單細胞轉錄多樣性是發育潛能的標誌
作者：
小柯機器人發布時間：2020/1/29 16:40:07
美國史丹福大學Aaron M. Newman研究團隊發現，單細胞轉錄多樣性是發育潛能的標誌。2020年1月24日，國際知名學術期刊《科學》發表了這一成果。
研究人員證實了一個簡單而強大的發育潛能決定因素（每個細胞表達的基因數量），並利用這種轉錄多樣性的度量方法來開發了計算框架（CytoTRACE），從而利用scRNA-seq數據預測分化狀態。當應用於多種組織類型和生物體時，CytoTRACE的性能優於以前的方法，並且可以解析將近19000個帶注釋的基因集，從而解析52個實驗確定的發育軌跡。此外，這個算法也促進了靜態幹細胞的鑑定，並揭示了有助於乳腺腫瘤發生的基因。因此，這項研究建立了一個發育潛能的關鍵RNA特徵以及一個描繪細胞層級的平臺。
據了解，單細胞RNA測序（scRNA-seq）是重建細胞分化軌跡的有力方法。然而，同時推斷分化的狀態和方向是具有挑戰性的。
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
Science：《科學》，創刊於1880年。隸屬於美國科學促進會，最新IF：41.037