Chen Yu-Chieh David, Chen Yen-Chung, Rajesh Raghuvanshi, Shoji Nathalie, Jacy Maisha, Lacin Haluk, Erclik Ted, Desplan Claude
Department of Biology, New York University, New York, NY 10003, USA.
Center for Genomics and Systems Biology, New York University, Abu Dhabi 51133, United Arab Emirates.
bioRxiv. 2023 Feb 4:2023.02.03.527019. doi: 10.1101/2023.02.03.527019.
Cell-type-specific tools facilitate the identification and functional characterization of distinct cell types, which underly the complexity of neuronal circuits. A large collection of existing genetic tools in Drosophila relies on enhancer activity to label different subsets of cells. These enhancer-based GAL4 lines often fail to show a predicable expression pattern to reflect the expression of nearby gene(s), partly due to an incomplete capture of the full gene regulatory elements. While genetic intersectional technique such as the split-GAL4 system further improve cell-type-specificity, it requires significant time and resource to generate and screen through combinations of enhancer expression patterns. In addition, since existing enhancer-based split-GAL4 lines that show cell-type-specific labeling in adult are not necessarily active nor specific in early development, there is a relative lack of tools for the study of neural development. Here, we use an existing single-cell RNA sequencing (scRNAseq) dataset to select gene pairs and provide an efficient pipeline to generate cell-type-specific split-GAL4 lines based on the native genetic regulatory elements. These gene-specific split-GAL4 lines can be generated from a large collection of coding intronic MiMIC/CRIMIC lines either by embryo injection or cassette swapping crosses and/or CRISPR knock-in at the N or C terminal of the gene. We use the developing Drosophila visual system as a model to demonstrate the high prediction power of scRNAseq-guided gene specific split-GAL4 lines in targeting known cell types. The toolkit allows efficient cluster annotation in scRNAseq datasets but also the identification of novel cell types. Lastly, the gene-specific split-GAL4 lines are broadly applicable to Drosophila tissues. 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 to the fly research community.
Understanding the functional role of individual cell types in the nervous systems has remained a major challenge for neuroscience researchers, partly due to incomplete identification and characterization of underlying cell types. To study the development of individual cell types and their functional roles in health and disease, experimental access to a specific cell type is often a prerequisite. Here, we establish an experimental pipeline to generate gene-specific split-GAL4 guided by single-cell RNA sequencing datasets. These lines show high accuracy for labeling targeted cell types from early developmental stages to adulthood and can be applied to any tissues in Drosophila. The collection of gene-speicifc-split-GAL4 will provide a valuable resource to the entire fly research community.
细胞类型特异性工具有助于识别和功能表征不同的细胞类型,这些细胞类型构成了神经回路的复杂性。果蝇中大量现有的遗传工具依赖增强子活性来标记不同的细胞亚群。这些基于增强子的GAL4品系常常无法显示出可预测的表达模式以反映附近基因的表达,部分原因是未能完全捕获完整的基因调控元件。虽然诸如分裂GAL4系统等遗传交叉技术进一步提高了细胞类型特异性,但生成和筛选增强子表达模式的组合需要大量时间和资源。此外,由于现有的在成体中显示细胞类型特异性标记的基于增强子的分裂GAL4品系在早期发育中不一定活跃或特异,因此相对缺乏用于神经发育研究的工具。在这里,我们使用现有的单细胞RNA测序(scRNAseq)数据集来选择基因对,并提供一种基于天然遗传调控元件生成细胞类型特异性分裂GAL4品系的有效方法。这些基因特异性分裂GAL4品系可以通过胚胎注射或盒式交换杂交从大量编码内含子的MiMIC/CRIMIC品系中产生,和/或在基因的N端或C端进行CRISPR敲入。我们以发育中的果蝇视觉系统为模型,证明了scRNAseq指导的基因特异性分裂GAL4品系在靶向已知细胞类型方面具有很高的预测能力。该工具包不仅能在scRNAseq数据集中进行有效的聚类注释,还能识别新的细胞类型。最后,基因特异性分裂GAL4品系广泛适用于果蝇组织。我们的工作为在整个发育过程中生成用于靶向操纵不同细胞类型的细胞类型特异性工具开辟了新途径,是果蝇研究界的宝贵资源。
理解单个细胞类型在神经系统中的功能作用一直是神经科学研究人员面临的重大挑战,部分原因是潜在细胞类型的识别和表征不完整。为了研究单个细胞类型的发育及其在健康和疾病中的功能作用,实验性地获取特定细胞类型通常是一个先决条件。在这里,我们建立了一个实验流程,以单细胞RNA测序数据集为指导生成基因特异性分裂GAL4。这些品系在从早期发育阶段到成年期标记靶向细胞类型方面显示出高精度,并且可以应用于果蝇的任何组织。基因特异性分裂GAL4的集合将为整个果蝇研究界提供宝贵的资源。