Molecular differences between brain regions
We have shown that spatial expression patterns of neuron-specific genes in the adult mouse brain show remarkably clear, spatially contiguous, transcriptionally distinct clusters. Specifically, taking advantage of spatial expression data from the Allen Institute, we have applied clustering approaches to reveal that the expression patterns of 170 neuron-specific transcripts revealed strikingly clear and symmetrical signatures for most of the brain’s major subdivisions in the mouse brain. Moreover, the brain expression spatial signatures correspond to anatomical structures and may even reflect developmental ontogeny. Spatial expression profiles of astrocyte- and oligodendrocyte-specific genes also revealed regional differences; these were less distinct, but still symmetrical. The regional differences revealed by neuron-specific genes related to individual genes with highly restricted expression patterns, functionally-related groups of genes with enriched or depleted expression across brain regions, and regional differences in neuronal cell density. Products from some of these neuron-specific genes are present in peripheral blood, raising the possibility that they could collectively function as biomarkers for clinical disease diagnostics.
Brain regulatory networks and behavior
We are addressing one of the biggest challenges in biology, which is to understand the relationship between genes and behavior. This is a collaborative project between our lab and Dr. Gene Robinson’s behavioral neuroscience lab and involves the application of systems approaches to predict the effect of a dynamic process like behavior on gene expression. Using a brain transcriptome data set (generated in Dr. Robinson’s lab) unparalleled in size and scope (over 800 individual honeybees sampled in almost 50 behavioral states) we succeeded in reconstructing a Transcriptional Regulatory Network (TRN) that showed remarkably high accuracy in quantitatively predicting brain gene expression. This TRN encompasses thousands of genes and we found specific transcription factors that are central actors in regulating behavior. Our results show that despite the daunting anatomical and physiological complexity of the brain, simple linear connections between transcription factors and their putative target genes are a surprisingly prominent feature of brain neurogenomic states that underlie naturally occurring behavior. We demonstrated that behavior—one of the most dynamic organismal phenotypes—is subserved by the kind of regulatory networks heretofore known only for simpler phenotypes. We consider this finding to be an important milestone in behavioral genomics.
Elucidating gene networks underlying bipolar disorder
How do genes influence brain function and behavior? What mutations increase risk for brain diseases such as psychiatric illness? We are working to elucidate gene networks underlying bipolar disorder through a combination of genome sequencing of affected individuals and their families, computational network analysis of brain gene expression, and genetic manipulations of neuronal cell lines. Bipolar disorder and other common psychiatric diseases are highly heritable, yet recent studies suggest that hundreds of different genetic mutations can influence disease risk. We believe that this extreme genetic complexity — though daunting — is essentially “solvable” given sufficient data on gene variants in patients and an appropriate network context. Preliminary results are yielding a variety of promising candidate genes and gene networks for follow-up. This work is done in collaboration with the lab of Leroy Hood at ISB and with researchers at UCSD and NIMH.