Accurate and Precise Measurements of Transcription Changes from Small Samples

准确、精确地测量小样本的转录变化

基本信息

批准号：
9263973
负责人：
Leighton James Core
金额：
$ 24.72万
依托单位：
UNIVERSITY OF CONNECTICUT STORRS
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-04-19 至 2019-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9263973
关键词：
Adopted Alpha Cell Bar Codes Basic Science Biochemical Biochemistry Biological Biological Assay Biology Biomedical Research Biotin Cell Count Cell Line Cells Cues DNA Detection Development Disease Progression Engineering Error Sources Event Gene Expression Gene Expression Profile Gene Expression Regulation Genes Genetic Code Genetic Transcription Genome Goals Heterogeneity Inflammatory Investigation Jurkat Cells Knowledge Laboratories Libraries Location Measurement Measures Messenger RNA Methodology Methods Modeling Noise Patients Phase Population Positioning Attribute Preparation Process Production Protocols documentation RNA Reporter Genes Research Sample Size Sampling Scientist Series Signal Transduction Sorting - Cell Movement Source Stimulus System T-Lymphocyte TNF gene Techniques Testing Time Transcript Transcription Process Transcriptional Regulation Variant Work assay development base biological systems cytokine experimental study genome-wide global run on sequencing human disease improved innovation insight programs public health relevance reconstruction response success transcriptome sequencing

项目摘要

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.

描述（由申请人提供）：细胞基于 DNA 的遗传密码首先通过高度调控的转录过程被读入 RNA。因此，在发育或疾病进展过程中如何调控转录是生物学中的一个基本问题，对基础研究具有重要意义。对于生物医学研究和应用来说，准确、精确地了解基因组中 RNA 产生的位置和强度以及它们在各种细胞反应过程中的变化是理解转录调控机制的第一步。生产是背景信号我们提出了一种结合了 Leighton Core 实验室专业知识的方法，其中包括细胞内预先存在的 RNA，以及 RNA 产生的确定性和随机细胞间变异性，这些变异性可能会掩盖真实的转录特征。和 Suzanne Gaudet 消除了 RNA 产生测量中的这些误差源，该方法有两个主要组成部分：1）重新设计一种独立于背景信号直接测量新转录事件的技术，以便它可以用于小细胞群，和2) 测试改进技术的效率，以检测在经过充分研究的纯细胞群中的细胞反应期间的变化，这些细胞首先按其反应成功水平进行排序。第一个目标的实现将导致一种RNA生产分析方法，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，特别是样本量有限的稀有患者样本。除了第一个目标带来的技术创新之外，我们的第二个目标将从更好地理解转录调控的角度揭示细胞内和群体细胞之间全基因组转录的协调程度。程序响应刺激，我们将能够确定是否特定基因反应的大部分变异是独立的或与其他基因的反应协调的。虽然我们的探索性实验将重点关注 T 细胞细胞系模型对肿瘤坏死因子的反应，但我们开发的重新设计的 RNA 产生测量方法将广泛适用于大多数生物实验系统。

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

An improved auxin-inducible degron system preserves native protein levels and enables rapid and specific protein depletion.

改进的生长素诱导降解决定子系统保留了天然蛋白质水平，并能够快速、特异性地消耗蛋白质。

DOI：
发表时间：
2019-10-01
期刊：
影响因子：
10.5
作者：
Sathyan, Kizhakke Mattada;McKenna, Brian D;Anderson, Warren D;Duarte, Fabiana M;Core, Leighton;Guertin, Michael J
通讯作者：
Guertin, Michael J