A General Monte Carlo Method for Mapping Multiple Quantitative Trait Loci

AUTOR(ES)

Jansen, R. C.

RESUMO

In this paper we address the mapping of multiple quantitative trait loci (QTLs) in line crosses for which the genetic data are highly incomplete. Such complicated situations occur, for instance, when dominant markers are used or when unequally informative markers are used in experiments with outbred populations. We describe a general and flexible Monte Carlo expectation-maximization (Monte Carlo EM) algorithm for fitting multiple-QTL models to such data. Implementation of this algorithm is straightforward in standard statistical software, but computation may take much time. The method may be generalized to cope with more complex models for animal and human pedigrees. A practical example is presented, where a three-QTL model is adopted in an outbreeding situation with dominant markers. The example is concerned with the linkage between randomly amplified polymorphic DNA (RAPD) markers and QTLs for partial resistance to Fusarium oxysporum in lily.

Documentos Relacionados

• Mapping-Linked Quantitative Trait Loci Using Bayesian Analysis and Markov Chain Monte Carlo Algorithms
• A Powerful and Robust Method for Mapping Quantitative Trait Loci in General Pedigrees
• Multiple Trait Analysis of Genetic Mapping for Quantitative Trait Loci
• The Use of Multiple Markers in a Bayesian Method for Mapping Quantitative Trait Loci
• Interval Mapping of Multiple Quantitative Trait Loci