  Studies of the genetic loci that contribute to variation in gene expression
frequently identify loci with broad effect on gene expression: expression
quantitative trait locus (eQTL) hotspots. We describe a set of exploratory
graphical methods as well as a formal likelihood-based test for assessing
whether a given hotspot is due to one or multiple polymorphisms. We first look
at the pattern of effects of the locus on the expression traits that map to the
locus: the direction of the effects, as well as the degree of dominance. A
second technique is to focus on the individuals that exhibit no recombination
event in the region, apply dimensionality reduction (such as with linear
discriminant analysis) and compare the phenotype distribution in the
non-recombinants to that in the recombinant individuals: If the recombinant
individuals display a different expression pattern than the non-recombinants,
this indicates the presence of multiple causal polymorphisms. In the formal
likelihood-based test, we compare a two-locus model, with each expression trait
affected by one or the other locus, to a single-locus model. We apply our
methods to a large mouse intercross with gene expression microarray data on six
tissues.
