Using the Transcriptome for SNP and Gene Annotation

描述（由申请人提供）： 虽然我们强烈支持NIH在数据共享方面的举措，但我们一直认为，仅共享基因组研究的原始数据是不够的。在今天的基因组研究中产生的大量数据产生了更大规模的结果，这些结果需要比通常实际情况更仔细的审查，除非通过使用复杂的数据库。因此，我们投入了大量资源开发成果数据库（例如，见：www.scandb.org），并向公众开放。SCAN数据库（SNP和拷贝数ANnotation）允许用户按SNP、基因和区域查询我们的转录组研究结果，并可用于用功能信息注释SNP，包括潜在的eQTL（表达数量性状基因座）功能。我们用SCAN进行的初步研究表明，与复杂性状相关的SNP更可能是eQTL，而不是从高密度SNP基因分型平台提取的次要等位基因频率匹配的SNP。这些结果在性状相关SNP和eQTL的广泛定义（p值范围为10-4至10-8）和广泛的复杂性状表型中是稳健的。我们现在建议扩展SCAN数据库，以包括芝加哥大学对广泛的人体组织进行的转录组关联研究的结果，并继续开发软件工具，以最大限度地利用该数据库。这些努力是由我们几乎完全沉浸在许多不同复杂性状的基因型与表型相关的研究（以及开发基因型与表型相关的方法）中所告知的。因此，我们的具体目标是：1）扩展SCAN数据库，以服务于肝脏、脑脂肪组织和骨骼肌中的转录组研究结果，以及来自GTEx的转录组研究结果和我们目前服务的淋巴母细胞系中的研究结果;（二）为了增强我们已经开发的用于SCAN数据库的新软件工具，以使用转录组关联结果来促进（3）发展以GxG互作和nQTL（network QTLs）为重点的遗传变异功能研究新方法。 公共卫生相关性： 长期以来，我们一直致力于公共结果数据库的开发（参见，例如：www.scandb.org），使我们能够以促进进一步发现研究的方式提供大量基因组研究结果。我们的项目将允许用户查询各种人体组织中转录组关联研究的结果，并使用这些信息来发现和更好地表征复杂性状的遗传风险因素。

DESCRIPTION (provided by applicant): While we are strongly supportive of NIH initiatives in data sharing, we have long believed that it is insufficient to share only the raw data from genomic studies. The massive amounts of data created in today's genomic studies generate even more massive results that merit more careful scrutiny than is generally practical except through the use of sophisticated databases. Thus, we have devoted substantial resources to developing results databases (see, for example, ://www.scandb.org) that we make publicly available. The SCAN database (SNP and Copy number ANnotation) allows users to query results of our transcriptome studies by SNP, by gene and by region, and can be used to annotate SNPs with information on function, including potential eQTL (expression Quantitative Trait Locus) function. Our preliminary studies with SCAN have revealed that SNPs associated with complex traits are more likely to be eQTLs than minor-allele-frequency matched SNPs drawn from high-density SNP genotyping platforms. These results are robust across a wide range of definitions for trait-associated SNPs and eQTLs (p-values ranging from 10-4 to 10-8), and across a broad range of complex trait phenotypes. We now propose to extend the SCAN database to include results of transcriptome association studies being conducted at the University of Chicago on a broad range of human tissues and to continue to develop software tools to maximize the utility of this database. These efforts are informed by our near-complete immersion in studies relating genotype to phenotype (and in developing methods for relating genotype to phenotype) for many different complex traits. Thus, our specific aims are: 1) to extend the SCAN database to serve results of transcriptome studies in liver, brain adipose tissue, and skeletal muscle in addition to the results of the transcriptome studies from GTEx and our studies in lymphoblastoid cell lines that are currently served; 2) to augment the novel software tools we have already developed for use with the SCAN database to use transcriptome association results to facilitate the identification of genetic risk factors for complex traits; and 3) to develop novel approaches for investigating the function of genetic variation with an emphasis on GxG interaction and nQTLs (network QTLs). PUBLIC HEALTH RELEVANCE: We have long been committed to the development of public results databases (see, for example ://www.scandb.org) that permit us to serve the massive results of genomic studies in a way that facilitates further discovery research. Our project will allow users to query results of transcriptome association studies in a variety of human tissues, and to use this information to discover and better characterize genetic risk factors for complex traits.