Cancer Genomics Technology Development

微阵列技术的最新进展与高分辨率微阵列的发展有关，它可以以极高的分辨率绘制DNA拷贝数的基因组改变和结构变异。我们以这种方式将高分辨率阵列应用于几个系统，并将该技术应用于DNase I超敏感位点的定位。最近，我们已经证明它们可以用来绘制复制的DNA起源。我们还通过将样品类型扩展到福尔马林固定样品、石蜡包埋样品、流动分选原代细胞和细针抽吸来突破检测的极限。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，并且正在继续扩展对这种材料的分析，以用于更广泛的基因组技术。目前的工作主要是针对下一代测序技术的实施。这些方法主要依赖于在测序反应中产生序列成像的DNA分子阵列。我们正在研究将这些方法用于大rna和小rna的基因表达谱分析，用于检测基因组重排、突变，以及用于测量染色质修饰、dna酶I超敏感位点和转录因子定位。这项工作的一个主要部分是开发一个强大的计算环境，可以用来分析由这项工作产生的大量序列数据。虽然这是一个具有挑战性的过程，但它最终将产生一个流线型的分析管道，其中多个基于序列的分析将很容易集成，并且不受阵列平台特定工件的影响。我们的计算工作的具体目标包括管道的优化，以处理序列数据的染色质分析，染色体重排，基因表达和突变检测。我们目前正致力于寻找新的方法，将测序工作的目标定位于基因组中由基因组成的一小部分，以便能够对单个样本中的数千个基因进行测序，并以互补的方式对数百个样本中的几个关键基因进行测序。这些目标是在成千上万的合成寡核苷酸的帮助下完成的，这些寡核苷酸被用来靶向基因组的所需部分。

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.