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G3 (Bethesda). 2019 May 15. pii: g3.400098.2019. doi: 10.1534/g3.119.400098. [Epub ahead of print]

Testing Pleiotropy vs. Separate QTL in Multiparental Populations.

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University of Wisconsin-Madison.
The Jackson Laboratory.
University of Wisconsin-Madison


The high mapping resolution of multiparental populations, combined with technology to measure tens of thousands of pheno-types, presents a need for quantitative methods to enhance understanding of the genetic architecture of complex traits. When multiple traits map to a common genomic region, knowledge of the number of distinct loci provides important insight into the underlying mechanism and can assist planning for subsequent experiments. We extend the method of Jiang and Zeng (1995), for testing pleiotropy with a pair of traits, to the case of more than two alleles. We also incorporate polygenic random effects to account for population structure. We use a parametric bootstrap to determine statistical significance. We apply our methods to a behavioral genetics data set from Diversity Outbred mice. Our methods have been incorporated into the R package qtl2pleio.


Quantitative trait locus; linear mixed effects models; multivariate analysis; pleiotropy; systems genetics

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