Abstract
To compare the power of various QTL mapping methodologies, a dataset was simulated within the framework of 12th QTLMAS workshop. A total of 5865 diploid individuals was simulated, spanning seven generations, with known pedigree. Individuals were genotyped for 6000 SNPs across six chromosomes. We present an illustration of a Bayesian QTL linkage analysis, as implemented in the special purpose software FlexQTL. Most importantly, we treated the number of bi-allelic QTL as a random variable and used Bayes Factors to infer plausible QTL models. We investigated the power of our analysis in relation to the number of phenotyped individuals and SNPs. We report clear posterior evidence for 12 QTL that jointly explained 30% of the phenotypic variance, which was very close to the total of included simulation effects, when using all phenotypes and a set of 600 SNPs. Decreasing the number of phenotyped individuals from 4665 to 1665 and/or the number of SNPs in the analysis from 600 to 120 dramatically reduced the power to identify and locate QTL. Posterior estimates of genome-wide breeding values for a small set of individuals were given. We presented a successful Bayesian linkage analysis of a simulated dataset with a pedigree spanning several generations. Our analysis identified all regions that contained QTL with effects explaining more than one percent of the phenotypic variance. We showed how the results of a Bayesian QTL mapping can be used in genomic prediction.
Highlights
Introduction to quantitative geneticsHarlow, UK: Addison Wesley Longman; 1989.12
The common dataset [1] comprised a total of 5865 diploid individuals, spanning seven generations, with known pedigree
The generation number and sex of each individual were provided as non-genetic variables that might be included in the analyses
Summary
Introduction to quantitative geneticsHarlow, UK: Addison Wesley Longman; 1989.12. Kass RE, Raftery AE: Bayes Factors. To compare the power of various QTL mapping methodologies, a dataset was simulated within the framework of 12th QTLMAS workshop. A total of 5865 diploid individuals was simulated, spanning seven generations, with known pedigree. We present an illustration of a Bayesian QTL linkage analysis, as implemented in the special purpose software FlexQTL. We investigated the power of our analysis in relation to the number of phenotyped individuals and SNPs. The 12th QTLMAS workshop included a section that focussed on discussions about analyses of a simulated data set. The common dataset [1] comprised a total of 5865 diploid individuals, spanning seven generations, with known pedigree. The dataset was simulated to allow the first four generations to be used for QTL detection (by association, linkage or combinations thereof). The objective of our contribution is to present the results of a Bayesian analysis fitting multiple QTL simultaneously by exploiting linkage information
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