HIGH DENSITY MICROARRAYS WITH QUANTITATIVE QC/QA

描述(申请人提供)：DNA微阵列分析已成为一种广泛使用的遗传工具；然而，其庞大的规模给希望使用它的大多数实验室带来了质量控制和分析问题。这项建议的目的是通过识别和解决cDNA微阵列数据变异性的来源，促进该技术在基本假设驱动的研究中的应用。由于阵列本身是一个相当大的可变性来源，我们开发了一个允许预杂交阵列可视化的三色阵列平台。我们的直接标记方法将载玻片涂层、打印和封堵的评估与杂交分开，从而能够在杂交之前评估元件/阵列形态、表面DNA沉积/保留和背景水平。我们还开发了MATARRAY，这是一个用于混合图像处理和数据采集的软件包，它提供了每个阵列元素以及整个幻灯片的定量质量控制。总而言之，这些努力为有效管理微阵列技术和系统变异性的综合质量控制(QC)方法提供了基础。对于这一应用，我们将通过以下具体目标在这些初步工作的基础上再接再厉1)我们将研究可测量的杂交前图像质量参数与数据质量/重复性之间的关系，包括背景、斑点形态和结合探针的影响。将使用第三种染料来量化由限制边界探头引起的数据压缩，以便可以对来自次优点的数据进行归一化或过滤。2)我们将根据目标1中确定的参数开发杂交前阵列鉴定软件，该软件将包括探针板跟踪、可用于杂交的探针的量化以及阵列/元件形态。将开发利用第三种染料信息进行数据归一化和过滤的杂交后算法。3)我们改进的微阵列和分析平台将通过在动物系统中表达谱疾病的发展来验证。商业寡核苷酸和cDNA阵列将被用作参考平台，以评估我们方法的成本效益和价值。我们的成功将为希望进行基因表达研究的实验室提供一种准确、灵活、成本较低的商业阵列的替代方案。

DESCRIPTION (provided by applicant): DNA microarray analysis has become a widely used genetic tool; however, its massive scale creates quality control and analysis problems for most laboratories wishing to use it. The purpose of this proposal is to facilitate the application of this technology to fundamental hypothesis-driven research through the identification and resolution of the sources of cDNA microarray data variability. Since the array itself is a considerable source of variability we have developed a three-color array platform that allows prehybridization array visualization. Our direct labeling approach separates assessment of slide coating, printing and blocking from hybridization, enabling evaluation of element/array morphology, surface DNA deposition/retention, and background levels prior to hybridization. We have also developed Matarray, a software package for hybridized image processing and data acquisition that provides quantitative QC for each array element as well as the entire slide. Combined, these efforts provide the basis for an integrated quality control (QC) approach to effectively manage microarray technical and systematic variability. For this application we will build upon these initial efforts through the following specific aims 1) We will study the relationship between measurable prehybridization image quality parameters and data quality/reproducibility, including the influence of background, spot morphology, and bound probe. Data compression caused by limiting bound probe will be quantified using the third dye so that data derived from sub-optimal spots can either be normalized or filtered. 2) We will develop pre-hybridization array qualification software based upon parameters identified in aim 1, which will encompass probe plate tracking, quantification of probe available for hybridization, and array/element morphology. Post-hybridization algorithms will be developed that utilize third dye information for data normalization and filtering. 3) Our improved microarray and analysis platforms will be validated by expression profiling disease development in an animal system. The commercial oligonucleotide and cDNA arrays will be used as reference platforms to assess cost effectiveness and value of our approach. Our success will provide an accurate, flexible, lower cost alternative to commercial arrays for laboratories wishing to conduct gene expression studies.