Detection of quantitative trait loci in outbred populations with incomplete marker data

M.C.A.M. Bink, J.A.M. van Arendonk

Research output: Contribution to journalArticleAcademicpeer-review

19 Citations (Scopus)

Abstract

Augmentation of marker genotypes for ungenotyped individuals is implemented in a Bayesian approach via the use of Markov chain Monte Carlo techniques. Marker data on relatives and phenotypes are combined to compute conditional posterior probabilities for marker genotypes of ungenotyped individuals. The presented procedure allows the analysis of complex pedigrees with ungenotyped individuals to detect segregating quantitative trait loci (QTL). Allelic effects at the QTL were assumed to follow a normal distribution with a covariance matrix based on known QTL position and identity by descent probabilities derived from flanking markers. The Bayesian approach estimates variance due to the single QTL, together with polygenic and residual variance. The method was empirically tested through analyzing simulated data from a complex granddaughter design. Ungenotyped dams were related to one or more sons or grandsires in the design. Heterozygosity of the marker loci and size of QTL were varied. Simulation results indicated a significant increase in power when ungenotyped dams were included in the analysis.
Original languageEnglish
Pages (from-to)409-420
JournalGenetics
Volume151
Publication statusPublished - 1999

Fingerprint Dive into the research topics of 'Detection of quantitative trait loci in outbred populations with incomplete marker data'. Together they form a unique fingerprint.

Cite this