NOVEL METHODS FOR VAST INCREASE IN THROUGHPUT AND ACCURACY OF CIS-REG ANALYSES

描述(由申请人提供)：本申请涉及广泛的挑战领域(08)、基因组学和特定挑战主题08-HG-101“用于基因组序列中功能元件的高通量功能分析的技术和资源”。提出了一个为期两年的项目，旨在扩展、开发、延伸并在示范的基础上应用一种全新的高通量顺式调节分析方法。我们最近开发了这项新技术的初始组件，作为快速验证海胆胚胎基因调控网络模型的工具，并展示了其在促进发现和测量先前未知的顺式调控模块的定量活性方面的有效性，吞吐量高达传统方法的100倍。这种方法的基本原理是使用序列标记的“条形码”载体，这些载体可以在一次实验中大量引入并在以后去卷积。但仍有许多额外的衍生产品和额外的开发需要付诸实践，而挑战拨款计划提供了一个机会，可以在不久的将来启动一个“紧急计划”，并将这些机会带到网上。此外，到目前为止，我们开发的方法衡量的是数量顺式调控产出，而不是空间活动。我们提出了更多的技术发展，以产生比任何其他方法所能获得的更高质量的空间表达数据，并提出了一种高通量的方法来恢复在任何给定的空间调控状态下运行的大量顺式调控模块。该建议的具体目的包括将序列标签方法应用于纳米串技术，以允许同时评估100个不同顺式调节模块的活性；展示使用该方法同时获得大量顺式调节模块的时间输出简档；开发通过使用纳米串测量来确定未知顺式调节模块的空间表达简档的非常高精度的方法；以及调整用于普遍使用的高通量技术，以分离在生物体的给定时空区域中工作的大量未知集合的所有顺式调节模块。另外两点很重要：第一，没有先验的理由不能将这些技术转移到利用直接DNA注射进行基因转移的任何其他系统；第二，为了实现这些目标，我们必须建立一个新的研究小组。这将需要雇用更多的人员，在这方面，该提案的科学和组织方面都与美国国立卫生研究院倡议的目标相协调。这项工作是关于找到控制线的因果关系，这些控制线决定了如何根据基因组调控系统中编码的指令执行基本的生命过程。对于复杂疾病状态的一般解决方案，最有效的方法需要对它们的控制电路有扎实的了解。我们的实践必须超越努力改善结果，而不是改变原因。这项研究展示了在因果基因组控制系统中发现结构和功能的方法。

DESCRIPTION (provided by applicant): This Application addresses broad Challenge Area (08), Genomics, and Specific Challenge Topic 08-HG-101 "Technology and resources for high throughput functional analysis of functional elements in genomic sequences". A two year project is proposed to expand, to exploit, to extend, and to apply on a demonstration basis a completely novel approach to high throughput cis-regulatory analysis. We have very recently developed the initial component of this new technology as a tool for rapid validation of sea urchin embryo gene regulatory network models, and demonstrated its efficacy in facilitating the discovery and in measuring the quantitative activity of previously unknown cis-regulatory modules with a throughput of up to 100x that of traditional methods. The essential principle of this approach is use of sequence-tagged "barcoded" vectors which can be introduced together in large number in a single experiment and de-convolved later. But there remain many additional spinoffs and additional developments to be brought to practice, and the Challenge Grant program offers the opportunity to mount a "crash program" and bring these opportunities on line in the immediate future. In addition, the methods we have so far developed measure quantitative cis-regulatory output and not spatial activity. We propose additional technological developments to generate higher quality spatial expression data than obtainable by any other means and a high throughput method of recovering large sets of cis-regulatory modules operating in any given spatial regulatory state. The specific aims of this proposal include adapting the sequence tag method to NanoString technology to permit simultaneous assessment of activity of > 100 different cis-regulatory modules; demonstrate the use of this method to obtain temporal output profiles of large numbers of cis-regulatory modules simultaneously; develop a very high accuracy method of determining spatial expression profiles of unknown cis-regulatory modules by use of NanoString measurements; and tune for general use a high throughput technology for isolating all cis-regulatory modules of a large unknown set which operate in a given time-space domain of the organism. Two additional comments are important: first, there is no a priori reason why these technologies should not be transferrable to any other system in which gene transfer by direct DNA injection is utilized; and second, in order to accomplish these objectives we shall have to build a new research subgroup. This will require hiring additional personnel, and in this respect both the scientific and organizational aspects of the proposal synergize with the objectives of the A.R.R.A. NIH initiative. This work is about finding the causal lines of control that determine how fundamental life processes are executed according to the instructions encoded in the genomic regulatory system. The most powerful approach to general solutions to complex disease states requires solid understanding of their control circuitry. Our practice must get beyond struggling to ameliorate effects rather than altering causes. This research shows the way to discovery of structure and function in causal genomic control systems.