Understanding Functional and Medical Impact of Genetic Variation

高通量测序(HTS)技术，如Illumina HiSeq和Life Technologies的Solid，能够每周对多个人类基因组进行测序，每个基因组的成本约为5,000美元。虽然分析由测序机产生的原始数据以重建原始基因组仍然是一个巨大的计算挑战，但在过去几年中，HTS数据比对和组装方法的准确性已经显著提高，用于识别单核苷酸多态(SNPs)、插入/缺失(Indels)和拷贝数变体(CNV)的标准化管道开始出现。人类基因类型的准确重建使得大规模的人口测序项目成为可能，如1000基因组计划。然而，由于难以识别重建的人类基因类型中的致病变异，HTS在医疗应用中的使用一直受到阻碍。尽管任何两个人类基因组都有99.9%的相似性，但它们也包含着数百万的差异。根据NSERC的发现拨款，我将制定一项研究计划，以更好地了解基因组变异，包括开发有助于识别功能性基因组变异的方法，以及推动Ciona savignyi成为种群基因组学的模式生物。

High-throughput sequencing (HTS) technologies, such as Illumina HiSEQ and Life Technologies' SOLiD, are able to sequence multiple human genome each week at a cost of ~$5,000/genome. While the analysis of primary data - reads - generated by the sequencing machines to reconstruct the original genome remains a significant computational challenge, the accuracy of methods for alignment and assembly of HTS data have improved significantly over the last few years, and standardized pipelines for identifying Single Nucleotide Polymorphisms (SNPs), Insertion/Deletions (Indels) and Copy Number Variants (CNVs) are beginning to appear. The accurate reconstruction of human genotypes has allowed for large-scale population sequencing projects such as the 1000 Genomes Project. However the use of HTS for medical applications has been hindered by the difficulty of identifying disease causing variants within reconstructed human genotypes. While any two human genomes will be 99.9% similar, they also contain millions of differences. Under the NSERC Discovery grant I will develop a research program that will lead to a better understanding of genomic variation, including developing methodologies that will help identify functional genomic variation, as well as advancing Ciona savignyi as a model organism for population genomics.