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Analysis of relationship between whole-genome transcriptome in human tissues and characteristics of the human genome

人体组织全基因组转录组与人类基因组特征的关系分析

基本信息

批准号：
18310134
负责人：
TSUNODA Tatsuhiko
金额：
$ 9.29万
依托单位：
The Institute of Physical and Chemical Research
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2006
资助国家：
日本
起止时间：
2006 至 2007
项目状态：
已结题

项目摘要

We have obtained whole-genome (40 million points; 1Gb) expression profiles of 22 tissues, neural stem cells, and cell-lines of the human. We also constructed a visualization tool for the transcriptome database acompanied with annotated genome-wide data, and analyzed characteristics of the transcriptome in the human genome. Because a higher quality set of RNA was required for the tiling array experiments compared to standard microarray ones, we originally developed an RNA purification methodology and a quality control system, with which we conformed that the RNA from all the samples were with high quality. Also, we developed/modified protocols for full-length RNA detection and cloning, and confirmed the expressions by qRT-PCR. For the expression profiling, we developed a new and widely applicable normalization method by optimizing parameters so that they would achieve the least false negative rate and the highest sensitivity on the basis of additional experimental data from gene-express … More ion microarrays. Using these, we newly found that most regions in the human genome were expressed in each tissue and that more than, 90% of transcriptome were from non-coding regions. We also identified dozens of thousands of transcipt products that expressed specifically in each tissue. By analysis with human genome annotation data, we found interesting relationship between the expression patterns, sequence conservation, and variation of polymorphisms in the human genome. These provide new methodologies for focusing regions for functional analyses. This database of genome-wide expression data in the human tissues is unique in the world. Researchers will be able to find disease-related loci including non-coding regions by comparing the expression data in human tissues with those from disease cells, e.g. cancer cells. Particularly, this database is useful for searching tissue specific disease-related molecules and also for prioritizing candidate molecules for therapies by looking at expression in normal tissues to avoid side effects. Less

我们已经获得了人类22种组织、神经干细胞和细胞系的全基因组（4000万点; 1Gb）表达谱。我们还为转录组数据库构建了一个可视化工具，并与注释的全基因组数据相结合，分析了人类基因组中转录组的特征。由于与标准微阵列实验相比，平铺阵列实验需要更高质量的RNA集，因此我们最初开发了RNA纯化方法和质量控制系统，通过该系统，我们确认来自所有样品的RNA都具有高质量。此外，我们开发/修改了全长RNA检测和克隆的方案，并通过qRT-PCR确认了表达。对于表达谱分析，我们开发了一种新的和广泛适用的归一化方法，通过优化参数，使它们在基因表达的额外实验数据的基础上达到最小的假阴性率和最高的灵敏度 ...更多信息离子微阵列利用这些，我们新发现人类基因组中的大多数区域在每个组织中表达，并且超过90%的转录组来自非编码区。我们还鉴定了在每个组织中特异性表达的数万种transcipt产物。通过对人类基因组注释数据的分析，我们发现了人类基因组中多态性的表达模式、序列保守性和变异之间的有趣关系。这些为功能分析的重点区域提供了新的方法。这个人类组织中全基因组表达数据的数据库在世界上是独一无二的。研究人员将能够通过比较人类组织中的表达数据与疾病细胞（例如癌细胞）的表达数据来找到疾病相关的基因座，包括非编码区。特别地，该数据库可用于搜索组织特异性疾病相关分子，并且还可用于通过观察正常组织中的表达来优先考虑用于治疗的候选分子以避免副作用。少