Drosophila melanogaster is a powerful, long-standing model for metazoan development and gene regulation. We profiled chromatin accessibility in almost 1 million and gene expression in half a million nuclei from overlapping windows spanning the entirety of embryogenesis. Leveraging developmental asynchronicity within embryo collections, we applied deep neural networks to infer the age of each nucleus, resulting in continuous, multimodal views of molecular and cellular transitions in absolute time. We identify cell lineages; infer their developmental relationships; and link dynamic changes in enhancer usage, transcription factor (TF) expression, and the accessibility of TFs’ cognate motifs. With these data, the dynamics of enhancer usage and gene expression can be explored within and across lineages at the scale of minutes, including for precise transitions like zygotic genome activation.

中文翻译：

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单细胞分辨率下果蝇胚胎发育的连续体


黑腹果蝇是后生动物发育和基因调控的强大且长期存在的模型。我们从跨越整个胚胎发生的重叠窗口中分析了近 100 万个染色质可及性和 50 万个细胞核的基因表达。利用胚胎集合中发育的异步性，我们应用深度神经网络来推断每个细胞核的年龄，从而获得绝对时间内分子和细胞转变的连续、多模式视图。我们识别细胞谱系；推断他们的发展关系；并将增强子使用、转录因子 (TF) 表达和 TF 同源基序的可及性的动态变化联系起来。利用这些数据，可以在几分钟内探索谱系内和谱系间增强子使用和基因表达的动态，包括诸如合子基因组激活之类的精确转变。