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G3 (Bethesda). 2019 Jul 9;9(7):2317-2324. doi: 10.1534/g3.119.400098.

Testing Pleiotropy vs. Separate QTL in Multiparental Populations.

Author information

1
The Jackson Laboratory, Bar Harbor, Maine 04609.
2
Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin 53706.
3
Department of Horticulture, University of Wisconsin-Madison, Madison, Wisconsin 53706.
4
Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53706 broman@wisc.edu.

Abstract

The high mapping resolution of multiparental populations, combined with technology to measure tens of thousands of phenotypes, 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.

KEYWORDS:

MPP; Multiparent Advanced Generation Inter-Cross (MAGIC); Quantitative trait locus; linear mixed effects models; multiparental populations; multivariate analysis; pleiotropy; systems genetics

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