Cancer Genome Anatomy Project's Gene Annotation Project

作为国家癌症研究所癌症基因组解剖计划（CGAP）的一部分，遗传注释计划（GAI）正试图扩大用于癌症研究的基于基因的遗传分析试剂的收集。使用一套序列分析工具（snpppipeline），我们通过检查公开可用的表达序列标签（EST）色谱图，确定了超过30,000个高概率的“候选”snp。已经开发了PCR检测来验证这些数据的一部分。利用92个独立的CEPH个体的汇总样本，通过MALDI-TOF质谱检测，已经验证了超过7000个snp。上述方法也适用于鼠标EST数据。利用这些数据，已经确定了超过16,000个候选小鼠snp。为了以一种对人类遗传社区有用的格式呈现遗传变异，我们基于CHLC/ABI Prism连锁标记集构建了一个集成的遗传/物理SNP图谱。参考标记的遗传图谱位置来自CHLC；物理地图位置来自GeneMap'98 Genebridge4辐射混合地图。这些地图的组织特异性和癌症特异性视图也可用。这些图谱允许选择具有特定表达模式的基因的snp。

As part of the National Cancer Institute's Cancer Genome Anatomy Project (CGAP) the Genetic Annotation Initiative (GAI) is attempting to expand the collection of gene-based genetic analysis reagents for cancer research. Using a set of sequence analysis tools, (the SNPpipeline) we have identified more than 30,000 high-probability "candidate" SNPs by examining publicly available expressed sequence tag (EST) chromatograms. PCR assays have been developed to validate a subset of these data. Using a pooled sample of 92 independent CEPH individuals, examined by MALDI-TOF mass spectrometry more than 7000 SNPs have been validated. The above approach has also been applied to mouse EST data. Using this data more than 16,000 candidate mouse SNPs have been identified. To present the genetic variants in a format useful for the human genetics community we have constructed an integrated genetic/physical SNP map based on the CHLC/ABI Prism linkage marker set. Genetic map positions of reference markers are from the CHLC; physical map positions are from the GeneMap'98 Genebridge4 radiation hybrid map. Tissue-specific and cancer-specific views of these maps are also available. These maps permit the selection of SNPs for genes with specific expression patterns. Through related CGAP infrastructure it is also possible to view the SNP data in other biologically relevant contexts. SNPs can be queried through the developing Gene Ontologies or through biologic pathways. These results have been integrated with those obtained from the TSC to give a comprehensive view of gene-based SNPs. A browser shows the location of each variant within the gene and provides information on whether the variant will result in a coding change. Motif models fit to the transcripts graphically indicate the location of functional characteristics of the gene. The significance of the variant's influence on the fit of these models is assessed and displayed. The integrated maps, a Java-based tool for viewing candidate SNPs in the context of EST assemblies, reagent information (including PCR primers and extension primers), and a SNP search engine are available at our website: http://cgap.nci.nih.gov. We provide access to our SNP detection software for non-commercial use.