Unraveling Microglia

A large number of computational tools utilizing omics data (bulk and scRNA sequencing, ATAC-seq, ChIP-seq, etc.) have come out in recent years with various levels of utility and adoption. Our efforts are twofold. First, to utilize two of these tools in particular, NicheNet and Seurat, to better understand paracrine and autocrine signaling interactions between microglia, neurons, and other cell types within the developing brain. Second, to develop a streamlined platform, allowing researchers with various levels of computational expertise to quickly and efficiently utilize these tools and create publication quality results.

We utilized a pre-existing fetal microglia scRNA-seq dataset from our lab in conjunction with a published scRNA-seq fetal cortical dataset as input for NicheNet, a computational tool to predict signaling interactions and generate novel hypotheses. We were able to isolate microglia, neuronal, and astrocytes from the raw data and run NicheNet to find novel signaling interactions that play a key role in the developing brain.