Systems-level identification of key regulators deciding immune cell state

摘要 了解免疫细胞发育的机制和识别免疫细胞发育和 分化对于开发新的和更有效的治疗方法至关重要。禁食 基因组技术的进步为研究人类基因组提供了前所未有的机遇 系统层面的免疫细胞。高通量测量中的噪声和 多组学数据的复杂性使其迫切需要开发新颖而强大的数据 用系统生物学方法进行综合分析以揭示潜在的调控 免疫系统的机制。我们提出了一种新的方法来整合多组学数据在 用于识别决定细胞状态和细胞命运的关键调控因子的遗传网络水平 (具体目标1)。我们将应用该方法系统地揭示调控机制。 在小鼠免疫系统中通过分析86个免疫细胞群(特定目标2)。我们会 还对人类和小鼠的免疫细胞进行了比较分析，以揭示 保守的免疫细胞规范调控代码(特定目标3)。我们将严格执行 评估计算分析的性能，通过实验确认 确定了关键的调节因子，并研究了它们在调节免疫细胞功能中的作用。一次 完成后，拟议的工作不仅将为综合分析 多组学数据，也是理解调控的具体机制见解 免疫系统的功能。

Abstract Understanding the mechanisms and identifying regulators of immune cell development and differentiation are critical for developing new and more effective therapeutics. The fast advancement of genomic technologies provides an unprecedented opportunity to study the immune cells at the system level. The noise in the high throughput measurements and the complexity of multiple omics data make it an urgent need for developing novel and powerful systems biology approach for integrative analysis to reveal the underlying regulatory mechanisms for immune system. We propose a new method to integrate multiomics data at the genetic network level for identification of key regulators deciding the cell state and cell fate (Specific Aim 1). We will apply the method to systematically uncover the regulatory mechanisms in the mouse immune system by analyzing 86 immune cell populations (Specific Aim 2). We will also perform comparative analysis of the human and mouse immune cells to reveal the conserved regulatory code for immune cell specification (Specific Aim 3). We will rigorously assess the performance of the computational analysis, experimentally confirm the importance of the identified key regulators and investigate their roles in regulating immune cell functions. Once complete, the proposed work will provide not only a general tool for integrative analysis of multiomics data but also specific mechanistic insights for understanding the regulation of immune system functions.