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

Public Health Relevance

We propose to use the latest single cell DNA sequencing technologies developed in our lab to study how our genomes change with time, which is important not only to fundamental biology, but also to understanding of cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
NIH Director’s Pioneer Award (NDPA) (DP1)
Project #
4DP1CA186693-04
Application #
9100676
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Li, Jerry
Project Start
2013-09-20
Project End
2018-07-31
Budget Start
2016-08-01
Budget End
2017-07-31
Support Year
4
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Harvard University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
082359691
City
Cambridge
State
MA
Country
United States
Zip Code
Blanshard, Robert C; Chen, Chongyi; Xie, Xiaoliang Sunney et al. (2018) Single cell genomics to study DNA and chromosome changes in human gametes and embryos. Methods Cell Biol 144:441-457
Tan, Longzhi; Xing, Dong; Chang, Chi-Han et al. (2018) Three-dimensional genome structures of single diploid human cells. Science 361:924-928
Tan, Longzhi; Xie, Xiaoliang Sunney (2018) A Near-Complete Spatial Map of Olfactory Receptors in the Mouse Main Olfactory Epithelium. Chem Senses 43:427-432
Chen, Chongyi; Xing, Dong; Tan, Longzhi et al. (2017) Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI). Science 356:189-194
Chapman, Alec R; He, Zi; Lu, Sijia et al. (2015) Single cell transcriptome amplification with MALBAC. PLoS One 10:e0120889
Huang, Lei; Ma, Fei; Chapman, Alec et al. (2015) Single-Cell Whole-Genome Amplification and Sequencing: Methodology and Applications. Annu Rev Genomics Hum Genet 16:79-102
Xie, Xiaoliang Sunney (2015) Single molecules meet genomics: pinpointing precision medicine. JAMA 313:2021-2
Tan, Longzhi; Li, Qian; Xie, X Sunney (2015) Olfactory sensory neurons transiently express multiple olfactory receptors during development. Mol Syst Biol 11:844