Transcriptional profile of hippocampal dentate granule cells in four rat epilepsy models.

Global expression profiling of neurologic or psychiatric disorders has been confounded by variability among laboratories, animal models, tissues sampled, and experimental platforms, with the result being that few genes demonstrate consistent expression changes. We attempted to minimize these confounds by pooling dentate granule cell transcriptional profiles from 164 rats in seven laboratories, using three status epilepticus (SE) epilepsy models (pilocarpine, kainate, self-sustained SE), plus amygdala kindling. In each epilepsy model, RNA was harvested from laser-captured dentate granule cells from six rats at four time points early in the process of developing epilepsy, and data were collected from two independent laboratories in each rodent model except SSSE. Hierarchical clustering of differentially-expressed transcripts in the three SE models revealed complete separation between controls and SE rats isolated 1 day after SE. However, concordance of gene expression changes in the SE models was only 26-38% between laboratories, and 4.5% among models, validating the consortium approach. Transcripts with unusually highly variable control expression across laboratories provide a 'red herring' list for low-powered studies.

A molecular neuroethological approach for identifying and characterizing a cascade of behaviorally regulated genes.

Songbirds have one of the most accessible neural systems for the study of brain mechanisms of behavior. However, neuroethological studies in songbirds have been limited by the lack of high-throughput molecular resources and gene-manipulation tools. To overcome these limitations, we constructed 21 regular, normalized, and subtracted full-length cDNA libraries from brains of zebra finches in 57 developmental and behavioral conditions in an attempt to clone as much of the brain transcriptome as possible. From these libraries, approximately 14,000 transcripts were isolated, representing an estimated 4,738 genes. With the cDNAs, we created a hierarchically organized transcriptome database and a large-scale songbird brain cDNA microarray. We used the arrays to reveal a set of 33 genes that are regulated in forebrain vocal nuclei by singing behavior. These genes clustered into four anatomical and six temporal expression patterns. Their functions spanned a large range of cellular and molecular categories, from signal transduction, trafficking, and structural, to synaptically released molecules. With the full-length cDNAs and a lentiviral vector system, we were able to overexpress, in vocal nuclei, proteins of representative singing-regulated genes in the absence of singing. This publicly accessible resource http://songbirdtranscriptome.net can now be used to study molecular neuroethological mechanisms of behavior.