Genome reshuffling for Advanced Intercross Permutation (GRAIP) : Simulation and Permutation for advanced intercross population analysis

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Abstract

Background: Advanced intercross lines (AIL) are segregating populations created using a multi-generation breeding protocol for fine mappping complex trait loci (QTL) in mice and other organisms. Applying QTL mapping methods for intercross and backcross populations, often followed by naïve permutation of individuals and phenotypes, does not account for the effect of AIL family structure in which final generations have been expanded and leads to inapropriately low significance thresholds. The critical problem with naïave mapping approaches in AIL populations is that the individual is not an exchangeable unit. Methodology/Principal Findings: The effect of family structure has immediate implications for the optimal AIL creation (many crosses, few animals per cross, and population expansion before the final generation) and we discuss these and the utility of AIL populations for QTL fine mapping. We also dexcribe Genome Reshuffling for Advanced Intercross Permutation, (GRAIP) a method for analyzing AIL data that accounts for family structure. GRAIP permutes a more interchangeable unit in the final generaation crosses - the parental genome - and simulating regeneration of a permuted AIL population based on exchanged parental identities. GRAIP determines appropriate genome-wide significance thesholds and locus specific P-values for AILs and other populations with similar family structures. We contrast GRAIP with naïve permuatation using a large densely genotyped mouse AIL population (1333 individuals from 32 crosses) A naïve permutation using coat color as a corrected using GRAIP. GRAIP also detects an established hippocampus weight locus and a new locus, Hipp90. Conclusions and Significance: GRAIP determines appropriate genome-wide significance thresholds and locus specific P-values for AILs and other populations with similar family structures. The effect of family structure has immediate implications for the optimal AIL creation and the utility of AIL populations. © 2008 Peirce et al.

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Peirce, J. L., Broman, K. W., Lu, L., Chesler, E. J., Zhou, G., Airey, D. C., … Williams, R. W. (2008). Genome reshuffling for Advanced Intercross Permutation (GRAIP) : Simulation and Permutation for advanced intercross population analysis. PLoS ONE, 3(4). https://doi.org/10.1371/journal.pone.0001977

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