Cortical GABAergic interneurons are critical components of neural circuitry, and their dysfunction has been linked to neurodevelopmental diseases. Although the diversity of interneurons is not disputed, both the extent of their heterogeneity and the gene regulatory mechanisms that drive it remain unclear. Recent advances in single cell RNA-sequencing technology have shed new light on this issue, enabling the prediction of novel interneuron subtypes based on gene expression. Cross-species meta-analysis would provide key insight into conserved mechanisms of interneuron diversity. However, cross-study integration remains a major challenge. I hypothesize that interneuron identity is defined by unifying molecular processes across species. This project is designed to reveal these processes by using an integrative, cross-species approach to explore the transcriptional, epigenetic, and developmental mechanisms that govern interneuron diversity. First, I have shown that mouse interneuron subtypes replicably express genes associated with cell-cell communication, enabling cross-dataset meta-analysis. The goal of Aim 1 is to use improved computational and phylogenetic methods to define homologous interneuron subtypes across species and identify robust gene targets. Second, preliminary investigation of single cell methylome-sequencing data indicates that it can be readily aligned with expression data.
In Aim 2 I will use machine learning methods to generate networks from epigenomic and expression data and identify subtype-specific regulatory features. Third, I have shown that transcriptional profiles from developing neurons can be quantitatively assessed with respect to adult expression data.
Aim 3 will use meta-analytic aggregation of temporal inference methods to enable cross-dataset comparisons and define conserved developmental gene programs. These studies will reveal a multidimensional portrait of interneuron molecular identity and enable genetic access to these cell types, a key aim of the BRAIN Initiative. I also propose an extensive training plan that will support my transition to independence. CSHL provides an outstanding research environment, with unequaled opportunities for scientific discussion, advanced skills training and career development. I have assembled an exceptional team of collaborators and mentors who will help me to achieve my goals. Dr. Jesse Gillis, expert in transcriptome meta-analysis, and Dr. Josh Huang, expert in GABAergic interneuron identity, will be my mentors. Dr. Bing Ren, Dr. Adam Siepel, Dr. Guoping Feng, Dr. Jessica Tollkuhn and Dr. Michael Greenberg will be collaborators and members of my advisory committee, ensuring that my research will be of the highest caliber. My training will also involve coursework in multiomics data integration and comparative genomics, and I will continue my professional development by presenting at international conferences, mentoring students and attending workshops at CSHL. Together, the proposed studies and professional training will ensure my successful transition to an independent position at a major university where I will lead a lab that will advance the goals of the BRAIN Initiative.
Interneurons are key components of neural circuitry, acting as the cellular `brakes' that dampen neuronal activity. Although it has long been known that interneurons come in many different shapes and sizes, both the extent of this diversity and its consequences for brain function remain unclear. In this project, we propose that by combining information about the gene activity and epigenetic landscapes of interneurons across multiple species we will generate an integrated, multi-layered portrait of interneuron diversity which we can use to understand brain
