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

Xiang Yang Lou, George Casella, Rory J. Todhunter, Mark C.K. Yang, Rongling Wu

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)158-171
Number of pages14
JournalJournal of the American Statistical Association
Volume100
Issue number469
DOIs
StatePublished - Mar 1 2005

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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