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首页> 外文期刊>PLoS Computational Biology >Construction and Validation of a Regulatory Network for Pluripotency and Self-Renewal of Mouse Embryonic Stem Cells
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Construction and Validation of a Regulatory Network for Pluripotency and Self-Renewal of Mouse Embryonic Stem Cells

机译:小鼠胚胎干细胞多能性和自我更新的监管网络的构建和验证。

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A 30-node signed and directed network responsible for self-renewal and pluripotency of mouse embryonic stem cells (mESCs) was extracted from several ChIP-Seq and knockdown followed by expression prior studies. The underlying regulatory logic among network components was then learned using the initial network topology and single cell gene expression measurements from mESCs cultured in serum/LIF or serum-free 2i/LIF conditions. Comparing the learned network regulatory logic derived from cells cultured in serum/LIF vs. 2i/LIF revealed differential roles for Nanog, Oct4/Pou5f1, Sox2, Esrrb and Tcf3. Overall, gene expression in the serum/LIF condition was more variable than in the 2i/LIF but mostly consistent across the two conditions. Expression levels for most genes in single cells were bimodal across the entire population and this motivated a Boolean modeling approach. In silico predictions derived from removal of nodes from the Boolean dynamical model were validated with experimental single and combinatorial RNA interference (RNAi) knockdowns of selected network components. Quantitative post-RNAi expression level measurements of remaining network components showed good agreement with the in silico predictions. Computational removal of nodes from the Boolean network model was also used to predict lineage specification outcomes. In summary, data integration, modeling, and targeted experiments were used to improve our understanding of the regulatory topology that controls mESC fate decisions as well as to develop robust directed lineage specification protocols.
机译:从几个ChIP-Seq中提取一个负责节点的自我更新和多能性的30节点签名和定向网络,并进行敲除,然后进行表达以前的研究。然后,使用初始网络拓扑结构和在血清/ LIF或无血清2i / LIF条件下培养的mESC进行单细胞基因表达测量,从而了解网络组件之间的基本调节逻辑。比较从血清/ LIF与2i / LIF中培养的细胞获得的网络调控逻辑,发现Nanog,Oct4 / Pou5f1,Sox2,Esrrb和Tcf3具有不同的作用。总体而言,血清/ LIF条件下的基因表达比2i / LIF条件下的变化更大,但在两种条件下基本一致。单细胞中大多数基因的表达水平在整个种群中是双峰的,这激发了布尔建模方法。在计算机模拟中,从布尔动态模型中删除节点得出的预测已通过所选网络组件的实验性单项RNA组合和组合RNA干扰(RNAi)组合进行了验证。其余网络组件的定量RNAi表达后水平测量结果与计算机预测相吻合。从布尔网络模型的节点的计算去除还用于预测谱系规范结果。总而言之,数据集成,建模和目标实验被用于增进我们对控制mESC命运决定的调节拓扑的了解,并开发出可靠的有向谱系规范协议。

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