演讲嘉宾--汤富酬

汤富酬
汤富酬
tangfuchou@pku.edu.cn
北京大学生命科学院,研究员 北大-清华生命科学联合中心,研究员 北京大学BIOPIC,研究员
研究学习经历:

2010年回国在北京大学组建自己的实验室,主要从事人类早期胚胎发育的单细胞功能基因组学研究。在国际上率先系统发展了单细胞功能基因组学研究体系,建立了单细胞RNA-Seq转录组高通量测序技术,单细胞DNA甲基化组高通量测序技术,单细胞转录组、基因组、DNA甲基化组多组学平行高通量测序技术,并利用这一技术体系对人类早期胚胎进行了深入、系统的分析,发现了人类早期胚胎中基因表达网络的重要表观遗传学调控机理。在国际上首次对人类卵细胞进行了单细胞高通量基因组测序,阐明了人类卵细胞减数分裂的关键生物学特征,实现了利用单细胞高通量基因组测序技术进行植入前遗传学诊断、以大幅度提高试管婴儿成功率。在此基础上阐明了人类早期胚胎发育以及胚胎干细胞建系过程中的基因表达网络的动态变化,发现在早期胚胎以及胚胎干细胞建系过程中多能性细胞内可变剪接、细胞代谢等方面的模式转变。在国际上首次实现了对人类早期胚胎发育过程中DNA甲基化组的系统研究,揭示了人类早期胚胎DNA去甲基化过程的异质性以及其他关键特征,为人们提供了一个全面分析人类早期胚胎DNA甲基化调控网络的研究框架。在国际上首次分别在单细胞以及单碱基分辨率对人类原始生殖细胞的转录调控网络和DNA甲基化重编程过程进行了深入、系统的分析,加深了对人类原始生殖细胞的发育以及表观遗传重编程过程的认识。发表论文50余篇,其中20余篇论文是以通讯(或者共同通讯)作者身份发表,其中5篇研究论文发表在Cell,Nature,Science上。文章已经被引用3000多次。其中两项工作获评2014年度中国科学十大进展和2015年度中国科学十大进展。

近期发表论文:
  1. Zhou F, Li X, Wang W, Zhu P, Zhou J, He W, Ding M, Xiong F, Zheng X, Li Z, Ni Y, Mu X, Wen L, Cheng T, Lan Y, Yuan W*, Fuchou Tang*, Liu B*. Tracing haematopoietic stem cell formation at single-cell resolution. Nature, 533: 487-492 (2016) (*: Co-corresponding authors).
  2. Wen L*, Tang Fuchou*, How to catch rare cell types. Nature 52: 197-198 (2015) (*: Co-corresponding authors) (Preview).
  3. Guo F, Yan L, Guo H, Li L, Hu B, Zhao Y, Yong J, Hu Y, Wang X, Wei Y, Wang W, Li R, Yan J, Zhi X, Zhang Y, Jin H, Zhang W, Hou Y, Zhu P, Li J, Zhang L, Liu S, Ren Y, Zhu X, Wen L, Gao Y, Tang Fuchou*, Qiao J*. The Transcriptome and DNA Methylome Landscapes of Human Primordial Germ Cells. Cell 161: 1437-1452 (2015) (*: Co-corresponding authors).
  4. Zhang W, Li J, Suzuki K, Qu J, Wang P, Zhou J, Liu X, Ren R, Xu X, Ocampo A, Yuan T, Yang J, Li Y, Shi L, Guan D, Pan H, Suan S, Ding Z, Li M, Yi F, Bai R, Wang Y, Chen C, Yang F, Li X, Wang Z, Aizawa E, Goebl A, Soligalla RE, Reddy P, Esteban CR, Tang Fuchou*, Liu G* and Izpisua Belmonte JC*. A Human Stem Cell Model of Werner Syndrome Uncovers Heterochromatin Degeneration as an Aging Driver. Science 348: 1160-1163 (2015) (*: Co-corresponding authors).
  5. Wen L*, Tang Fuchou*. Charting a Map through the Cellular Reprogramming Landscape. Cell Stem Cell 16: 215-216 (2015) (*: Co-corresponding authors) (Preview).
  6. Guo H, Zhu P, Yan L, Li R, Hu B, Lian Y, Yan J, Ren X, Lin S, Li J, Jin X, Shi X, Liu P, Wang X, Wang W, Wei Y, Li X, Guo F, Wu X, Fan X, Yong J, Wen L, Xie SX, Tang Fuchou*, Qiao J*. The DNA methylation landscape of human early embryos. Nature 511: 606-610 (2014) (*: Co-corresponding authors).
  7. Wen L, Tang Fuchou*. Reconstructing Complex Tissues from Single-Cell Analyses. Cell 157: 771-773 (2014) (*: Corresponding author) (Preview).
  8. Hou Y, Fan W, Yan L, Li R, Lian Y, Huang J, Li J, Xu L, Tang Fuchou*, Xie XS*, Qiao J*. Genome Analyses of Single Human Oocytes. Cell 155:1492-1506 (2013) (*: Co-corresponding authors).
  9. Guo H, Zhu P, Wu X, Li X, Wen L, Tang Fuchou*. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Research 23: 2126-2135 (2013) (*: Corresponding author).
  10. Yan L, Yang M, Guo H, Yang L, Wu J, Li R, Liu P, Lian Y, Zheng X, Yan J, Huang J, Li M, Wu X, Wen L, Lao K, Li R*, Qiao J*, Tang Fuchou*. Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells. Nature Structural & Molecular Biology 20: 1131-1139 (2013) (*: Co-corresponding authors).
会议报告摘要:
Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas (4月22日 10:50 - 11:15 am)

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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第四届肿瘤基础和转化医学前沿国际研讨会