Key nodes in the T-cell developmental gene regulatory network

描述(申请人提供)：这个项目是利用最近的进展，可以帮助打破基因网络电路，调节T细胞发育的关键阶段。T细胞发育是从多能干细胞的生理池开始的细胞命运选择机制的一个模型。哺乳动物的T细胞发育可以高度精细地剖析谱系承诺的过程，因为在这个系统中，人们可以高纯度地分离出具有渐进程度的发育潜力限制的中间前体细胞。优秀的体外T谱系分化系统使整个谱系选择过程能够以一种开放的、实验可及的方式发生。特异性基因敲除实验还鉴定了一组T细胞规范所需的转录因子，包括GATA-3和E蛋白。基于在短期转录因子扰动实验中测量的基因调控效应，我们发表了T细胞发育的临时基因网络模型。然而，为了解释承诺过程的性质，在网络中需要三个函数，其中代理是未知的。这一建议是基于最近的两项进展，我们预测这两项进展现在将使我们有可能解释网络中的关键功能。这使我们能够看到，这一过程由两个可分离的阶段组成，第一个阶段由从干细胞前体遗传的调节因子主导，第二个阶段由T细胞相关因子集主导。首先，我们发现Bcl11b是长期寻找的T细胞特异性负调控成分，需要它将细胞从第一阶段转移到第二阶段。只有当第一阶段结束时，Bcl11b才被激活，然后需要允许承诺和关闭第二阶段的干细胞相关调控基因。第二，我们已经产生了一个主要的资源：对整个T细胞规范过程中五个阶段的转录组和全基因组表观遗传标记变化的全面调查。因此，我们可以完成所有在T细胞承诺过程中动态调节的基因的鉴定，确定几乎所有发生主动调节变化的顺式调节元件的候选基因，并将调节状态标记与特定转录因子结合的位点相关联以预测功能。我们假设Bcl11b的表达是在第一阶段成功激活第一波T细胞调节因子的读数，当过渡到第二阶段时，包括GATA-3和E蛋白在内的先前表达的因子然后重新聚焦它们的功能以启动新的T细胞特异性基因。使用Bcl11b作为分裂T细胞承诺过程的楔子，我们将首先确定在第一阶段完成时启动Bcl11b自身的顺式和反式元件。通过在正常和Bcl11b突变细胞中的ChIPseq作图，我们还将确定E蛋白和GATA-3的靶点结合和相关的组蛋白修饰如何从第一阶段转移到第二阶段。然后，我们将使用功能获得和损失来测试E蛋白和GATA-3的第一阶段或第二阶段相互作用伙伴如何导致其部署的特定转变。

DESCRIPTION (provided by applicant): This project is to exploit recent advances that can help break open the gene network circuitry that mediates a pivotal stage in T cell development. T cell development is a model for the mechanism of cell fate choice starting from a physiological pool of multipotent stem cells. Mammalian T-cell development permits highly refined dissection of the process of lineage commitment, because in this system one can isolate intermediate precursors with progressive degrees of developmental potential restriction in high purity. Excellent in vitro systems for T-lineage differentiation enable the whole lineage choice process to occur in an open, experimentally accessible way. Specific gene knockout experiments have also identified a group of transcription factors needed for T-cell specification, including GATA-3 and E proteins. Based on gene regulatory effects measured in short-term transcription factor perturbation experiments, we have published a provisional gene network model for T-cell development. However, to explain the properties of the commitment process, three functions were needed in the network for which the agents were not known. This proposal is based on two very recent advances which we predict will now make it possible to account for the crucial functions in the network. These enable us to see that the process consists of two separable phases, the first dominated by regulatory factors inherited from the stem-cell precursor, the second dominated by a T-cell associated factor set. First we found that Bcl11b is the long-sought T-cell specific negative regulatory component that is needed to shift cells from phase 1 to phase 2. Bcl11b is turned on only as phase 1 ends, then needed to allow commitment and to turn off the stem-cell associated regulatory genes for phase 2. Second, we have generated a major resource: a full survey of transcriptome and genome-wide epigenetic marking changes across five stages throughout the T-cell specification process. We can thus complete identification of all genes dynamically regulated during T-cell commitment, identify candidates for nearly all cis-regulatory elements where active regulatory change occurs, and correlate regulatory status marks with sites for specific transcription factor binding to predict function. We hypothesize that Bcl11b expression is a readout for successful activation of a first wave of T-cell regulators in phase 1, and that when transition to phase 2 occurs, previously expressed factors including GATA-3 and E proteins then refocus their functions to turn on new T-cell specific genes. Using Bcl11b as a wedge to split the T-cell commitment process, we will first identify the cis- and trans-elements that turn Bcl11b itself on at the completion of phase 1. Using ChIPseq mapping in normal and Bcl11b mutant cells, we will also determine how the target site binding and associated histone modifications of E proteins and GATA-3 may shift from phase 1 to phase 2. We will then use gain and loss of function to test how phase 1 or phase 2 interaction partners of E proteins and GATA-3 can cause specific shifts in their deployment.