RNA sequencing of Drosophila melanogaster optic lobe cell types

Transcription factors regulate the molecular, morphological, and physiological characters of neurons and generate their impressive cell type diversity. To gain insight into general principles that govern how transcription factors regulate cell type diversity, we used large-scale single-cell mRNA sequencing to characterize the extensive cellular diversity in the Drosophila optic lobes. We sequenced 57,000 single optic lobe neurons and glia and assigned them to 52 clusters of transcriptionally distinct single cells. We validated the clustering and annotated many of the clusters using RNA sequencing of characterized FACS-sorted single cell types, as well as marker genes specific to given clusters. To identify transcription factors responsible for inducing specific terminal differentiation features, we used machine-learning to generate a ‘random forest’ model. The predictive power of the model was confirmed by showing that two transcription factors expressed specifically in cholinergic (apterous) and glutamatergic (traffic-jam) neurons are necessary for the expression of ChAT and VGlut in many, but not all, cholinergic or glutamatergic neurons, respectively. Therefore, the same terminal characters can be regulated by different transcription factors in different cell types, arguing for extensive phenotypic convergence. Our data provide a deep understanding of the developmental and functional specification of a complex brain structure. We sequenced 17 FACS-sorted single cell types from the Drosophila optic lobe, as well as FACS-sorted neurons as a control. We also sequenced a line that had GFP expression in two cell types - Tm1 and T1.

转录因子（Transcription factors）可调控神经元的分子、形态与生理特征，并赋予神经元丰富的细胞类型多样性。为探究转录因子调控细胞类型多样性的通用原理，我们借助大规模单细胞mRNA测序（single-cell mRNA sequencing）对果蝇视神经叶（Drosophila optic lobes）中的广泛细胞多样性进行了系统表征。我们共完成57000个单个视神经叶神经元和神经胶质细胞的测序，并将其划分为52个转录特征迥异的单细胞簇。

我们通过对已鉴定的经荧光激活细胞分选（Fluorescence-activated cell sorting, FACS）富集的单细胞类型进行RNA测序，结合针对特定细胞簇的标记基因验证，完成了聚类结果的确认与多数细胞簇的注释。为鉴定调控特定终末分化特征的转录因子，我们采用机器学习方法构建了随机森林（random forest）模型。该模型的预测能力得到验证：在胆碱能神经元中特异性表达的转录因子无翅（apterous），以及在谷氨酸能神经元中特异性表达的转录因子交通阻塞（traffic-jam），分别对多数（而非全部）胆碱能神经元中ChAT的表达，以及多数（而非全部）谷氨酸能神经元中VGlut的表达具有必需作用。

本研究结果表明，相同的终末特征可在不同细胞类型中由不同转录因子调控，这提示存在广泛的表型趋同现象。我们的数据集为解析复杂脑结构的发育与功能特化提供了深刻的认知基础。此外，我们还对17种源自果蝇视神经叶的经FACS富集的单细胞类型，以及作为对照的经FACS富集的神经元开展了测序。同时，我们对一种在Tm1和T1两种细胞类型中表达绿色荧光蛋白（GFP）的果蝇品系进行了测序。