TY - JOUR
T1 - A general statistical framework for unifying interval and linkage disequilibrium mapping
T2 - Toward high-resolution mapping of quantitative traits
AU - Lou, Xiang Yang
AU - Casella, George
AU - Todhunter, Rory J.
AU - Yang, Mark C.K.
AU - Wu, Rongling
N1 - Funding Information:
Xiang-Yang Lou is Postdoctoral Research Associate, under the guidance of Dr. Rongling Wu, and George Casella is Distinguished Professor and Chair, Department of Statistics, University of Florida, Gainesville, FL 32611. Rory J. Todhunter is Associate Professor, The James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853. Mark Yang is Professor, Department of Statistics, University of Florida, Gainesville, FL 32611. Rongling Wu is Associate Professor, Department of Statistics, University of Florida, Gainesville, FL 32611 (E-mail: [email protected]) and Adjunct Distinguished Professor, Zhejiang Forestry University, Lin’An, Zhejiang 311300, China. Rongling Wu conceived the idea of this study, wrote this manuscript, and was responsible for directing the research. The authors thank the associate editor and an anonymous referee for their constructive comments on this manuscript. This work is supported in part by a National Science Foundation grant (9971586) to G. Casella; an Outstanding Young Investigators Award of the National Science Foundation of China (30128017), a University of Florida Research Opportunity Fund (02050259); and a University of South Florida Biodefense grant (7222061-12) to R. Wu; and the Morris Animal Foundation contract grant (722206212) to R. J. Todhunter. The publication of this manuscript is approved as journal series No. R-09584 by the Florida Agricultural Experiment Station.
PY - 2005/3
Y1 - 2005/3
N2 - 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.
AB - 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.
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U2 - 10.1198/016214504000001295
DO - 10.1198/016214504000001295
M3 - Article
AN - SCOPUS:14944380898
SN - 0162-1459
VL - 100
SP - 158
EP - 171
JO - Journal of the American Statistical Association
JF - Journal of the American Statistical Association
IS - 469
ER -