Summary Comparative analysis of BACarray data can provide important insights into complex biological systems. As demonstrated in the accompanying paper, BACarray translational profiling permits comprehensive studies of translated mRNAs in genetically defined cell populations following physiological perturbations. To establish the generality of this approach, we present BACarray translational profiles for twenty four CNS cell populations, and identify known cell-specific and enriched transcripts for each population. We report thousands of cell-specific mRNAs that were not detected in whole tissue microarray studies, and provide examples that demonstrate the benefits deriving from comparative analysis. To provide a foundation for further biological and in silico studies, we provide a resource of sixteen transgenic mouse lines, their corresponding anatomic characterization, and BACarray translational profiles for cell types from a variety of CNS structures. This resource will enable a wide spectrum of molecular and mechanistic studies of both well known and previously uncharacterized neural cell populations.

In the above article, Figure 2A is stated to summarize data from Figures 1A and 1B; however, we inadvertently displayed a plot of a different data set that was collected with a similar but slightly different experimental design. The data in Figures 1A and 1B are from an experiment in which one group of flies underwent mock conditioning and an independent group was conditioned with electric shock, whereas the data in Figure 2A were from an experiment in which the same population of flies sequentially underwent mock conditioning and actual conditioning.We provide here a corrected graph for Figure 2A plotting the data from Figure 1. The new plot does not affect the description of the results in the paper or the conclusions drawn. We apologize for any inconvenience caused by this error.

We have recently developed a novel method for the affinity purification of the complete suite of translating mRNA from genetically labeled cell populations. This method permits comprehensive quantitative comparisons of the genes employed by each specific cell type. We provide a detailed description of tools for analysis of data generated with this and related methodologies. An essential question that arises from these data is how to identify those genes that are enriched in each cell type relative to all others. Genes relatively specifically employed by a cell type may contribute to the unique functions of that cell, and thus may become useful targets for development of pharmacological tools for cell-specific manipulations. We describe here a novel statistic, the specificity index, which can be used for comparative quantitative analysis to identify genes enriched in specific cell populations across a large number of profiles. This measure correctly predicts in situ hybridization patterns for many cell types. We apply this measure to a large survey of CNS cell-specific microarray data to identify those genes that are significantly enriched in each population Data and algorithms are available online (www.bactrap.org).