qtl2pleio

qtl2pleio distinguishes pleiotropy from separate quantitative trait loci (QTL) in multiparental populations to elucidate the genetic architecture of complex traits measured by high-throughput phenotyping.

Key Features:

• Pleiotropy vs. Separate QTL Testing: Extends the Jiang and Zeng (1995) pleiotropy test to scenarios involving more than two alleles.
• Polygenic Random Effects: Incorporates polygenic random effects to account for population structure in mixed-model analyses.
• Statistical Significance via Parametric Bootstrap: Employs a parametric bootstrap approach to determine significance of pleiotropy versus separate QTL hypotheses.
• Application to Behavioral Genetics Data: Applied to behavioral genetics data sets from Diversity Outbred mice to evaluate pleiotropic relationships.

Scientific Applications:

• Discrimination of Genetic Effects: Distinguishes whether a single locus affects multiple traits (pleiotropy) or distinct loci underlie correlated traits.
• Analysis of Multiparental Populations: Used to analyze complex genetic architectures in multiparental populations with high mapping resolution.
• Informing Experimental Follow-up: Provides evidence to guide targeted gene editing and breeding program decisions based on pleiotropic relationships.
• Behavioral Genetics Studies: Supports interpretation of trait relationships in Diversity Outbred mouse behavioral datasets.

Methodology:

Extends the Jiang and Zeng (1995) pleiotropy test to multiple alleles, fits mixed models with polygenic random effects to account for population structure, and uses a parametric bootstrap to assess statistical significance.