Understanding Functional and Medical Impact of Genetic Variation

高通量测序（HTS）技术，如Illumina HiSEQ和Life technologies的SOLiD，每周能够对多个人类基因组进行测序，每个基因组的成本约为5000美元。虽然分析由测序机生成的原始数据（reads）来重建原始基因组仍然是一个重大的计算挑战，但在过去几年中，HTS数据的校准和组装方法的准确性有了显著提高，用于识别单核苷酸多态性（snp）、插入/删除（Indels）和拷贝数变异（cnv）的标准化管道开始出现。人类基因型的精确重建使得大规模的种群测序项目成为可能，比如千人基因组计划。然而，由于难以在重建的人类基因型中确定引起疾病的变异，HTS用于医疗应用受到了阻碍。虽然任何两个人的基因组都有99.9%的相似度，但它们也包含数百万的差异。在NSERC发现基金的资助下，我将开发一个研究项目，以更好地理解基因组变异，包括开发有助于识别功能性基因组变异的方法，以及推进Ciona savignyi作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.