| |
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha : |
15/11/2015 |
|
Actualizado : |
09/10/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
FRAGOMENI, B.O.; MISZTAL, I.; LOURENCO, D.L.; AGUILAR, I.; OKIMOTO, R.; MUIR, W.M. |
|
Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
|
Título : |
Changes in variance explained by top SNP windows over generations for three traits in broiler chicken |
|
Fecha de publicación : |
2014 |
|
Fuente / Imprenta : |
Frontiers in Genetics, 2014, v.5, no.Oct., Article number 332. OPEN ACCESS. |
|
ISSN : |
1664-8021 |
|
DOI : |
10.3389/fgene.2014.00332 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Published 01 October 2014. |
|
Contenido : |
ABSTRACT.
The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.
© 2014 Fragomeni, Misztal, Lourenco, Aguilar, Okimoto and Muir. MenosABSTRACT.
The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.
© 2014 Fragomeni, Misztal, Lourenco, Aguilar, Okimoto and... Presentar Todo |
|
Palabras claves : |
Gene identification; Genome-wide association study; Genomic selection; QTL; SsGBLUP. |
|
Thesagro : |
MEJORAMIENTO GENETICO ANIMAL; POLLO DE ENGORDE. |
|
Asunto categoría : |
L10 Genética y mejoramiento animal |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5195/1/Aguilar-I.-2014.-Frontiers-in-Genetics.pdf
|
|
Marc : |
LEADER 02443naa a2200301 a 4500
001 1053891
005 2019-10-09
008 2014 bl uuuu u00u1 u #d
022 $a1664-8021
024 7 $a10.3389/fgene.2014.00332$2DOI
100 1 $aFRAGOMENI, B.O.
245 $aChanges in variance explained by top SNP windows over generations for three traits in broiler chicken$h[electronic resource]
260 $c2014
500 $aArticle history: Published 01 October 2014.
520 $aABSTRACT. The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated. © 2014 Fragomeni, Misztal, Lourenco, Aguilar, Okimoto and Muir.
650 $aMEJORAMIENTO GENETICO ANIMAL
650 $aPOLLO DE ENGORDE
653 $aGene identification
653 $aGenome-wide association study
653 $aGenomic selection
653 $aQTL
653 $aSsGBLUP
700 1 $aMISZTAL, I.
700 1 $aLOURENCO, D.L.
700 1 $aAGUILAR, I.
700 1 $aOKIMOTO, R.
700 1 $aMUIR, W.M.
773 $tFrontiers in Genetics, 2014$gv.5, no.Oct., Article number 332. OPEN ACCESS.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Tacuarembó. |
|
Fecha actual : |
21/02/2014 |
|
Actualizado : |
17/08/2018 |
|
Autor : |
BIANCHI, G. |
|
Afiliación : |
GIANNI BIANCHI. |
|
Título : |
Cómo enfrentar uno de los problemas más importantes en la faena de ovinos: la contaminación de las canales. |
|
Fecha de publicación : |
2010 |
|
Fuente / Imprenta : |
El País Agropecuario, 2010, v. 16, no. 188, p. 28-30. |
|
Idioma : |
Español |
|
Contenido : |
El problema. ¿Qué se ha realizado en Uruguay?. ¿Qué se puede hacer con la información local disponible hasta el momento? |
|
Palabras claves : |
CONTAMINACIÓN DE LA CANAL. |
|
Thesagro : |
CANAL ANIMAL; OVINOS; TRANSPORTE DE ANIMALES. |
|
Asunto categoría : |
L01 Ganadería |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/11025/1/188p28.pdf
|
|
Marc : |
LEADER 00645naa a2200169 a 4500
001 1028639
005 2018-08-17
008 2010 bl uuuu u00u1 u #d
100 1 $aBIANCHI, G.
245 $aCómo enfrentar uno de los problemas más importantes en la faena de ovinos$bla contaminación de las canales.
260 $c2010
520 $aEl problema. ¿Qué se ha realizado en Uruguay?. ¿Qué se puede hacer con la información local disponible hasta el momento?
650 $aCANAL ANIMAL
650 $aOVINOS
650 $aTRANSPORTE DE ANIMALES
653 $aCONTAMINACIÓN DE LA CANAL
773 $tEl País Agropecuario, 2010$gv. 16, no. 188, p. 28-30.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Tacuarembó (TBO) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
