A general statistical framework for unifying interval and linkage disequilibrium mapping: Toward high-resolution mapping of quantitative traits

The nonrandom association between different genes, termed linkage disequilibrium (LD), provides a powerful tool for high-resolution mapping of quantitative trait loci (QTL) underlying complex traits. This LD-based mapping approach can be made more efficient when it is coupled with interval mapping characterizing the genetic distance between markers and QTL. This article describes a general statistical framework for simultaneously estimating the linkage and LD that are related in a two-stage hierarchical sampling scheme. This framework is constructed within a maximum likelihood context and can be expanded to fine-scale mapping of complex traits for different population structures and reproductive behaviors. We provide a closed-form solution for joint estimation of quantitative genetic parameters describing QTL effects, QTL position and residual variances, and population genetic parameters describing allele frequencies and QTL-marker LD. We perform simulation studies to investigate the statistical properties of our joint analysis model for interval and LD mapping. An example using body weights of dogs from a multifamily outcrossed pedigree illustrates the use of the model.