Accurate and Precise Measurements of Transcription Changes from Small Samples

 描述（由申请人提供）：细胞的基于DNA的遗传密码首先通过高度调节的转录过程读入RNA。因此，在发育或疾病进展过程中如何调节转录是生物学中的一个基本问题，对基础研究和生物医学研究和应用具有重要意义。准确和精确地了解基因组中RNA产生的位置和强度以及这些在各种细胞反应中如何变化是理解转录调控机制的第一步。 在测量RNA产生时要克服的两个主要挑战是来自细胞内预先存在的RNA的背景信号，以及RNA产生中的确定性和随机性细胞间变异性，这可能在检查细胞群体时掩盖真实的转录特征。我们提出了一种方法，结合了Leighton Core和Suzanne Gaudet实验室的专业知识，以消除RNA生产测量中的这些误差来源。该方法有两个主要组成部分：1）重新设计一种技术，该技术独立于背景信号直接测量新的转录事件，使得它可以用于小细胞群体，以及2）测试经修改的技术的效率，以检测在首先通过其响应水平分选的纯细胞群体中充分研究的细胞响应期间的变化。 成功 第一个目标的实现将导致RNA产生的测定，其可以更容易地被更广泛的科学家使用，并应用于更广泛的实验系统，特别是应用于样本量有限的罕见患者样本。除了第一个目标带来的技术创新外，我们的第二个目标将揭示在对刺激做出反应期间，全基因组转录在细胞内和细胞之间协调的程度。从更好地理解转录程序对刺激的反应的调节的角度来看，我们将能够确定特定基因反应中的大部分变异性是独立的还是与其他基因的变异性协调。 虽然我们的探索性实验将集中在T细胞的细胞系模型对肿瘤坏死因子的反应的见解，我们开发的测量RNA产生的重新设计的方法将广泛适用于大多数生物实验系统。

 DESCRIPTION (provided by applicant): A cell's DNA-based genetic code is first read into RNA through the highly regulated process of transcription. How transcription is regulated during development or disease progression is therefore a fundamental question in biology that has important implications for basic research and for biomedical research and applications. Accurate and precise knowledge of the location and the intensity of RNA production in the genome and how these change during various cellular responses is the first step in understanding mechanisms of transcription regulation. Two major challenges to overcome when measuring RNA production are the background signal from pre-existing RNAs within the cell, and the deterministic and stochastic cell-to-cell variability in RNA production that can obscure the true transcriptional signatures when examining populations of cells. We propose an approach that combines the expertise of the laboratories of Leighton Core and Suzanne Gaudet to eliminate these sources of error in the measurements of RNA production. The approach has two main components: 1) re-engineer a technique that directly measures new transcription events independently of background signal such that it can be used with small cell populations, and 2) test the efficiency of the modified technique to detect changes during a well-studied cellular response in pure populations of cells that are first sorted by their level of response. Successful execution of the first aim will result in an assay of RNA production that can be much more easily used by a wider range of scientists and applied to a broader array of experimental systems, in particular to rare patient samples where the sample size is limited. In addition to the technical innovations brought about by the first aim, our second aim will reveal the extent to which genome-wide transcription is coordinated within cells and between cells in a population during response to stimuli. From the perspective of better understanding the regulation of transcriptional programs in response to stimuli, we will be able to ascertain whether most of variability in a particular gene's response is independent or coordinated with that of other genes. While our exploratory experiments will focus on insights for the response of a cell line model of T-cells to tumor necrosis factor, the re-engineered approach to measurements of RNA production that we develop will be broadly applicable to most biological experimental systems.