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Cell Res. 2016 Mar;26(3):304-19. doi: 10.1038/cr.2016.23. Epub 2016 Feb 23.

Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas.

Hou Y1, Guo H2,3,4, Cao C1, Li X1, Hu B1, Zhu P1,5, Wu X1,5, Wen L1, Tang F1,6,5,7, Huang Y1,5,8, Peng J2,3,4.

Author information

Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Beijing 100871, China.
Department of Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
Ninth School of Clinical Medicine, Peking University, Beijing 100038, China.
School of Oncology, Capital Medical University, Beijing 100038, China.
Peking-Tsinghua Center for Life Science, Beijing 100084, China.
Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing 100871, China.
Center for Molecular and Translational Medicine (CMTM), Beijing 100101, China.
College of Engineering, Peking University, Beijing 100871, China.


Single-cell genome, DNA methylome, and transcriptome sequencing methods have been separately developed. However, to accurately analyze the mechanism by which transcriptome, genome and DNA methylome regulate each other, these omic methods need to be performed in the same single cell. Here we demonstrate a single-cell triple omics sequencing technique, scTrio-seq, that can be used to simultaneously analyze the genomic copy-number variations (CNVs), DNA methylome, and transcriptome of an individual mammalian cell. We show that large-scale CNVs cause proportional changes in RNA expression of genes within the gained or lost genomic regions, whereas these CNVs generally do not affect DNA methylation in these regions. Furthermore, we applied scTrio-seq to 25 single cancer cells derived from a human hepatocellular carcinoma tissue sample. We identified two subpopulations within these cells based on CNVs, DNA methylome, or transcriptome of individual cells. Our work offers a new avenue of dissecting the complex contribution of genomic and epigenomic heterogeneities to the transcriptomic heterogeneity within a population of cells.

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