Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model

<p>Abstract</p> <p>Background</p> <p>Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with dif...

Full description

Bibliographic Details
Main Authors: Fernando Rohan, Habier David, Preisinger Rudolf, O'Sullivan Neil P, Fulton Janet E, Settar Petek, Arango Jesus, Stricker Chris, Wolc Anna, Garrick Dorian J, Lamont Susan J, Dekkers Jack CM
Format: Article
Language:deu
Published: BMC 2011-01-01
Series:Genetics Selection Evolution
Online Access:http://www.gsejournal.org/content/43/1/5
id doaj-f4912dc69bd44dc3bc7f716e934fa1b7
record_format Article
spelling doaj-f4912dc69bd44dc3bc7f716e934fa1b72020-11-25T01:41:57ZdeuBMCGenetics Selection Evolution0999-193X1297-96862011-01-01431510.1186/1297-9686-43-5Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal modelFernando RohanHabier DavidPreisinger RudolfO'Sullivan Neil PFulton Janet ESettar PetekArango JesusStricker ChrisWolc AnnaGarrick Dorian JLamont Susan JDekkers Jack CM<p>Abstract</p> <p>Background</p> <p>Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.</p> <p>Methods</p> <p>The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).</p> <p>The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.</p> <p>Results</p> <p>Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.</p> http://www.gsejournal.org/content/43/1/5
collection DOAJ
language deu
format Article
sources DOAJ
author Fernando Rohan
Habier David
Preisinger Rudolf
O'Sullivan Neil P
Fulton Janet E
Settar Petek
Arango Jesus
Stricker Chris
Wolc Anna
Garrick Dorian J
Lamont Susan J
Dekkers Jack CM
spellingShingle Fernando Rohan
Habier David
Preisinger Rudolf
O'Sullivan Neil P
Fulton Janet E
Settar Petek
Arango Jesus
Stricker Chris
Wolc Anna
Garrick Dorian J
Lamont Susan J
Dekkers Jack CM
Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
Genetics Selection Evolution
author_facet Fernando Rohan
Habier David
Preisinger Rudolf
O'Sullivan Neil P
Fulton Janet E
Settar Petek
Arango Jesus
Stricker Chris
Wolc Anna
Garrick Dorian J
Lamont Susan J
Dekkers Jack CM
author_sort Fernando Rohan
title Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
title_short Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
title_full Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
title_fullStr Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
title_full_unstemmed Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
title_sort breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model
publisher BMC
series Genetics Selection Evolution
issn 0999-193X
1297-9686
publishDate 2011-01-01
description <p>Abstract</p> <p>Background</p> <p>Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.</p> <p>Methods</p> <p>The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).</p> <p>The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.</p> <p>Results</p> <p>Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.</p>
url http://www.gsejournal.org/content/43/1/5
work_keys_str_mv AT fernandorohan breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT habierdavid breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT preisingerrudolf breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT osullivanneilp breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT fultonjanete breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT settarpetek breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT arangojesus breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT strickerchris breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT wolcanna breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT garrickdorianj breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT lamontsusanj breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
AT dekkersjackcm breedingvaluepredictionforproductiontraitsinlayerchickensusingpedigreeorgenomicrelationshipsinareducedanimalmodel
_version_ 1725038661798461440