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Probing Dynamics of The Human Genome by Single Cell Sequencing

通过单细胞测序探测人类基因组的动态

基本信息

批准号：
9304988
负责人：
PATRICIA PURCELL
金额：
$ 84.5万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-20 至 2019-03-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Every cell in our body has a genome that carries the blueprint of our lives. Our genome is dynamical, i.e., changing with time. Genomic instability gives rise to genetic variations among cells originating from the same lineage, particularly cancer cells. However, we have not yet been able to study such dynamics of genomes because tools are not available, despite the tremendous advances in the next generation of genome sequencing in the past few years. Single cell whole genome amplification and sequencing is highly desirable for characterizing such heterogeneity among cells. However, existing amplification methods, such as PCR or multiple displacement amplification (MDA), are severely limited by strong bias and artifacts such as chimeras. We have developed several strategies that can significantly reduce the bias and allow single cell quantification of genome and transcriptome. We have developed a new whole genome amplification method: Multiple Annealing and Looping Based Amplification Cycle (MALBAC), which greatly circumvents the above difficulties. It allows us to read out digitized copy number variations and identify unique single nucleotide polymorphisms with overall ~80% efficiency of a single cell. We were able to call SNVs with extremely low false positive rates and directly measure the genome-wide mutation rate for the first time. We have also developed a method for digital RNAseq, which will allow determination of a single cell transcriptome with single copy sensitivity and no amplification bias. Cancer is a genetic disease. There have been many theoretical models about the genesis of cancer that have been difficult to test experimentally. Single cell genome sequencing is the ultimate experiment. We propose to characterize the copy number and single nucleotide variations of one hundred individual cells from cancer tissues, from which we will be able to extract information regarding how genetic variations occur in real time in a solid

描述（由申请人提供）：我们身体的每个细胞都有一个基因组，它携带着我们生命的蓝图。我们的基因组是动态的，也就是说，随着时间的推移而变化。基因组的不稳定性导致来自同一谱系的细胞之间的遗传变异，特别是癌细胞。然而，尽管在过去的几年里下一代基因组测序取得了巨大的进步，但我们还没有能够研究基因组的这种动态，因为工具是不可用的。单细胞全基因组扩增和测序是非常理想的表征细胞间的这种异质性。然而，现有的扩增方法，如PCR或多重位移扩增（MDA），受到强烈偏见和嵌合体等伪影的严重限制。我们已经开发了几种策略，可以显著减少偏差，并允许基因组和转录组的单细胞量化。我们开发了一种新的全基因组扩增方法：基于多重退火和循环的扩增循环（MALBAC），极大地解决了上述困难。它使我们能够读出数字化拷贝数变化并识别独特的单核苷酸多态性，单个细胞的总体效率约为80%。我们能够以极低的假阳性率调用snv，并首次直接测量全基因组突变率。我们还开发了一种数字RNAseq方法，该方法将允许以单拷贝敏感性和无扩增偏倚来确定单细胞转录组。癌症是一种遗传性疾病。有许多关于癌症起源的理论模型很难通过实验来验证。单细胞基因组测序是终极实验。我们建议描述来自癌症组织的100个单个细胞的拷贝数和单核苷酸变异，从中我们将能够提取有关遗传变异如何在固体中实时发生的信息