Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies.

Area of Science:

• Developmental Biology
• Genomics
• Neuroscience

Background:

• Single-cell sequencing reveals gene expression dynamics and cellular heterogeneity.
• Linking anatomical data to transcriptomic clusters and identifying cell types remains challenging.
• Existing methods lack efficient in vivo cell population tagging for transcriptomic analysis.

Purpose of the Study:

• To develop a genetic barcoding method for in vivo tagging of specific cell populations in Drosophila.
• To enable positive identification of cell types within single-cell sequencing datasets.
• To facilitate population-scale behavioral measurements using next-generation sequencing.

Main Methods:

• Developed Targeted Genetically-Encoded Multiplexing (TaG-EM) using DNA barcodes inserted into UAS-GFP constructs.
• Utilized Drosophila genetic tools for targeted in vivo labeling of cell populations.
• Read out DNA barcodes via next-generation sequencing.

Main Results:

• TaG-EM allows for the in vivo tagging of defined cell populations with unique DNA barcodes.
• Barcodes enable positive identification of cell types in transcriptomic atlases and detection of multiplet droplets.
• TaG-EM facilitates population-scale behavioral measurements through next-generation sequencing.

Conclusions:

• TaG-EM provides a straightforward approach for multiplexing and reliably annotating single-cell transcriptomic experiments.
• The method enhances the ability to link gene expression data with anatomical information.
• TaG-EM opens possibilities for large-scale behavioral screens in Drosophila.