Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas
Single-ceU 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 demonstra...
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| Published in | Cell research Vol. 26; no. 3; pp. 304 - 319 |
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| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
01.03.2016
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Single-ceU 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 om- ics 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 gen- erally 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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| AbstractList | 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. Single-ceU 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 om- ics 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 gen- erally 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. 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.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. |
| Author | Yu Hou Huahu Guo then Cao Xianlong Li Boqiang Hu Ping Zhu Xinglong Wu Lu Wen FuchouTang Yanyi Huang Jirun Peng |
| AuthorAffiliation | Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Beijing 100871, China Department of Surgery, Beifing Shijitan Hospital, Capital Medical University, Beijing 100038, China Ninth School of Clinical Medicine, Peking Univer- sity, Beijing 100038, China School of Oncology, Capital Medical University, Beijing 100038, China Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing 1008 71, China Peking- Tsinghua Center for Life Science, Beijing 100084, China Center for Molecular and Translational Medicine （CMTM）, Beijing 100101, China College of Engineering, Peking University, Beijing 100871, China |
| Author_xml | – sequence: 1 givenname: Yu surname: Hou fullname: Hou, Yu organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University – sequence: 2 givenname: Huahu surname: Guo fullname: Guo, Huahu organization: Department of Surgery, Beijing Shijitan Hospital, Capital Medical University, Ninth School of Clinical Medicine, Peking University, School of Oncology, Capital Medical University – sequence: 3 givenname: Chen surname: Cao fullname: Cao, Chen organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University – sequence: 4 givenname: Xianlong surname: Li fullname: Li, Xianlong organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University – sequence: 5 givenname: Boqiang surname: Hu fullname: Hu, Boqiang organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University – sequence: 6 givenname: Ping surname: Zhu fullname: Zhu, Ping organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Peking-Tsinghua Center for Life Science – sequence: 7 givenname: Xinglong surname: Wu fullname: Wu, Xinglong organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Peking-Tsinghua Center for Life Science – sequence: 8 givenname: Lu surname: Wen fullname: Wen, Lu organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University – sequence: 9 givenname: Fuchou surname: Tang fullname: Tang, Fuchou email: tangfuchou@pku.edu.cn organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Peking-Tsinghua Center for Life Science, Center for Molecular and Translational Medicine (CMTM) – sequence: 10 givenname: Yanyi surname: Huang fullname: Huang, Yanyi email: yanyi@pku.edu.cn organization: Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Peking-Tsinghua Center for Life Science, College of Engineering, Peking University – sequence: 11 givenname: Jirun surname: Peng fullname: Peng, Jirun email: pengjr@medmail.com.cn organization: Department of Surgery, Beijing Shijitan Hospital, Capital Medical University, Ninth School of Clinical Medicine, Peking University, School of Oncology, Capital Medical University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26902283$$D View this record in MEDLINE/PubMed |
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| Copyright | The Author(s) 2016 Copyright Nature Publishing Group Mar 2016 Copyright © 2016 Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences 2016 Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences |
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| DocumentTitleAlternate | Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas scTrio-seq reveals heterogeneity in HCC |
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| Keywords | DNA methylome HCC CNV scTrio-seq transcriptome |
| Language | English |
| License | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 |
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| Notes | 31-1568 scTrio-seq; CNV; transcriptome; DNA methylome; HCC Single-ceU 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 om- ics 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 gen- erally 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. ObjectType-Article-1 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-2 content type line 23 These two authors contributed equally to this work. |
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| SubjectTerms | 631/208/176/1988 631/61/212/2019 631/61/514/1948 692/4028/67/1504/1610/4029 Animals Biomedical and Life Sciences Carcinoma, Hepatocellular - genetics Cell Biology Deoxyribonucleic acid DNA DNA Copy Number Variations DNA Methylation DNA甲基化 Epigenesis, Genetic Epigenomics - methods Gene Expression Profiling - methods Genomics Genomics - methods Hep G2 Cells Heterogeneity Humans Life Sciences Liver Neoplasms - genetics Male Mice Middle Aged Original original-article Sequence Analysis, DNA Single-Cell Analysis Subpopulations Transcriptome 单细胞 哺乳动物细胞 异质性 测序方法 肝细胞癌 表观遗传学 转录组 |
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| Title | Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas |
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