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 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 polyadenylation 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 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.

No abstract

Microinjection is a widely used technique for transgenesis, mutagenesis, cell labeling, cryopreservation, and in vitro fertilization in multiple single and multicellular organisms. Microinjection requires specialized skills acquired for each target organism and involves rate limiting and labor-intensive preparatory steps. Here we constructed a machine vision (MV) guided generalized robot that fully automates the process of microinjection in fruit fly (Drosophila melanogaster) and zebrafish (Danio rerio) embryos. The robot uses machine learning (ML) models trained to detect individual embryos in images of agar plates, and models trained to identify specific anatomical locations within each embryo in 3D space using dual view microscopes. The robot uses this information to serially perform microinjection in each detected embryo without any human intervention. We constructed and used three such robots to automatically microinject tens of thousands of Drosophila and zebrafish embryos. We systematically optimized robotic microinjection for each species and validated the use of the robot by performing routine transgenesis with proficiency comparable to highly skilled human practitioners while achieving up to 4x increases in microinjection throughput in Drosophila. The automated microinjection robot was utilized to microinject pools of over 20,000 uniquely barcoded plasmids into 1,713 embryos in two days to rapidly generate more than 400 unique transgenic Drosophila lines. This high throughput microinjection experiment enabled a novel measurement of the number of independent germline integration events per successfully injected embryo. Finally, we showed that robotic microinjection of cryoprotective agents in zebrafish embryos significantly improves vitrification rates and survival of cryopreserved embryos post-thaw as compared to manual microinjection, opening the tantalizing possibility of large-scale cryobanking of aquatic species at an industrial scale. We anticipate that this versatile automated microinjection system can be applied to carry out microinjection for genome-wide manipulation and cryopreservation at scale in a wide range of other organisms.

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 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 polyadenylation 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 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.