Quantitative trait locus mapping methods for diversity outbred mice

Abstract

Genetic mapping studies in the mouse and other model organisms are used to search for genes underlying complex phenotypes. Traditional genetic mapping studies that employ single-generation crosses have poor mapping resolution and limit discovery to loci that are polymorphic between the two parental strains. Multiparent outbreeding populations address these shortcomings by increasing the density of recombination events and introducing allelic variants from multiple founder strains. However, multiparent crosses present new analytical challenges and require specialized software to take full advantage of these benefits. Each animal in an outbreeding population is genetically unique and must be genotyped using a high-density marker set; regression models for mapping must accommodate multiple founder alleles, and complex breeding designs give rise to polygenic covariance among related animals that must be accounted for in mapping analysis. The Diversity Outbred (DO) mice combine the genetic diversity of eight founder strains in a multigenerational breeding design that has been maintained for >16 generations. The large population size and randomized mating ensure the long-term genetic stability of this population. We present a complete analytical pipeline for genetic mapping in DO mice, including algorithms for probabilistic reconstruction of founder haplotypes from genotyping array intensity data, and mapping methods that accommodate multiple founder haplotypes and account for relatedness among animals. Power analysis suggests that studies with as few as 200 DO mice can detect loci with large effects, but loci that account for <5% of trait variance may require a sample size of up to 1000 animals. The methods described here are implemented in the freely available R package DOQTL.

Keywords: MPP; Multiparent Advanced Generation Inter-Cross (MAGIC); Multiparental populations; diversity outbred; haplotype reconstruction; quantitative trait locus mapping.

Figure 1

X and Y probe intensities on the MUGA contain information about founder haplotypes that is not captured by the four genotype allele calls. Each point represents the X and Y intensity values for one sample at marker UNC190139327, chromosome 19, 5.083353 Mb (rs46230775). Locations of the founder strains, including multiple independent samples of founder and F1 hybrids animals, are shown as colored circles. Founder strains are represented as colored circles and F1 hybrids are represented by a circle in one founder color and an internal triangle in the other founder color. For example, the eight red points in cluster 3 represent replicates of the PWK/PhJ founder. (A) Cluster 1 represents homozygotes and heterozygotes between A/J, CAST/EiJ, NOD/ShiLtJ, and WSB/EiJ. Cluster 2 represents heterozygotes between the founders in cluster 1 and PWK/PhJ. Cluster 3 represents PWK/PhJ homozygotes. Cluster 4 contains heterozygotes between the founders in clusters 1 and 6. Cluster 5 represents homozygotes and heterozygotes between PWK/PhJ and the strains in cluster 6. Cluster 6 consists of homozygotes and heterozygotes between 129S1/SvImJ, C57BL/6J, and NZO/HlLtJ. (B) The X and Y intensities from A have been transformed to ρ and θ coordinates and the cluster axes are aligned vertically. (C) Initial 36 diplotype state cluster locations that are estimated using mclust from the sample and founder data. Many diplotype states have the same cluster center. (D) Final diplotype state locations after the genotyping algorithm has completed.

Figure 2

(A) Founder allele proportions across samples and markers. Horizontal axis shows the proportion of alleles from each founder across all samples. Boxes show median and interquartile range. Dotted line is 1/8. (B) Diplotype state proportions across all samples. Diplotypes on vertical axis are given in two-letter codes shown in legend. Dotted lines at 1/32 and 1/64. (C) Founder allele proportions across markers. Dashed line is a 1/8. (D) Diplotype state across markers.

Figure 3

(A) Estimated number of autosomal recombinations per sample run on the MUGA plotted by generation using the marker allele calls (□) or the genotyping array intensities (○). Solid lines are the least-squares fit for each method. Dashed line is the expected theoretical number of recombinations. Numbers are the slopes of each line. Boxes show median plus interquartile range. (B) The same plot as in A, but with samples run on the MegaMUGA. Top and bottom numbers are the slope of the intensity- and allele-call-based reconstructions, respectively. (C) Histogram of recombination block size using the MUGA (C) and MegaMUGA (D). The inset shows the region from 0 to 10 Mb. Red curves are the maximum-likelihood fit of the data to an exponential distribution.

Figure 4

Power simulations demonstrate the relationship between power, sample size, and percentage variance explained. The percentage variance explained by the simulated QTL is plotted vs. the power to detect the simulated QTL for five different sample sizes. Points are the mean value from 1000 simulations and curves are logistic regression models fit to the data.

Figure 5

Mapping of constitutive neutrophil counts. (A) Genome scan of constitutive neutrophil counts using the full model does not show any significant peaks. The horizontal axis shows the mouse genome. The vertical axis plots the LOD score at each locus. Red line is p ≤ 0.05 significance threshold. (B) Linkage mapping of neutrophil counts using the additive haplotype model reveals a large peak on chromosome 1. (C) Association mapping of neutrophil counts using the additive SNP model produces a plot similar to linkage mapping. Vertical axis shows LOD score. Red line is p ≤ 0.05 significance threshold. (D) Founder coefficients from the linkage model on chromosome 1 show the effects of each founder allele. The founder coefficients are centered around zero. Bottom shows the LOD score with support interval shaded light blue. (E) Zoomed view of QTL support interval highlights two genes (GRC Build 38 coordinates). Top shows the LOD score for the additive SNP model with the red line denoting the P ≤ 0.05 significance threshold.