Abstract
BackgroundGenetic mapping has proven to be powerful for studying the genetic architecture of complex traits by characterizing a network of the underlying interacting quantitative trait loci (QTLs). Current statistical models for genetic mapping were mostly founded on the biallelic epistasis of QTLs, incapable of analyzing multiallelic QTLs and their interactions that are widespread in an outcrossing population.ResultsHere we have formulated a general framework to model and define the epistasis between multiallelic QTLs. Based on this framework, we have derived a statistical algorithm for the estimation and test of multiallelic epistasis between different QTLs in a full-sib family of outcrossing species. We used this algorithm to genomewide scan for the distribution of mul-tiallelic epistasis for a rooting ability trait in an outbred cross derived from two heterozygous poplar trees. The results from simulation studies indicate that the positions and effects of multiallelic QTLs can well be estimated with a modest sample and heritability.ConclusionsThe model and algorithm developed provide a useful tool for better characterizing the genetic control of complex traits in a heterozygous family derived from outcrossing species, such as forest trees, and thus fill a gap that occurs in genetic mapping of this group of important but underrepresented species.
Highlights
Genetic mapping has proven to be powerful for studying the genetic architecture of complex traits by characterizing a network of the underlying interacting quantitative trait loci (QTLs)
A Worked Example We use a real example of a forest tree to illustrate our multiallelic epistiatic quantitative trait locus (QTL) mapping method in an outbred population
A total of 86 individuals were selected for QTL mapping
Summary
Genetic mapping has proven to be powerful for studying the genetic architecture of complex traits by characterizing a network of the underlying interacting quantitative trait loci (QTLs). There is a group of species of great economical and environmental importance - out-crossing species, such as forest trees, in which traditional QTL mapping approaches cannot be appropriately used. For these species, it is difficult or impossible to generate inbred lines due to long generation intervals and high heterozygosity [4], . Grattapaglia and Sederoff [7] proposed a socalled pseudo-test backcross strategy for linkage mapping in a controlled cross between two outbred parents. Stam [11] wrote powerful software for integrating genetic linkage maps using different types of markers
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