Using single-cell RNA sequencing to generate predictive cell-type-specific split-GAL4 reagents throughout development.

Cell-type-specific tools facilitate the identification and functional characterization of the distinct cell types that form the complexity of neuronal circuits. A large collection of existing genetic tools in relies on enhancer activity to label different subsets of cells and has been extremely useful in analyzing functional circuits in adults. However, these enhancer-based GAL4 lines often do not reflect the expression of nearby gene(s) as they only represent a small portion of the full gene regulatory elements. While genetic intersectional techniques such as the split-GAL4 system further improve cell-type-specificity, it requires significant time and resources to screen through combinations of enhancer expression patterns. Here, we use existing developmental single-cell RNA sequencing (scRNAseq) datasets to select gene pairs for split-GAL4 and provide a highly efficient and predictive pipeline (scMarco) to generate cell-type-specific split-GAL4 lines at any time during development, based on the native gene regulatory elements. These gene-specific split-GAL4 lines can be generated from a large collection of coding intronic MiMIC/CRIMIC lines or by CRISPR knock-in. We use the developing visual system as a model to demonstrate the high predictive power of scRNAseq-guided gene-specific split-GAL4 lines in targeting known cell types, annotating clusters in scRNAseq datasets as well as in identifying novel cell types. Lastly, the gene-specific split-GAL4 lines are broadly applicable to any other tissue. Our work opens new avenues for generating cell-type-specific tools for the targeted manipulation of distinct cell types throughout development and represents a valuable resource for the community.