新技術實現對單細胞中基因表達動態的表徵
作者:
小柯機器人發布時間:2020/4/19 23:10:24
2020年4月13日,《自然—生物技術》雜誌在線發表了美國華盛頓大學Jay Shendure、Junyue Cao等研究人員的最新成果。他們開發了一個能夠表徵單細胞中基因表達動態的新技術。
研究人員提出了一種結合單細胞組合索引和信使RNA標記(Sci-fate)的方法,其使用組合細胞索引和新合成mRNA的4-硫尿苷標記,從而在單個細胞中同時分析完整和新的轉錄組。
研究人員使用Sci-fate研究了超過6000個培養的單細胞中的皮質醇反應。根據這些數據,研究人員量化了細胞周期和糖皮質激素受體激活的動態,並探討了它們的交叉點。最後,研究人員開發了推斷和分析細胞狀態轉換的軟體。他們認為,Sci-fate將廣泛適用於定量表徵各種系統中的轉錄動態。
據悉,基因表達程序隨著時間、分化和發育以及對刺激的響應而改變。但是,幾乎所有用於在單細胞中分析基因表達的技術都不能直接捕獲轉錄動態。
附:英文原文
Title: Sci-fate characterizes the dynamics of gene expression in single cells
Author: Junyue Cao, Wei Zhou, Frank Steemers, Cole Trapnell, Jay Shendure
Issue&Volume: 2020-04-13
Abstract: Gene expression programs change over time, differentiation and development, and in response to stimuli. However, nearly all techniques for profiling gene expression in single cells do not directly capture transcriptional dynamics. In the present study, we present a method for combined single-cell combinatorial indexing and messenger RNA labeling (sci-fate), which uses combinatorial cell indexing and 4-thiouridine labeling of newly synthesized mRNA to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. We used sci-fate to study the cortisol response in >6,000 single cultured cells. From these data, we quantified the dynamics of the cell cycle and glucocorticoid receptor activation, and explored their intersection. Finally, we developed software to infer and analyze cell-state transitions. We anticipate that sci-fate will be broadly applicable to quantitatively characterize transcriptional dynamics in diverse systems.
DOI: 10.1038/s41587-020-0480-9
Source: https://www.nature.com/articles/s41587-020-0480-9