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Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm |
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| Authors: | Hou Yong Song Luting Zhu Ping Zhang Bo Tao Ye Xu Xun Li Fuqiang Wu Kui Liang Jie Shao Di Wu Hanjie Ye Xiaofei Ye Chen Wu Renhua Jian Min Chen Yan Xie Wei Zhang Ruren Chen Lei Liu Xin Yao Xiaotian Zheng Hancheng Yu Chang Li Qibin Gong Zhuolin Mao Mao Yang Xu Yang Lin Li Jingxiang Wang Wen Lu Zuhong Gu Ning Laurie Goodman Bolund Lars Kristiansen Karsten Wang Jian Yang Huanming Li Yingrui Zhang Xiuqing Wang Jun |
| Institution: | 1 BGI-Shenzhen, Shenzhen, 518083, China 2 State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China 3 School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China 4 College of Life Sciences, Wuhan University, Wuhan 430072, China 5 CAS-Max Planck Junior Research Group, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences (CAS), Kunming, Yunnan 650223, China 6 Graduate School of Chinese Academy of Sciences, Beijing 100049, China 7 Department of Hematology, Peking University First Hospital, Beijing 100034, China 8 Pfizer Inc., San Diego, CA 92121, USA 9 Department of Biology, University of Copenhagen, DK-1165 Copenhagen, Denmark 10 The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, DK-1165 Copenhagen, Denmark |
| Abstract: | Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients. |
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