TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells.

TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells.
复制标题

DOI:
10.1016/j.isci.2022.103806
复制
发表时间:
2022-02-18
期刊:
影响因子:
5.8
通讯作者:
Das S
Das S
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Cherbonneau F;Li G;Gokulnath P;Sahu P;Prunevieille A;Kitchen R;Benichou G;Larghero J;Domian I;Das S

文献摘要

参考文献

被引文献

相似文献

在特定的微环境中,在不需要细胞破坏的情况下,对基因表达的变化进行动态分析仍然具有挑战性。目前寻求在分子水平上询问基因表达的方法需要对细胞转录组进行采样,因此需要裂解细胞,从而阻止了细胞转录组的系列分析。为了解决这一未满足需求的领域,我们最近开发了一种技术,允许在不破坏细胞的情况下随时间进行转录组学分析。我们的方法TRACE-seq(使用测序在细胞外囊泡中捕获的转录组学分析)的特征在于细胞类型特异性转基因表达。它提供了细胞外囊泡内转录组的数据,提供了应激反应细胞转录组变化的准确表示。因此,表达TRACE的细胞的转录组可以随着时间的推移而被跟踪,而不会破坏源细胞,这是基础和转化生物学研究的许多领域的有力工具。使用RNA测序在细胞外囊泡中捕获转录组学分析使用该方法实现细胞和EV转录组的出色相关性响应于应激信号的基因表达变化的准确分析细胞生物学;组学;转录组学
Dynamic profiling of changes in gene expression in response to stressors in specific microenvironments without requiring cellular destruction remains challenging. Current methodologies that seek to interrogate gene expression at a molecular level require sampling of cellular transcriptome and therefore lysis of the cell, preventing serial analysis of cellular transcriptome. To address this area of unmet need, we have recently developed a technology allowing transcriptomic analysis over time without cellular destruction. Our method, TRACE-seq (TRanscriptomic Analysis Captured in Extracellular vesicles using sequencing), is characterized by a cell-type specific transgene expression. It provides data on the transcriptome inside extracellular vesicles that provides an accurate representation of stress-responsive cellular transcriptomic changes. Thus, the transcriptome of cells expressing TRACE can be followed over time without destroying the source cell, which is a powerful tool for many fields of fundamental and translational biology research. TRanscriptomic Analysis Captured in Extracellular vesicles using RNA-sequencing Excellent correlation of cellular and EV transcriptome using this method Accurate profiling of gene expression changes in response to stress signals Cell biology; Omics; Transcriptomics
DOI: 10.1080/20013078.2017.1286095
发表时间: 2017
影响因子: 16
作者:
Mateescu B;Kowal EJ;van Balkom BW;Bartel S;Bhattacharyya SN;Buzás EI;Buck AH;de Candia P;Chow FW;Das S;Driedonks TA;Fernández-Messina L;Haderk F;Hill AF;Jones JC;Van Keuren-Jensen KR;Lai CP;Lässer C;Liegro ID;Lunavat TR;Lorenowicz MJ;Maas SL;Mäger I;Mittelbrunn M;Momma S;Mukherjee K;Nawaz M;Pegtel DM;Pfaffl MW;Schiffelers RM;Tahara H;Théry C;Tosar JP;Wauben MH;Witwer KW;Nolte-'t Hoen EN
通讯作者: Nolte-'t Hoen EN
DOI: 10.1073/pnas.1521230113
发表时间: 2016-02-23
影响因子: 11.1
作者:
Kowal, Joanna;Arras, Guillaume;Thery, Clotilde
通讯作者: Thery, Clotilde
YTHDF2 通过直接招募 CCR4-NOT 去腺苷酶复合物来破坏含有 m(6)A 的 RNA 的稳定性。
DOI: 10.1038/ncomms12626
发表时间: 2016-08-25
影响因子: 16.6
作者:
Du, Hao;Zhao, Ya;He, Jinqiu;Zhang, Yao;Xi, Hairui;Liu, Mofang;Ma, Jinbiao;Wu, Ligang
通讯作者: Wu, Ligang
DOI: 10.1093/nar/gkv007
发表时间: 2015-04-20
影响因子: 14.9
作者:
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者: Smyth GK
DOI: 10.1073/pnas.1615375114
发表时间: 2017-03-07
影响因子: 11.1
作者:
Cao, Yuhong;Hjort, Martin;Melosh, Nicholas A.
通讯作者: Melosh, Nicholas A.