Technolgy Implementation

项目摘要：技术实施 此提案是斯坦福大学基因组技术中心资助的延续申请。全基因组测序（WGS）的承诺现在已经实现，SGTC在序列自动化和高通量寡核苷酸合成方面率先取得了许多技术突破，使其成为现实。转化基因组医学仍然存在两大挑战。第一，人类生物体不是一个单一的基因组，而是一组基因组略有不同的细胞，这些变异在疾病中往往非常重要。第二个是，并非基因组的所有区域在致病潜力方面都是等同的，或者同样适合测序。在这第三层的建议。技术实施，我们将专注于使我们在SGTC开发的技术能够为更广泛的生物医学研究人员和临床医生社区所用。我们已经开发了几种新技术，能够选择性地捕获非常小的细胞群体和池中高度多重的基因组靶区域，并以非常高保真的方式对其进行测序。成功的实施要求该技术：1）稳健和可重复，在转化和临床研究中实际实施的障碍低; 2）成本低，以便经济地进行大人群的临床研究。我们将应用靶向重测序方法来识别癌症中罕见的遗传变异，并为移植提供准确的HLA分型，以及为临床样本的成本效益分析量身定制的转录组微阵列方法，以研究基因表达变化。这些努力的结果将使生物医学研究人员和临床医生能够为每个人提供个性化治疗，从而提高患者护理的质量。

Project Summary: Technology Implementation This proposal is a renewal application for the Stanford Genome Technology Center Grant. The promise of Whole Genome Sequencing (WGS) is now realized, and SGTC has pioneered many of the technological breakthroughs in sequence automation and high-throughput oligonucleotide synthesis that have made this a reality. Two big challenges in translational genomic medicine remain. The first is that the human organism is not a single genome, but a collection of cells with slightly varying genomes, and those variations are often very important in disease. The second is that not all regions of the genome are equivalent in disease causing potential or equally amenable to sequencing. In this third tier of the proposal. Technology Implementation, we will focus on making technologies that we have developed at SGTC accessible to a wider community of biomedical researchers and clinicians. We have developed several new technologies that are able to selectively capture highly multiplex, targeted regions ofthe genome in very small cell populations and in pools, and sequence them with very high fidelity. Successful implementation requires that the technology be: 1) robust and reproducible with low barriers for practical implementation in translational and clinical studies; and 2) low cost, such that clinical studies of large populations are done economically. We will apply targeted resequencing methods to identify rare genetic variants in cancer and provide accurate HLA typing for transplantation, and a transcriptome microarray method tailored for the cost-effective analysis of clinical samples to investigate gene expression changes. The resulting discoveries from these efforts will improve the quality of patient care by enabling biomedical researchers and clinicians to personalize treatments to each individual.