Rodent inbred line crosses are widely used to map genetic loci associated with complex traits. This approach has proven to be powerful for detecting quantitative trait loci (QTL); however, the resolution of QTL locations, typically similar to 20 cM, means that hundreds of genes are implicated as potential candidates. We describe analytical methods based on linear models to combine information available in two or more inbred line crosses. Our strategy is motivated by the hypothesis that common inbred strains of the laboratory mouse are derived from a limited ancestral gene pool and thus QTL detected in multiple crosses are likely to represent shared ancestral polymorph isms. We demonstrate that the combined-cross analysis can improve the power to detect weak QTL, can narrow support intervals for QTL regions, and can be used to separate multiple QTL that colocalize by chance. Moreover, combined-cross analysis can establish the allelic states of a QTL among a set of parental lines, thus providing critical information for narrowing QTL regions by haplotype analysis.
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Univ Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USAUniv Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USA
Yi, N.
Shriner, D.
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Univ Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USAUniv Alabama Birmingham, Dept Biostat, Sect Stat Genet, Birmingham, AL 35294 USA
机构:
Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
Wuhan Univ, Sch Math & Stat, Wuhan 430072, Hubei, Peoples R ChinaUniv N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
Yuan, Zhongshang
Zou, Fei
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Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
Univ N Carolina, Carolina Ctr Genome Sci, Chapel Hill, NC 27599 USAUniv N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
Zou, Fei
Liu, Yanyan
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Wuhan Univ, Sch Math & Stat, Wuhan 430072, Hubei, Peoples R ChinaUniv N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA