Comparision of analysis of the QTLMAS XII common dataset: I: Genomic selection

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A dataset was simulated and distributed to participants of the QTLMAS XII workshop who were invited to develop genomic selection models. Each contributing group was asked to describe the model development and validation as well as to submit genomic predictions for three generations of individuals, for which they only knew the genotypes. The organisers used these genomic predictions to perform the final validation by comparison to the true breeding values, which were known only to the organisers. Methods used by the 5 groups fell in 3 classes 1) fixed effects models 2) BLUP models, and 3) Bayesian MCMC based models. The Bayesian analyses gave the highest accuracies, followed by the BLUP models, while the fixed effects models generally had low accuracies and large error variance. The best BLUP models as well as the best Bayesian models gave unbiased predictions. The BLUP models are clearly sensitive to the assumed SNP variance, because they do not estimate SNP variance, but take the specified variance as the true variance. The current comparison suggests that Bayesian analyses on haplotypes or SNPs are the most promising approach for Genomic selection although the BLUP models may provide a computationally attractive alternative with little loss of efficiency. On the other hand fixed effect type models are unlikely to provide any gain over traditional pedigree indexes for selection
OriginalsprogEngelsk
TidsskriftBMC Proceedings
NummerSuppl 1
Antal sider8
ISSN1753-6561
StatusUdgivet - 2009
BegivenhedEuropean workshop on QTL mapping and marker assisted selection - Uppsala, Sverige
Varighed: 15 maj 200816 maj 2008
Konferencens nummer: 12th

Konference

KonferenceEuropean workshop on QTL mapping and marker assisted selection
Nummer12th
LandSverige
ByUppsala
Periode15/05/200816/05/2008

Bibliografisk note

Udgivelsesdato: 23. February
Volumne: 3

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