Deterministic Genetic Barcoding for Multiplexed Behavioral and Single-Cell Transcriptomic Studies

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 describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools available in Drosophila to allowin vivotagging of defined cell populations. This method, called<underline>Ta</underline>rgeted<underline>G</underline>enetically-<underline>E</underline>ncoded<underline>M</underline>ultiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducibleUAS-GFPconstruct 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 including positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. 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 has the potential to enable large-scale behavioral screens in addition to improving the ability to reliably annotate cell atlas data, expanding the scope, and improving the robustness of single-cell transcriptomic experiments.