人类大脑的发育涉及到在许多其他物种中未被观察到的独特过程，这些过程可能与神经发育障碍有关[1-4]。脑器官样体使得我们能够在人类环境中研究神经发育障碍。我们开发了CRISPR-人类器官样体-单细胞RNA测序（CHOOSE）系统，该系统利用经过验证的一对一的RNA引导子，可诱导的CRISPR-Cas9基因破坏和单细胞转录组学来进行合并的功能丧失筛选。在这里，我们展示了对与转录调控有关的36个高风险自闭症谱系障碍基因的干扰揭示了它们对细胞命运决定的影响。我们发现，腹侧中间祖细胞、腹侧祖细胞和上层兴奋性神经元是最易受损的细胞类型之一。我们从单细胞转录组和染色质情况构建了脑器官样体的发育基因调控网络，并识别出与自闭症谱系障碍相关和干扰富集的调控模块。扰乱BRG1/BRM相关因子（BAF）染色质重塑复合物成员导致腹侧端脑后代细胞丰富。具体而言，突变的BAF亚基ARID1B影响了后代细胞向寡突胶质细胞和跨突神经元前体细胞的命运转变，我们在患者特异性诱导多能干细胞源器官样体中证实了这一表型。我们的研究为采用细胞状态、分子途径和基因调控网络输出的器官样体模型中对疾病易感基因进行高通量表型特征化铺平了道路。© 2023。作者。

The development of the human brain involves unique processes (not observed in many other species) that can contribute to neurodevelopmental disorders1-4. Cerebral organoids enable the study of neurodevelopmental disorders in a human context. We have developed the CRISPR-human organoids-single-cell RNA sequencing (CHOOSE) system, which uses verified pairs of guide RNAs, inducible CRISPR-Cas9-based genetic disruption and single-cell transcriptomics for pooled loss-of-function screening in mosaic organoids. Here we show that perturbation of 36 high-risk autism spectrum disorder genes related to transcriptional regulation uncovers their effects on cell fate determination. We find that dorsal intermediate progenitors, ventral progenitors and upper-layer excitatory neurons are among the most vulnerable cell types. We construct a developmental gene regulatory network of cerebral organoids from single-cell transcriptomes and chromatin modalities and identify autism spectrum disorder-associated and perturbation-enriched regulatory modules. Perturbing members of the BRG1/BRM-associated factor (BAF) chromatin remodelling complex leads to enrichment of ventral telencephalon progenitors. Specifically, mutating the BAF subunit ARID1B affects the fate transition of progenitors to oligodendrocyte and interneuron precursor cells, a phenotype that we confirmed in patient-specific induced pluripotent stem cell-derived organoids. Our study paves the way for high-throughput phenotypic characterization of disease susceptibility genes in organoid models with cell state, molecular pathway and gene regulatory network readouts.© 2023. The Author(s).