果蝇大脑是神经科学中常用的模型。单细胞转录组分析1,2,3,4,5,6，三维形态学分类7和连接组8,9的电子显微镜作图已经揭示了神经元和神经胶质细胞类型的巨大多样性，它们是果蝇一系列功能和行为特征的基础。这些细胞类型的身份由基因调控网络 (GRN) 控制，涉及与基因组增强子结合以调节其靶基因的转录因子组合。在这里，为了在果蝇大脑的细胞类型水平上表征 GRN，我们分析了跨越 9 个发育时间点的 240,919 个单细胞的染色质可及性，并将这些数据与单细胞转录组整合。我们确定了超过 95,000 个用于不同神经元细胞类型的调节区域，其中 70,000 个与涉及神经发生、重编程和成熟的发育轨迹有关。对于 40 种细胞类型，通过基序发现、网络推理和深度学习的结合，将独特可及区域与其表达的转录因子和下游靶基因相关联，从而创建增强子 GRN。DeepFlyBrain 揭示的增强子架构有助于更好地理解神经元调节多样性，并可用于在特定时间点为细胞类型设计遗传驱动线，促进它们的表征和操作。

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The Drosophila brain is a frequently used model in neuroscience. Single-cell transcriptome analysis1,2,3,4,5,6, three-dimensional morphological classification7 and electron microscopy mapping of the connectome8,9 have revealed an immense diversity of neuronal and glial cell types that underlie an array of functional and behavioural traits in the fly. The identities of these cell types are controlled by gene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. Here, to characterize GRNs at the cell-type level in the fly brain, we profiled the chromatin accessibility of 240,919 single cells spanning 9 developmental timepoints and integrated these data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which 70,000 are linked to developmental trajectories involving neurogenesis, reprogramming and maturation. For 40 cell types, uniquely accessible regions were associated with their expressed transcription factors and downstream target genes through a combination of motif discovery, network inference and deep learning, creating enhancer GRNs. The enhancer architectures revealed by DeepFlyBrain lead to a better understanding of neuronal regulatory diversity and can be used to design genetic driver lines for cell types at specific timepoints, facilitating their characterization and manipulation.