Cancer Genomics Technology Development

癌症基因组学技术开发

• 批准号: 8157624
• 负责人: PAUL S. MELTZER
• 金额: $ 83.36万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8157624
• 关键词: Address; Base Sequence; Bioinformatics; Biological Assay; Cancer Biology; Clinical; Constitutional; DNA; DNA Methylation; DNA Sequence; DNA Sequence Rearrangement; DNA mapping; DNA replication origin; Data; Deoxyribonuclease I; Detection; Development; Environment; Fine needle aspiration biopsy; Functional RNA; Future; Gene Expression; Genes; Genetic Transcription; Genome; Goals; Growth; Harvest; Hospitals; Human; Human Genome; Image; Individual; Laboratories; Maps; Measurement; Methodology; Methods; Microarray Analysis; Mutation; Mutation Detection; Nucleic Acids; Oligonucleotides; Pathology; Pathway interactions; Preparation; Process; Reaction; Research; Resolution; Role; Scientist; Site; Small RNA; Specimen; System; Technology; Variant; Work; base; cancer cell; cancer genomics; chromatin modification; improved; technology development; transcription factor

Recent progress in microarray technology has been related to the development of high resolution microarrays which can map genomic alterations and constitutional variants in DNA copy number at an extremely high resolution. We have applied high resolution arrays in this fashion to several systems and have also adapted this technology to the mapping of DNase I hypersensitive sites. Recently, we have demonstrated that they can be used to map DNA origins of replication. We have also worked to push the limits of detection by extending sample types to formalin fixed, paraffin embedded samples, flow sorted primary cells and fine needle aspirates. We have established that useful nucleic acid preparations can be obtained from these fixed tissues and are continuing to extend the analysis of this material for a wider range of genomic technologies. Current efforts have been directed primarily at the implementation of next generation sequencing technologies. These methods primarily depend on producing an array of DNA molecules which are sequentially imaged during the sequencing reaction. We are investigating the use of these methods for gene expression profiling for large and small RNAs, for the detection of genome rearrangements, mutations, and for the measurement of chromatin modifications, DNase I hypersensitive sites, and transcription factor localization. A major part of this effort is the development of a powerful computational environment which can be used to analyze the massive amount of sequence data which is generated by this work. Although this is a challenging process, it ultimately will yield a streamlined analysis pipeline in which multiple sequence based assays will be easy to integrate and free of array platform specific artifacts. Specific goals of our computational efforts include the optimization of pipelines to process sequence data for chromatin analysis, chromosome rearrangements, gene expression, and mutation detection. We are currently engaged in pursuing new approaches to target sequencing efforts to the small proportion of the genome composed of genes in order to be able to sequence thousands of genes in individual samples and in a complementary fashion, to sequence a few key genes in hundreds of samples. These are goals are being accomplished with the aid of thousands of synthetic oligonucleotides which are used to target the desired portion of the genome.

微阵列技术的最新进展与高分辨率微阵列的开发有关，该微阵列可以以极高的分辨率绘制基因组改变和DNA拷贝数的组成变体。我们已经以这种方式将高分辨率阵列应用于几个系统，并且还将这种技术应用于DNase I超敏位点的映射。最近，我们已经证明，它们可以用于映射DNA复制起点。 我们还努力通过将样本类型扩展到福尔马林固定、石蜡包埋样本、流式分选原代细胞和细针抽吸物来提高检测极限。我们已经确定，可以从这些固定的组织中获得有用的核酸制剂，并将继续扩展这种材料的分析，以用于更广泛的基因组技术。目前的努力主要针对下一代测序技术的实施。这些方法主要依赖于产生在测序反应期间顺序成像的DNA分子阵列。我们正在研究使用这些方法的基因表达谱的大小RNA，基因组重排，突变的检测，染色质修饰，DNase I超敏位点和转录因子定位的测量。这项工作的一个主要部分是开发一个强大的计算环境，可以用来分析大量的序列数据，这是由这项工作产生的。 虽然这是一个具有挑战性的过程，但它最终将产生一个简化的分析管道，其中基于多个序列的测定将易于集成，并且没有阵列平台特定的伪影。我们的计算工作的具体目标包括优化管道，以处理染色质分析，染色体重排，基因表达和突变检测的序列数据。我们目前正在寻求新的方法，将测序工作的目标定位于由基因组成的基因组的一小部分，以便能够对单个样品中的数千个基因进行测序，并以互补的方式对数百个样品中的几个关键基因进行测序。这些目标是在数千种用于靶向基因组的所需部分的合成寡核苷酸的帮助下实现的。