de Jong S et al. BMC Genomics 2010, 11:20 http://www.biomedcentral.com/1471-2164/11/20 interconnected. Hippocampal function has been exten- sively studied and it has been shown to be a key struc- ture in learning and memory processes [10]. The amygdala is important in processing fear and anxiety and is also thought to be involved in associative learning and memory. Because of its small size and complicated anatomy the amygdala has been less well studied in man. The structure consists of about 10 different subnu- clei with distinct roles for the input and output of infor- mation [11]. Both brain regions have been implicated in neuropsychiatric disorders such as schizophrenia and depression, as well as epilepsy, but there is increasing evidence that they might play differential roles as well [12,13]. Using the mouse as an animal model is advantageous for the study of neurobehavioral traits because the genetic make-up of these inbred strains is known and they have been extensively phenotyped for more than two decades. This makes it possible to select strains most divergent for the (behavioral) trait of interest and to search for underlying genetic factors [14]. A recent study estimated that there are ~8 million single nucleo- tide polymorphisms (SNPs) between classical mouse inbred strains, which results in an estimated strain diversity of 1 SNP every 250-300 base pairs [15]. Although gene expression carries information about biological state and environment, a number of studies have shown that up to 85% of the measured transcripts in human lymphocytes are significantly heritable [16,17]. This suggests that gene expression in general is under strong genetic control. An association analysis of expres- sion levels with SNPs and genomic copy number varia- tions (CNVs) in human lymphoblastoid cell lines was performed and showed that SNPs and CNVs capture 83.6% and 17.7% of the total detected genetic variation in gene expression, respectively [18]. Expression levels are shown to be more variable among individuals than among the populations they belong to, as studied in fun- dulus fish and man [17,19,20]. Differences in allele fre- quencies seem to explain most of the variation in transcript levels between human populations [21]. To explore gene expression differences specific to a strain and/or brain region, we studied the amygdala and hippocampus brain tissues of mouse inbred strains A/J and C57BL/6J. These strains have been consistently shown to differ in behavioral, physiological and develop- mental processes. For example, studies have reported that A/J show more anxiety-like behaviors and are less social towards other mice [22]. A/J is also known to have lower motor activity levels [23] and be more resis- tant to developing epilepsy [24] than C57BL/6J. Although they are heavily interconnected, the amyg- dala and hippocampus perform separate functions in memory and emotion (see earlier). The amygdala Page 2 of 14 functions mostly through GABA-ergic transmission, while the hippocampus uses excitatory connections [6]. Here we explore whether behavioral differences between the mouse strains and functional specificity of the two brain regions are reflected in differential gene expression profiles. It is plausible that differences in expression pro- files represent a combination of genetic and functional variation. Considering the involvement of the hippocam- pus and amygdala in neurobehavioral symptoms in both mouse and man, the results from our mouse analysis may shed new light on pathways underlying neuropsy- chiatric traits in humans as well. Since we were interested in finding co-expression modules that relate to amygdala and hippocampus in the different mouse strains, we used gene co-expression network analysis. Gene co-expression network methods have been successfully applied in a variety of different settings [8,25-29]. This systems biology analysis method starts out by defining clusters of co-expressed genes (called ‘modules’) which may represent molecular net- works involved in a common biological pathway. Genes that are highly connected within these groups are thought to drive the modules and are considered to be ‘hub genes’. As described below, we identified large co- expression modules that are significantly associated with differences between mouse strains and brain regions. We found that the observed strain-specific modules in fact reflect hybridization artifacts but, strikingly, two large modules distinguish brain regions irrespective of genetic background. Detailed functional enrichment ana- lyses revealed an overrepresentation of genes involved in neurological and psychological disorders, in addition to nervous system function and development. Results Data preprocessing After background correction, expression arrays were transformed and normalized according to the Lumi pro- cedure [30]. Genes were then filtered based on detection values generated by BeadStudio©. The detection p-value threshold was set at 0.01, leaving 13,627 of the 24,620 probes on the microarrays for analysis. Hierarchical clustering using all probe information yielded no sample outliers. Network reconstruction A gene co-expression network was constructed using amygdala and hippocampus tissue from both A/J and C57BL/6J strains (total N = 35). For computational rea- sons, only the 5,000 most variable probes (across all sam- ples) were used for the network construction. To construct a weighted co-expression network based on the matrix of pairwise Pearson correlation coefficients, we used a soft thresholding approach by raising each correc- tion to a fixed power. We used the criterion described by