A Flexible Bayesian framework for multiple QTL mapping in pedigreed populations

Plant breeders and geneticists have been using statistical methods to identify Quantitative Trait Loci (QTL) that affect traits showing continuous variation. These methods have been directed mainly at populations derived from pure lines. When considering single populations derived from pure lines, the success of QTL experiments may be hampered dramatically if markers and/or QTL do not segregate. Moreover, identified QTL may not be relevant for the plant material used in ongoing breeding programs. Here, we will present a new software package, FlexQTLTM: a Bayesian statistical framework for mapping QTL in pedigreed populations. This package can be used to identify QTL using populations that are developed in ongoing breeding programs. The Bayesian approach provides clear visual presentations of the statistical aspects of all parameters relevant to QTL analysis. The flexibility of FlexQTLTM with respect to pedigree structures, inbred or outbred, as well as QTL models will be illustrated.