Coexpression profiles reveal hidden gene networks.

The large-scale automation of neuroscience has enabled the construction of genome-wide atlases, of which the Allen Brain Atlas (ABA), which allows the 3D visualization of the expression profile of 21,500 genes in the male mouse brain down to single-cell level resolution, is the most comprehensive (1). In PNAS, Mahfouz et al. (2) use the ability of the ABA to pinpoint the anatomical locations of expressed genes to uncover transcripts whose expression profiles correlate with those of steroid receptors, to begin to understand their function and specificity of action in different brain regions. This study shows that mapping combinatorial interactions among specific sets of genes represents a significant leap forward in our understanding of how tissue specificity for a given signaling pathway is determined, and in identifying the potential relationship between otherwise unrelated brain areas in terms of the adaptive response to specific biological and environmental challenges. Steroid receptors are pleiotropic transcription factors belonging to the superfamily of nuclear receptors, whose activity is induced by steroid hormones: lipophilic signaling molecules derived from cholesterol and primarily produced by the gonads and the adrenal cortex. In the mammalian brain, steroid hormones mediate the feedback from these steroid-generating organs on the neuroendocrine hypothalamus to control bodily functions (reproduction, metabolism, stress, inflammation, osmoregulation), but also play a fundamental organizational role during brain development, trigger adult brain plasticity, and are involved in cognitive and emotional regulation (3–10). The idea of having an anatomical map combined with a quantitative expression map of nuclear receptor genes dates back to 2007, when Gofflot et al. created an interactive database of 49 nuclear receptor genes spanning more than 100 different regions of the mouse brain (11). These researchers used two complementary approaches to meet the challenge of obtaining both cell-level resolution and an unbiased expression profile of large anatomical regions: real-time PCR provided a broad estimate of nuclear receptor expression levels in selected brain regions, and spatial expression patterns were more closely studied using highresolution in situ hybridization (ISH). The study by Mahfouz et al. (2) significantly extends this approach to identify novel aspects of steroid hormone action via the spatial correlation of the expression patterns of steroid receptors with those of genes that could potentially be steroid hormone targets or even downstream receptor coregulators. Six well-studied steroid receptors were chosen by Mahfouz et al. (2) to costar in the “guilt by association” play; their expression profiles, although already reported in the literature, were validated using 3D spatial gene-expression data from the ABA (1). Based on the “guilt by association” principle, genes with similar spatial expression profiles are assumed to share similar biological functions, forming a neighborhood network of potential partners (12). Hence, for each receptor, Mahfouz et al. (2) ranked potential partner genes based on their spatial coexpression in various brain structures in different parts of the brain, and tested the assumption that Fig. 1. Three-dimensional gene expression in the human brain. The model shows the expression of ESR1 andMAGEL2mapped onto a ventral view of a 3D-reference atlas reconstruction. The expression of these genes is indicated by the dots. The color of the dots indicates the expression level: green (low expression) through red (high expression). Images were produced by the Brain explorer 2 software application, an interactive version of the Allen Human Brain Atlas.