Probing Dynamics of The Human Genome by Single Cell Sequencing

描述(申请人提供)：我们身体中的每个细胞都有一个基因组，携带着我们生活的蓝图。我们的基因组是动态的，也就是说，随着时间的推移而变化。基因组的不稳定性会导致起源于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，但由于没有可用的工具，我们还无法研究基因组的这种动态。单细胞全基因组扩增和测序是表征细胞间这种异质性的非常理想的方法。然而，现有的扩增方法，如聚合酶链式反应或多重置换扩增，受到强烈的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，并允许对基因组和转录组进行单细胞量化。我们开发了一种新的全基因组扩增方法：基于多重退火环的扩增循环(MALBAC)，它极大地绕过了上述困难。它使我们能够读出数字化的拷贝数变异，并识别独特的单核苷酸多态，总体效率约为单个细胞的80%。我们能够调用假阳性率极低的SNV，并首次直接测量全基因组的突变率。我们还开发了一种数字RNAseq的方法，它将允许以单拷贝灵敏度和无扩增偏差来确定单细胞转录组。癌症是一种遗传病。关于癌症的起源有许多理论模型，但很难在实验中进行验证。单细胞基因组测序是最终的实验。我们建议表征100个来自癌症组织的单个细胞的拷贝数和单核苷酸变异，从中我们将能够提取关于遗传变异如何在固体中实时发生的信息

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