View Program - 63rd Annual Drosophila Research Conference

Advances in single cell sequencing technologies have provided novel insights into the dynamics of gene expression throughout development, been used to characterize somatic variation and heterogeneity within tissues and are currently enabling the construction of transcriptomic cell atlases. However, despite these remarkable advances, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single cell sequencing data sets remains a challenge. We are developing a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools available in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the poly-adenylation site in a Gal4-inducible UAS-GFP construct, so that the barcode sequence can be read out during single cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM will enable a number of potential applications that will improve the quality and information content of single cell transcriptomic data. Potential applications of this method include positive identification of cell types in cell atlas projects, barcoding of experimental timepoints, conditions, or replicates, and detection and elimination of multiplets through detection of multiple barcodes. Furthermore, we demonstrate that the barcodes from TaG-EM fly lines can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM will enable many types of large-scale behavioral screens in addition to improving the ability to reliably annotate cell atlas data, expanding the scope of single cell transcriptomic experiments, and improving the robustness of such data by facilitating inclusion of replicates.

Genetic barcoding for single cell transcriptomics and population behavioral assays