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发展有关，这些阵列可以以极高的分辨率绘制DNA拷贝数中的基因组变化和宪法变体。我们以这种方式将高分辨率阵列应用于多种系统，还将这项技术调整为DNase I超敏站点的映射。最近，我们证明它们可以用于绘制复制的DNA起源。 我们还努力通过将样品类型扩展到福尔马林固定的石蜡嵌入样品，流动排序的原始细胞和细针吸入术来推动检测限制。我们已经确定，可以从这些固定组织中获得有用的核酸制剂，并继续扩展对更广泛的基因组技术的分析。当前的努力主要是针对下一代测序技术的实施。这些方法主要取决于产生一系列DNA分子，这些DNA分子在测序反应过程中依次成像。我们正在研究这些方法用于大小RNA的基因表达分析，以检测基因组重排，突变以及测量染色质修饰，DNase I超敏位点和转录因子定位。这项工作的主要部分是开发强大的计算环境，该环境可用于分析这项工作生成的大量序列数据。 尽管这是一个具有挑战性的过程，但最终将产生简化的分析管道，在该管道中，基于多个序列的测定将易于集成并不含阵列平台的特定工件。我们计算工作的具体目标包括优化管道来处理染色质分析，染色体重排，基因表达和突变检测的序列数据。目前，我们正在采用新的方法来将测序努力靶向由基因组成的一小部分基因组，以便能够以各个样本和互补方式对数千个基因进行对数来对数百个样本中的一些关键基因进行测序。这些是借助数千种合成寡核苷酸来实现的，这些寡核苷酸用于针对基因组的所需部分。