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单细胞转录多样性是发育潜能的标志
作者:小柯机器人 发布时间:2020/1/29 16:40:07

美国斯坦福大学Aaron M. Newman研究团队发现,单细胞转录多样性是发育潜能的标志。2020年1月24日,国际知名学术期刊《科学》发表了这一成果。

研究人员证实了一个简单而强大的发育潜能决定因素(每个细胞表达的基因数量),并利用这种转录多样性的度量方法来开发了计算框架(CytoTRACE),从而利用scRNA-seq数据预测分化状态。当应用于多种组织类型和生物体时,CytoTRACE的性能优于以前的方法,并且可以解析将近19000个带注释的基因集,从而解析52个实验确定的发育轨迹。此外,这个算法也促进了静态干细胞的鉴定,并揭示了有助于乳腺肿瘤发生的基因。因此,这项研究建立了一个发育潜能的关键RNA特征以及一个描绘细胞层级的平台。
 
据了解,单细胞RNA测序(scRNA-seq)是重建细胞分化轨迹的有力方法。然而,同时推断分化的状态和方向是具有挑战性的。
 
附:英文原文

Title: Single-cell transcriptional diversity is a hallmark of developmental potential

Author: Gunsagar S. Gulati, Shaheen S. Sikandar, Daniel J. Wesche, Anoop Manjunath, Anjan Bharadwaj, Mark J. Berger, Francisco Ilagan, Angera H. Kuo, Robert W. Hsieh, Shang Cai, Maider Zabala, Ferenc A. Scheeren, Neethan A. Lobo, Dalong Qian, Feiqiao B. Yu, Frederick M. Dirbas, Michael F. Clarke, Aaron M. Newman

Issue&Volume: 2020/01/24

Abstract: Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential—the number of expressed genes per cell—and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied to diverse tissue types and organisms, CytoTRACE outperformed previous methods and nearly 19,000 annotated gene sets for resolving 52 experimentally determined developmental trajectories. Additionally, it facilitated the identification of quiescent stem cells and revealed genes that contribute to breast tumorigenesis. This study thus establishes a key RNA-based feature of developmental potential and a platform for delineation of cellular hierarchies.

DOI: 10.1126/science.aax0249

Source: https://science.sciencemag.org/content/367/6476/405

期刊信息
Science:《科学》,创刊于1880年。隶属于美国科学促进会,最新IF:41.037