项目来源

美国卫生和人类服务部基金(HHS)

项目主持人

Li， Jerry

项目受资助机构

HARVARD UNIVERSITY

立项年度

2017

立项时间

未公开

项目编号

5DP1CA186693-05

研究期限

未知 / 未知

项目级别

国家级

受资助金额

845000.00美元

学科

Biotechnology; Cancer; Cancer Genomics; Clinical Research; Genetics; Human Genome;

学科代码

未公开

基金类别

Non-SBIR/STTR RPGs

关键词

未公开

参与者

PURCELL, PATRICIA

参与机构

NATIONAL CANCER INSTITUTE

项目标书摘要：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