We used microarrays and a previously established linkage map to localize the genetic determinants of brain gene expression for a backcross family of lake whitefish species pairs (Coregonus sp.). Our goals were to elucidate the genomic distribution and sex-specificity of brain expression QTL (eQTL) and to determine the extent to which genes controlling transcriptional variation may underlie adaptive divergence in the recently evolved dwarf (limnetic) and normal (benthic) whitefish. We observed a sex-bias in transcriptional genetic architecture, with more eQTL observed in males, as well as divergence in genome location of eQTL between sexes. Hotspots of nonrandom aggregations of up to 32 eQTL in one location were observed. We identified candidate genes for species pair divergence involved with energetic metabolism, protein synthesis, and neural development based on co-localization of eQTL for these genes with eight previously identified adaptive phenotypic QTL and four previously identified outlier loci from a genome scan in natural populations. 88% of eQTL-phenotypic QTL co-localization involved growth rate and condition factor QTL, two traits central to adaptive divergence between whitefish species pairs. Hotspots co-localized with phenotypic QTL in several cases, revealing possible locations where master regulatory genes, such as a zinc finger protein in one case, control gene expression directly related to adaptive phenotypic divergence. We observed little evidence of co-localization of brain eQTL with behavioral QTL, which provides insight on the genes identified by behavioral QTL studies. These results extend to the transcriptome level previous work illustrating that selection has shaped recent parallel divergence between dwarf and normal lake whitefish species pairs and that metabolic, more than morphological differences appear to play a key role in this divergence.
The objective of this study was to elucidate the genomic distribution and sex-specificity of brain eQTL in dwarf and normal lake whitefish. Dissected brain tissue (250-350 mg) was sampled for 55 individuals from a hybrid x dwarf backcross mapping family. We used a loop design (YANG and SPEED 2002; CHURCHILL 2002) to maximize the number of sampled meioses. Each of 55 samples was technically replicated on two distinct slides, while performing dye swapping (Cy3 and Alexa) to estimate the dye intensity variation bias. After correcting for local background, raw intensity values were both log2 transformed and normalized using the regional LOWESS method implemented in the R/MANOVA software (KERR et al. 2000). We used a previously generated linkage map based on the same backcross individuals for which gene expression was measured. eQTL mapping was performed with QTL Cartographer.
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