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通过MERGE-Seq技术解析小鼠PFC脑区的单细胞转录组-连接图谱的数据

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中国科学院脑科学数据中心2023-12-04 更新2024-03-05 收录
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https://www.braindatacenter.cn/datacenter/web/#/dataSet/details?id=1731575574797213697
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细胞谱系在不同发育阶段的情况仍待阐明。在这里,我们开发了单细胞分割条形码(SISBAR)技术,允许在体外人类腹侧中脑-后脑分化模型中跨阶段跟踪单细胞转录组的克隆情况。我们开发了“潜在-视角”和“起源-视角”的分析方法,以研究跨阶段的谱系关系,并绘制了一个多级克隆谱系景观,描绘了整个分化过程。我们揭示了许多以前未被了解的汇聚和分歧轨迹。此外,我们证明了一个以转录组定义的细胞类型可以起源于不同的谱系,这些谱系在其后代上留下分子印记,而一个前体细胞类型的多谱系命运代表了不同而不是相似的单个前体细胞克隆命运的集体结果,每个克隆都具有不同的分子特征。具体而言,我们揭示了一个腹侧中脑前体簇是中脑多巴胺能(mDA)神经元、中脑谷氨酸能神经元以及血管和软膜细胞的共同克隆起源,并鉴定了一个可以改善移植结果的表面标记物。

The cellular lineages across distinct developmental stages remain to be fully elucidated. Here, we developed the single-cell segmentation barcoding (SISBAR) technology, which enables cross-stage tracking of clonal dynamics of single-cell transcriptomes in an in vitro human ventral midbrain-hindbrain differentiation model. We established two analytical frameworks, the "latent-perspective" and "origin-perspective" approaches, to investigate cross-stage lineage relationships, and constructed a multi-level clonal lineage landscape that recapitulates the entire differentiation process. We uncovered numerous previously unrecognized convergent and divergent trajectories. Furthermore, we demonstrated that transcriptomically defined cell types can arise from distinct lineages, which leave molecular imprints on their progeny. Additionally, the multi-lineage fates of a progenitor cell type represent the collective outcomes of distinct rather than similar clonal fates of individual progenitor clones, each bearing unique molecular signatures. Specifically, we revealed that a ventral midbrain progenitor cluster serves as a common clonal origin for midbrain dopaminergic (mDA) neurons, midbrain glutamatergic neurons, as well as vascular and leptomeningeal cells, and identified a surface marker that improves transplantation outcomes.
提供机构:
中国科学院脑科学数据中心
创建时间:
2023-12-04
搜集汇总
数据集介绍
main_image_url
背景与挑战
背景概述
该数据集通过MERGE-Seq技术生成了小鼠前额叶皮质(PFC)脑区的单细胞转录组数据,旨在构建该脑区的连接图谱。数据集包含多个实验阶段和重复的转录组文件(如基因表达矩阵、特征和条形码文件),总容量为1.22 GB,由中国科学院脑科学与智能技术卓越中心于2023年发布,采用CC BY 4.0许可证。
以上内容由遇见数据集搜集并总结生成
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