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nature biotechnology:单细胞基因表达分析解密血液早期发育调控网络

来源:生物谷 2015-02-10 10:50

                                                           

      
2015年2月10日讯  /生物谷BIOON/  --近日,著名国际期刊nature biotechnology发表了英国科学家的一项最新研究成果,他们应用单细胞基因表达分析与计算方法描述了血液发育的转录调控网络。这项研究为分析器官发育的调控网络提供了一种可行的方法。
 
研究人员指出,重建调控器官发育的分子途经受限于缺少对胚胎祖细胞进行研究的方法,他们提出一种策略,通过对大量单细胞基因表达进行基于降维的扩散映射数据分析和用状态转换图合成数据网络来解决这一难题。研究人员应用这一方法研究小鼠胚胎造血发育,对E7.0和E8.5之间四个时间点取的3934个具有血液形成潜能的细胞使用单细胞基因表达分析,描述了中胚叶向血液方向分化的过程。然后将个体细胞状态转化用作输入信息形成单细胞网络合成工具,来建立一个针对血液发育的计算执行转录调控网络模型。研究人员应用几个模型预测Sox和Hox因子作用的结果都得到了实验验证。
 
综上所述,该文章应用单细胞基因表达分析和计算方法描述了血液发育的调控网络,表明单细胞分析结合计算方法描述器官发育能够揭示器官发育的转录调控网络。(生物谷Bioon.com)
 
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Decoding the regulatory network of early blood development from single-cell gene expression measurements
 
Victoria Moignard, Steven Woodhouse, Laleh Haghverdi, Andrew J Lilly, Yosuke Tanaka,Adam C Wilkinson, Florian Buettner, Iain C Macaulay, Wajid Jawaid, Evangelia Diamanti,Shin-Ichi Nishikawa, Nir Piterman, Valerie Kouskoff, Fabian J Theis, Jasmin Fisher &Berthold G?ttgens
 
Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.
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