Title |
Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells
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Published in |
Giga Science, November 2015
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DOI | 10.1186/s13742-015-0091-4 |
Pubmed ID | |
Authors |
Liang Wu, Xiaolong Zhang, Zhikun Zhao, Ling Wang, Bo Li, Guibo Li, Michael Dean, Qichao Yu, Yanhui Wang, Xinxin Lin, Weijian Rao, Zhanlong Mei, Yang Li, Runze Jiang, Huan Yang, Fuqiang Li, Guoyun Xie, Liqin Xu, Kui Wu, Jie Zhang, Jianghao Chen, Ting Wang, Karsten Kristiansen, Xiuqing Zhang, Yingrui Li, Huanming Yang, Jian Wang, Yong Hou, Xun Xu |
Abstract |
Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line. We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins. Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers. |
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Canada | 1 | 13% |
South Africa | 1 | 13% |
United States | 1 | 13% |
Hong Kong | 1 | 13% |
Unknown | 4 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 50% |
Scientists | 3 | 38% |
Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 2 | 2% |
South Africa | 1 | <1% |
Sweden | 1 | <1% |
United Kingdom | 1 | <1% |
United States | 1 | <1% |
Unknown | 109 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 26 | 23% |
Student > Ph. D. Student | 25 | 22% |
Student > Bachelor | 11 | 10% |
Student > Master | 11 | 10% |
Other | 9 | 8% |
Other | 19 | 17% |
Unknown | 14 | 12% |
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Biochemistry, Genetics and Molecular Biology | 48 | 42% |
Agricultural and Biological Sciences | 24 | 21% |
Medicine and Dentistry | 7 | 6% |
Computer Science | 4 | 3% |
Immunology and Microbiology | 3 | 3% |
Other | 10 | 9% |
Unknown | 19 | 17% |