Quantitative trait locus analysis using recombinant inbred intercrosses: Theoretical and empirical considerations

Fei Zou, Jonathan A.L. Gelfond, David C. Airey, Lu Lu, Kenneth F. Manly, Robert W. Williams, David W. Threadgill

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

Abstract

We describe a new approach, called recombinant inbred intercross (RIX) mapping, that extends the power of recombinant inbred (RJ) lines to provide sensitive detection of quantitative trait loci (QTL) responsible for complex genetic and nongenetic interactions. RIXs are generated by producing F 1 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.

Original languageEnglish (US)
Pages (from-to)1299-1311
Number of pages13
JournalGenetics
Volume170
Issue number3
DOIs
StatePublished - Jul 2005
Externally publishedYes

ASJC Scopus subject areas

  • General Medicine

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