The central goal of this program is to understand neural diversity at the most detailed molecular level by profiling the gene expression patterns of neurons in the invertebrate and vertebrate brain. We take advantage of the powerful tools available in Drosophila to label each class of neurons in the optic lobes, isolate them using fluorescence-activated cell sorting (FACS), and sequence their transcriptomes. A similar approach is performed with cortical interneurons in the mouse brain. This effort takes advantage of a complementary long-term relationship between neuroscience labs at NYUAD and NYUNY, benefiting from the genomics and bioinformatics cores at the Center.
The huge diversity of cell types and the number of neuronal connections in the brain are a daunting problem that must be understood in order to comprehend neural circuit function. Modern tools of molecular genetics have allowed the identification and labeling of many cell types that compose each brain structure. Despite the complexity of these systems, the composite cell types within each of these circuits ranges from ten to a hundred, making assembly of a comprehensive transcriptome of all these cell types a complex but tractable problem. Indeed, advances in molecular genetics in flies and mice, as well as in cell sorting and deep-sequencing technologies, have made it possible to isolate and determine the battery of genes expressed in homogeneous populations of single cell-types. The PIs in this program are among the leaders in this field. We are generating quantitative data on gene expression patterns for all neurons in the Drosophila optic lobes and in the circadian clock, as well as all mouse cortical interneurons.
The goal is to establish for each neuronal class a matrix of regulatory proteins (transcription factors) and phenotypic features such as neurotransmitter, their receptors, neuronal arborizations, target regions of the brain, excitatory vs inhibitory neurons and a wealth of molecular markers obtained from the transcriptome. This will allow us to understand how each phenotypic character is controlled at the transcriptional level, enabling us to eventually generate these neurons from their precursors in vitro or in vivo.
Researchers and Staff:
Naila Adams: Research Technician
Najate Benhra: Research Associate
Khaled Ben Elkadhi: Postdoctoral Associate
Rana El Danaf: Research Scientist
Lihua Guo: Research Associate
Deema Al Husari: Research Technician
Katarina Kapuralin: Research Scientist
Filipe Pinto Teixeira Sousa: Postdoctoral Associate
Qing Xu: Senior Research Scientist