Source:http://linkedlifedata.com/resource/pubmed/id/19589189
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
3
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| pubmed:dateCreated |
2009-7-10
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| pubmed:abstractText |
In self-pollinating populations, individuals are characterized by a high degree of inbreeding. Additionally, phenotypic observations are highly influenced by genotype-by-environment interaction effects. Usually, Bayesian approaches to predict breeding values (in self-pollinating crops) omit genotype-by-environment interactions in the statistical model, which may result in biased estimates. In our study, a Bayesian Gibbs sampling algorithm was developed that is adapted to the high degree of inbreeding in self-pollinated crops and accounts for interaction effects between genotype and environment. As related lines are supposed to show similar genotype-by-environment interaction effects, an extended genetic relationship matrix is included in the Bayesian model. Additionally, since the coefficient matrix C in the mixed model equations can be characterized by rank deficiencies, the pseudoinverse of C was calculated by using the nullspace, which resulted in a faster computation time. In this study, field data of spring barley lines and data of a 'virtual' parental population of self-pollinating crops, generated by computer simulation, were used. For comparison, additional breeding values were predicted by a frequentist approach. In general, standard Bayesian Gibbs sampling and a frequentist approach resulted in similar estimates if heritability of the regarded trait was high. For low heritable traits, the modified Bayesian model, accounting for relatedness between lines in genotype-by-environment interaction, was superior to the standard model.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
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| pubmed:month |
Jun
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| pubmed:issn |
1469-5073
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| pubmed:author | |
| pubmed:issnType |
Electronic
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| pubmed:volume |
91
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
193-207
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| pubmed:dateRevised |
2010-12-28
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| pubmed:meshHeading |
pubmed-meshheading:19589189-Bayes Theorem,
pubmed-meshheading:19589189-Breeding,
pubmed-meshheading:19589189-Computer Simulation,
pubmed-meshheading:19589189-Crops, Agricultural,
pubmed-meshheading:19589189-Environment,
pubmed-meshheading:19589189-Genotype,
pubmed-meshheading:19589189-Inbreeding,
pubmed-meshheading:19589189-Models, Genetic,
pubmed-meshheading:19589189-Models, Statistical,
pubmed-meshheading:19589189-Pollination
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| pubmed:year |
2009
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| pubmed:articleTitle |
Bayesian prediction of breeding values by accounting for genotype-by-environment interaction in self-pollinating crops.
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| pubmed:affiliation |
Institute of Crop Science and Resource Conservation, University of Bonn, D-53115 Bonn, Germany. a.bauer@uni-bonn.de
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| pubmed:publicationType |
Journal Article
|