Understanding Functional and Medical Impact of Genetic Variation

高通量测序（HTS）技术，如Illumina HiSEQ和Life Technologies的SOLiD，每周能够以约5，000美元/基因组的成本对多个人类基因组进行测序。虽然分析测序机生成的主要数据（读数）以重建原始基因组仍然是一个重大的计算挑战，但HTS数据比对和组装方法的准确性在过去几年中已显着提高，并且用于识别单核苷酸多态性的标准化管道（SNP）、插入/缺失（Indels）和拷贝数变体（CNVs）开始出现。人类基因型的精确重建使得大规模的人口测序项目成为可能，例如1000个基因组计划。然而，HTS在医学应用中的应用受到难以在重建的人基因型内鉴定致病变体的阻碍。虽然任何两个人类基因组都有99.9%的相似性，但它们也包含数百万的差异。在NSERC发现资助下，我将开发一个研究项目，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，以及将Ciona savignyi作为群体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.