Improving INDEL Identification in Genomic Sequences

改进基因组序列中的 INDEL 识别

• 批准号: 7222429
• 负责人: RYAN E MILLS
• 金额: $ 4.4万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-30 至 2009-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7222429
• 关键词: clinical research; fasting; genome; human

DESCRIPTION (provided by applicant): This research project is focused on developing a comprehensive map of INDEL variation in the human genome and detecting these INDELs using microarray technology. We estimate over 1.6 million insertion and deletion mutations are prevalent in the genome, of which only a fraction have been presently identified. These INDELs are likely to be directly responsible for phenotypic differences in humans, including differences in physical traits, susceptibility to diseases, and physiological responses to the environment. This variation will be identified by improving our existing method for identifying INDELs from trace sequence data through increases of speed and accuracy. All available human traces will be obtained from the trace archive at NCBI and INDELs will be identified using this faster pipeline through comparison with the human genome reference sequence. A method will be developed to use full length genomic sequences as input into this pipeline, and this will then be used to analyze the Celera genome sequence for further INDEL discovery. The identified INDELs also will be compared to the chimp genome for identification of an ancestral allele, where possible. The distribution of these INDELs also will be examined, and rules for INDEL classification will be defined, in particular for troublesome classes such as repeat expansions. A set of microarray probes will be designed to validate a portion of the INDELs we have identified. Microarrays have been used previously with SNP detection and a similar theory of probe construction should be applicable to INDEL variation as well. These probes will then be analyzed on commercially-available custom microarray platforms. Hybridization temperatures and other conditions will be tested to identify optimal parameters. The INDELs chosen for this aim will consist of a wide variety of classes and lengths in order to test these methods with a broad spectrum of INDELs.

描述(申请人提供)：这项研究项目集中于开发人类基因组中Indel变异的全面图谱，并使用微阵列技术检测这些Indel。我们估计，基因组中普遍存在超过160万个插入和缺失突变，目前只发现了其中的一小部分。这些INDELs很可能直接导致人类的表型差异，包括身体特征、疾病易感性和对环境的生理反应的差异。这一变异将通过提高速度和准确性来改进我们现有的从痕迹序列数据中识别INDELs的方法来识别。所有可用的人类痕迹将从NCBI的痕迹档案中获得，INDELs将通过与人类基因组参考序列的比较，使用这一更快的管道来识别。将开发一种方法，将全长基因组序列作为输入到这条管道中，然后将用于分析Celera基因组序列，以便进一步发现Indel。在可能的情况下，还将把识别出的Indels与黑猩猩的基因组进行比较，以确定其祖先的等位基因。还将检查这些Indel的分布，并定义Indel分类规则，特别是对于诸如重复扩展等麻烦的类。一组微阵列探针将被设计来验证我们已经鉴定的部分INDELs。微阵列以前已经用于SNP检测，类似的探针构建理论也应该适用于Indel变异。然后，这些探针将在商业上可获得的定制微阵列平台上进行分析。将对杂交温度和其他条件进行测试，以确定最佳参数。为实现这一目标而选择的INDELs将由各种各样的类别和长度组成，以便用广泛的INDELs测试这些方法。