING OF FORAGE AND TURF, 6., 2010. Buenos Aires, AR: INTA$c2010
300 $ap. 116.
650 $aPULGONES
650 $aRESISTENCIA A LAS PLAGAS
650 $aTRÉBOL ROJO
650 $aTRIFOLIUM PRATENSE
653 $aACYRTHOSIPHON KONDOI
653 $aANTIXENOSIS
653 $aPULGÓN AZUL
653 $aRESISTENCIA GENÉTICA
700 1 $aREBUFFO, M.
700 1 $aALZUGARAY, R.
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