Systems variation underlying the genetics of aging

项目摘要 在美国，老龄化是目前慢性病最重要的相关因素。一根本性的问题 是衰老本身是疾病的原因，还是衰老是失败的普遍积累的结果， 在许多构成正常功能基础的复杂系统中， 这是这种失败的最极端形式。从系统生物学的角度来看，这个问题可能是 表述为与衰老相关的复杂功能调节网络的退化是否是由 由有限的一组中心组件/节点产生，或者与衰老相关的衰退是否由以下因素产生 跨整个网络的异构故障，从而导致不可避免地跨越关键弱点 阈值我们的目标是通过对特定年龄变化的全面网络分析来验证这些假设 在基因表达和蛋白质丰度使用线虫作为模型系统。 具体来说，我们的目标是（1）确定细胞内基因调控网络的年龄特异性变化， 解决方案，定义与寿命和核心 （2）使用自然遗传变异系统地干扰特定年龄的 监管网络，以确定监管结构和因果关系， 网络，和（3）测试功能假说的紧急结构的年龄特定的监管 网络，并将网络属性与寿命的个体差异联系起来，使用敲除和过度- 表达构建体。我们的方法有三个独特的要素。首先，我们使用微流体技术， 在细胞和亚细胞分辨率水平上对基因表达报告进行成像， 方法是组织特异性的。因为这种方法是高通量和非破坏性的，这些成像 实验还将告知网络的时间动态。第二，我们利用自然的遗传变异 再加上全基因组测序，首先扰乱网络结构，然后绘制遗传因果关系， 从而允许建立跨网络的方向性。第三，我们实现了这一高水平的 通过对已经被分类的样品进行批量分离分析（极端QTL）， 差异基因表达，寿命和健康生物标志物使用定制设计的微流体装置。 这些方法将使我们能够重建组织特异性年龄相关的调控网络， 检查和功能验证网络结构和功能变化的紧急特性， 衰老，并将这些变化与寿命的个体差异结合起来。

PROJECT SUMMARY Aging is currently the most important correlate of chronic illness in the United States. A fundamental question is whether aging is itself causal of disease or if aging is the result of generalized accumulation of failures among the many complex systems that underlie normal function, with the diseases associated with old age simply being the most extreme form of this failure. From a systems biology perspective, this question can be phrased as whether the degradation in complex functional regulatory networks associated with aging is caused by a limited set of central components/nodes or whether aging-associated decline is generated by heterogeneous failure across the entire network which then leads to an inevitable crossing of a critical frailty threshold. We aim to test these hypotheses using a comprehensive network analysis of age-specific changes in gene expression and protein abundance using the nematode Caenorhabditis elegans as a model system. Specifically, we aim to (1) determine age-specific changes in the gene regulatory network at a cellular resolution, defining subcomponents that are specifically correlated with lifespan and central healthspan measures, (2) use natural genetic variation to systematically perturb the age-specific regulatory network in order to determine the regulatory structure and causal connections within the network, and (3) test functional hypotheses about the emergent structure of the age-specific regulatory network and relate network properties to individual variation in longevity, using knockouts and over- expression constructs. Our approach has three unique elements. First, we use microfluidic techniques to image gene expression reporters at a cellular and sub-cellular level of resolution, allowing our network approaches to be tissue specific. Because this approach is high-throughput and nondestructive, these imaging experiments will also inform the temporal dynamics of the networks. Second, we use natural genetic variation coupled with whole genome sequencing to first perturb network structure and then map genetic causation, thereby allowing directionality across the network to be established. Third, we achieve this high level of mapping precision by conducting bulk segregant analysis (extreme QTL) on samples that have been sorted for differential gene expression, longevity and healthspan biomarkers using custom-designed microfluidic devices. These approaches will allow us to reconstruct the tissue-specific age-associated regulatory network, to examine and functionally validate emergent properties of changes in network structure and function during aging, and to couple these changes to individual variation in longevity.