difficult to analyze, owing to many factors, including staining artifacts and sample-to-sample variabilities. The simultaneous visualization of two different staining patterns may circumvent this problem to some extent by providing a reference to analyze the other. Accumulating samples for quantitative evaluation may also be helpful. Nevertheless, the latter method requires that data are obtained and accumulated from accurately identified cortical areas. This task is, in fact, quite difficult, especially for the rodent cortex, where there are no clear- cut borders for area demarcation. In an effort to analyze the spatial distribution of c-Fos expression [31], we previously developed cortical box method. By this method, the gene expression in the rat neocortex can be mapped into a three- dimensional standardized cortical box from serially prepared sections. Importantly, this standardization process enables us to integrate data from different animals for statistical evaluation. Several methods have been proposed to reconstruct section data into a three-dimensional structure (e.g., [27], [32–35]). In comparison with these previous methods, the advantage of our method is that the lamina information is preserved in one axis of the three-dimensional cortical map. The simplicity of the result is also a strength of our method, which helps in the intuitive understanding of the area distribution. In the present study, we used the rat cortex as a model system to analyze the area-specific expression patterns of three ‘‘layer- specific’’ mRNAs, RORbeta [14], ER81 [10], [22], [23] and Nurr1 [13], [19], [23], which are expressed mainly in layers 4, 5 and 6 of the rodent neocortex, respectively. Although the heterogeneous expressions of these genes within neocortical areas have been reported in these previous studies, we think that more detailed analysis is necessary to understand their complex spatial distribution patterns. In this endeavor, we employed double ISH to examine the coexpression profiles of these genes at single cell level and cortical box method for a global view. Cortical box method enabled us to perform statistical evaluation of the data from different individual animals as well as multivariate analysis to extract common and differential patterns of expression for the three genes. Our study underscores the usefulness of quantitative approaches in analyzing gene expression data. Results Heterogeneity of layer-specific gene expression revealed by double ISH Figure 1A shows the double ISH of RORbeta and ER81 mRNAs and Fig. 1B shows that of RORbeta and Nurr1 mRNAs in the middle and occipital coronal sections of rat brains. RORbeta and Nurr1 mRNAs showed prominent area differences while ER81 mRNA did not show such conspicuous area difference. As reported previously [14], RORbeta mRNA was most abundant in the barrel field of the parietal cortex area 1 (Par1) (Fig. 1). RORbeta mRNA was generally expressed more abundantly in the sensory areas than in other areas. ER81 mRNA exhibited the opposite pattern, showing higher levels of expression in the areas where the RORbeta mRNA expression level was low (Fig. 1A, see also Fig. 2, panels a, e and f). Nurr1 mRNA exhibited a characteristic area expression pattern (Fig. 1B): its expression in layer 6A was restricted to the lateral regions (e.g., Fig. 1B, par2, Oc2L and Te1, see also Fig. 2, panels b’, c’, e’ and f’) and there was only low expression in layer 6B in the dorsal areas (e.g., Fig. 1B, Par1 and Oc1, see also Fig. 2 panels a’ and d’). Figure 2 shows the double ISH of these genes in various areas at higher magnification. At this magnification, we were able to identify individual neurons and examine how the positively stained ISH Profiling of Rat Cortex Figure 1. Double in situ hybridization histochemistry (ISH) of RORbeta/ER81 (A) and RORbeta/Nurr1 (B). Signals in red are for RORbeta and those in green are for ER81 (A) or Nurr1 (B). The arrowheads indicate the area borders that were deduced by comparing the gene expression patterns shown by double ISH and those revealed by the cortical box method. Par1, Par2, Oc1, Oc2L and Te1 correspond to the primary and secondary somatosensory areas (Par1 and Par2), the primary and secondary visual areas (Oc1 and Oc2L) and the primary auditory area (Te1). Ectorhinal cortex (Ect) is also indicated. The white bars denoted as a–e and a’–e’ are the regions magnified in Fig. 2. This figure is a montage of several images. Although the lighting condition of the original images was not even at this low resolution, we adjusted the contrast of each component image manually so that the montage appeared to be consecutive. Scale bar, 2 mm. doi:10.1371/journal.pone.0003266.g001 neurons are distributed within and across layers in different areas. For example, although Nurr1-mRNA-positive cells were mostly confined to layers 6A and 6B of most areas (Fig. 2, panels a’–e’), its subpopulation was found scattered into layer 5 and even layer 4 in the lateral-most areas. In the laterocaudal area (e.g., Fig. 1B, Ect), Nurr1-mRNA-positive cells were found both in layers 5 and 6 to a similar extent and extensively intermingled with the RORbeta- mRNA-positive cells (Fig. 2, panel f’). Such area differences were also observed for ER81-mRNA-positive cells. In the barrel field (Fig. 2, panel b), we observed a sublayer with lower expression levels of both RORbeta and ER81 mRNAs (white arrows). Based on Hoechst nuclear staining, this cleft sublayer appears to be the PLoS ONE | www.plosone.org 2 September 2008 | Volume 3 | Issue 9 | e3266