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Originally published as Genetics Published Articles Ahead of Print on May 6, 2005.
Genetics, Vol. 170, 1299-1311, July 2005, Copyright © 2005
doi:10.1534/genetics.104.035709
Quantitative Trait Locus Analysis Using Recombinant Inbred Intercrosses
Theoretical and Empirical Considerations
Fei Zou*,
Jonathan A. L. Gelfond*,
David C. Airey
,
,1,
Lu Lu,,
Kenneth F. Manly,
,
Robert W. Williams, and
David W. Threadgill**,2
* Department of Biostatistics, Lineberger Comprehensive Cancer Center and Center for Environmental Health and Susceptibility, University of North Carolina, Chapel Hill, North Carolina 27599
** Department of Genetics and the Carolina Center for Genome Sciences, Lineberger Comprehensive Cancer Center and Center for Environmental Health and Susceptibility, University of North Carolina, Chapel Hill, North Carolina 27599
Center for Genomics and Bioinformatics, University of Tennessee, Memphis, Tennessee 38163
Department of Anatomy and Neuroscience, University of Tennessee, Memphis, Tennessee 38163
Department of Pathology, University of Tennessee, Memphis, Tennessee 38163
2 Corresponding author: Department of Genetics, CB 7264, University of North Carolina, Chapel Hill, NC 27599.
E-mail: dwt{at}med.unc.edu
We describe a new approach, called recombinant inbred intercross (RIX) mapping, that extends the power of recombinant inbred (RI) lines to provide sensitive detection of quantitative trait loci (QTL) responsible for complex genetic and nongenetic interactions. RIXs are generated by producing F1 hybrids between all or a subset of parental RI lines. By dramatically extending the number of unique, reproducible genomes, RIXs share some of the best properties of both the parental RI and F2 mapping panels. These attributes make the RIX method ideally suited for experiments requiring analysis of multiple parameters, under different environmental conditions and/or temporal sampling. However, since any pair of RIX genomes shares either one or no parental RIs, this cross introduces an unusual population structure requiring special computational approaches for analysis. Herein, we propose an efficient statistical procedure for QTL mapping with RIXs and describe a novel empirical permutation procedure to assess genome-wide significance. This procedure will also be applicable to diallel crosses. Extensive simulations using strain distribution patterns from CXB, AXB/BXA, and BXD mouse RI lines show the theoretical power of the RIX approach and the analysis of CXB RIXs demonstrates the limitations of this procedure when using small RI panels.
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