Statistical Power to Detect QTL Peaks in Genetic Modifier Crosses

Justine Chu

Document Type

Article

Publication Date

2025

Keywords

JMG

Abstract

Monogenic diseases often display broad variation in age of onset and severity. This variation may be due to environmental or genetic factors. The genetic causes of this variation can be identified using a “modifier screen”, in which mice carrying a dominant disease-causing gene are crossed with genetically diverse mice. Genetic diversity can be introduced through recombinant inbred lines, such as the BXD or Collaborative Cross (CC), or outcross mice, such as the Diversity Outbred (DO) to create an F1 mouse population in which investigators perform quantitative trait locus (QTL) mapping. We ran QTL mapping simulations with varying heritability, effect size, and sample size in BXD, CC, DO, BXD-F1, CC-F1, and DO-F1 mouse populations to determine the power and precision to detect QTL peaks in these populations. We found that the power in the F1 populations is half that of the power in the corresponding parent populations. We also found that the support interval was larger in the F1 and that the QTL position was more variable in the F1. Modifier mapping studies require more mice than mapping studies with the parent populations, and the findings in this study can assist investigators in determining the necessary sample size.

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