Single-cell RNA sequencing in Drosophila: Technologies and applications

Abstract

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cell states and functions at the single-cell level. It has greatly revolutionized transcriptomic studies in many life science research fields, such as neurobiology, immunology, and developmental biology. With the fast development of both experimental platforms and bioinformatics approaches over the past decade, scRNA-seq is becoming economically feasible and experimentally practical for many biomedical laboratories. Drosophila has served as an excellent model organism for dissecting cellular and molecular mechanisms that underlie tissue development, adult cell function, disease, and aging. The recent application of scRNA-seq methods to Drosophila tissues has led to a number of exciting discoveries. In this review, I will provide a summary of recent scRNA-seq studies in Drosophila, focusing on technical approaches and biological applications. I will also discuss current challenges and future opportunities of making new discoveries using scRNA-seq in Drosophila. This article is categorized under: Technologies > Analysis of the Transcriptome.

Keywords: drosophila; single-cell RNA sequencing.

FIGURE 1

(a) Single-cell RNA-seq workflow. It contains five major steps: tissue dissection and dissociation, single-cell capture, cDNA and library preparation, sequencing, and data analysis. FACS- and microfluidics-based methods are two most commonly used methods for single-cell capture. In plate-based methods, each individual cell is captured in one well. In droplet-based methods, cells are captured in droplets with enzymes and barcoded-beads. (b) Summary of scRNA-seq studies in Drosophila (see Table 1 for details). Tissue stages are indicated. The abdominal cuticle is profiled through single-nucleus RNA-seq, and all other tissues are sequenced by single-cell RNA-seq. VNC, ventral nerve cord

FIGURE 2

Summary of current applications of single-cell RNA-seq in Drosophila, including classifying cell types and identifying rare cells, constructing cellular developmental trajectories, deciphering gene regulatory networks, and discovering mechanisms that control development and aging and that contribute to diseases

FIGURE 3

Challenges and future opportunities to extend the applications of scRNA-seq by combining scRNA-seq with other technologies, including single-nucleus RNA-seq, single-cell genomics, and epigenomics, nonpoly(A) RNA profiling, single-cell proteomics, and single-cell spatial transcriptomics