生物
转录组
计算生物学
单细胞分析
单细胞测序
核糖核酸
突变体
RNA序列
突变
基因
细胞
遗传学
深度测序
基因表达
基因组
外显子组测序
作者
Alba Rodríguez-Meira,Gemma Buck,Sally‐Ann Clark,Benjamin J. Povinelli,Verónica Alcolea,Eleni Louka,Simon J. McGowan,Angela D. Hamblin,Nikolaos Sousos,Nikolaos Barkas,Alice Giustacchini,Bethan Psaila,Sten Eirik W. Jacobsen,Supat Thongjuea,Adam J. Mead
出处
期刊:Molecular Cell
[Elsevier BV]
日期:2019-02-11
卷期号:73 (6): 1292-1305.e8
被引量:310
标识
DOI:10.1016/j.molcel.2019.01.009
摘要
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for resolving transcriptional heterogeneity. However, its application to studying cancerous tissues is currently hampered by the lack of coverage across key mutation hotspots in the vast majority of cells; this lack of coverage prevents the correlation of genetic and transcriptional readouts from the same single cell. To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single cells from both genomic and coding DNA, in parallel with unbiased whole-transcriptome analysis. Applying TARGET-seq to 4,559 single cells, we demonstrate how this technique uniquely resolves transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasms (MPN) stem and progenitor cells, providing insights into deregulated pathways of mutant and non-mutant cells. TARGET-seq is a powerful tool for resolving the molecular signatures of genetically distinct subclones of cancer cells.
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