Mapping of expression quantitative trait loci (eQTL) is a powerful means for elucidating the genetic architecture of gene regulation. Yet, eQTL mapping has not been applied toward investigating the regulation architecture of genes involved in the process of population divergence, ultimately leading to speciation events. Here, we conducted an eQTL mapping experiment to compare the genetic architecture of transcript regulation in adaptive traits, differentiating the recently evolved limnetic (dwarf) and benthic (normal) species pairs of lake whitefish. The eQTL were mapped in three data sets derived from an F1 hybrid-dwarf backcrossed family: the entire set of 66 genotyped individuals and the two sexes treated separately. We identified strikingly more eQTL in the female data set (174), compared to both male (54) and combined (33) data sets. The majority of these genes were not differentially expressed between male and female progeny of the backcross family, thus providing evidence for a strong pleiotropic sex-linked effect in transcriptomic regulation. The subtelomeric region of a linkage group segregating in females encompassed >50% of all eQTL, which exhibited the most pronounced additive effects. We also conducted a direct comparison of transcriptomic profiles between pure dwarf and normal progeny reared in controlled conditions. We detected 34 differentially expressed transcripts associated with eQTL segregating only in sex-specific data sets and mostly belonging to functional groups that differentiate dwarf and normal whitefish in natural populations. Therefore, these eQTL are not related to interindividual variation, but instead to the adaptive and historical genetic divergence between dwarf and normal whitefish. This study exemplifies how the integration of genetic and transcriptomic data offers a strong means for dissecting the functional genomic response to selection by separating mapping family-specific effects from genetic factors under selection, potentially involved in the phenotypic divergence of natural populations.