Interval mapping by simple regression is a powerful method for the detection of quantitative trait
loci (QTLs) in line crosses such as F2 populations. Due to the ease of computation of the
regression approach, relatively complex models with multiple fixed effects, interactions between
QTLs or between QTLs and fixed effects can easily be accommodated. However, polygenic effects,
which are not targeted in QTL analysis, cannot be treated as random effects in a least squares
analysis. In a cross between true inbred lines this is of no consequence, as the polygenic effect
contributes just to the residual variance. In a cross between outbred lines, however, if a trait has
high polygenic heritability, the additive polygenic effect has a large influence on variation in the
population. Here we extend the fixed model for the regression interval mapping method to a mixed
model using an animal model. This makes it possible to use not only the observations from
progeny (e.g. F2), but also those from the parents (F1) to evaluate QTLs and polygenic effects. We
show how the animal model using parental observations can be applied to an outbred cross and so
increase the power and accuracy of QTL analysis. Three estimation methods, i.e. regression and an
animal model either with or without parental observations, are applied to simulated data. The
animal model using parental observations is shown to have advantages in estimating QTL position
and additive genotypic value, especially when the polygenic heritability is large and the number of
progeny per parent is small.
A mixed model QTL analysis for sugarcane multiple-harvest-location trial data
