美国麻省理工学院和哈佛大学布罗德研究所Aviv Regev， Kristin G. Ardlie，Orit Rozenblatt-Rosen，Orit Rozenblatt-Rosen和美国哈佛医学院Ayellet V. Segrè共同合作取得重要工作进展。他们绘制
在这里，研究人员将四种单核RNA测序方法应用于来自16个捐赠者和25个样本的8种不同组织类型，产生了一个包含209,126个核图谱的跨组织图谱，他们用条件变异自动编码器整合了不同的组织、捐赠者和实验室方法。利用由此产生的跨组织图谱，研究人员突出了组织驻留细胞群的共同和组织特异性特征，确定可能有助于单基因疾病的神经肌肉、代谢和免疫成分的细胞类型以及参与其病理的生物过程，并确定可能成为全基因组关联研究分析的复杂性状的疾病机制基础的细胞类型和基因模块。
据介绍，想要了解基因在平衡状态和疾病中的功能和调控，需要了解基因表达的细胞和组织环境。
附：英文原文
Title: Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function
Author: Gkcen Eraslan, Eugene Drokhlyansky, Shankara Anand, Evgenij Fiskin, Ayshwarya Subramanian, Michal Slyper, Jiali Wang, Nicholas Van Wittenberghe, John M. Rouhana, Julia Waldman, Orr Ashenberg, Monkol Lek, Danielle Dionne, Thet Su Win, Michael S. Cuoco, Olena Kuksenko, Alexander M. Tsankov, Philip A. Branton, Jamie L. Marshall, Anna Greka, Gad Getz, Ayellet V. Segrè, Franois Aguet, Orit Rozenblatt-Rosen, Kristin G. Ardlie, Aviv Regev
Issue&Volume: 2022-05-13
Abstract: Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.
DOI: abl4290
Source: https://www.science.org/doi/10.1126/science.abl4290