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TRANSCRIPT
INDEX
1. IntroductionA. The single-cell concept
B. Relevance and advances in single-cell sequencing (SCS)
C. NGS-based single cell assays
2. Single-cell sequencingA. Single-cell Genome Sequencing (scDNA-seq)
B. Single-cell RNA Sequencing (scRNA-seq)
C. Key step: Cell isolation
3. ApplicationsA. Cancer
B. Neurobiology
4. Conclusions and future perspectives
5. References
1. The single-cell concept
Blainey et al., 2014 Eberwine et al., 2014
• Analysis of genomes at
the single-cell level is old
A single-cell genome image of polytene
chromosomes from insects from the 1882
monograph by Flemming
Individual cells of the
same phenotype
Identical functional units of a tissue or organ
But…
Single-cell DNA and RNA
sequencing
Heterogeneuscell states
System-level
function
2. Relevance and advances in
single-cell sequencing (SCS)
• According to Nature
Methods, it was the
Method of the Year in
2013.
C. Prevalence of publications
categorized by fields.
B. Histogram of the number of
publications in SCS over the
past 5 yearsWang et al., 2015
c. NGS-based single cell assays
Single-
cell
Single-cellgenomics
Single-celltranscriptomics
Single-cellproteomics
Single-cellepigenomics
Weaver et al., 2014
2. SINGLE-CELL SEQUENCING
TYPES
A. Single-cell Genome Sequencing (scDNA-seq)
B. Single-cell RNA Sequencing (scRNA-seq)
C. Key step: Cell isolation
•Analysis of the whole sequenceinformation from an individual cell usingNext-Generation Sequencing
Single-cellsequencing
Cell isolationDNA
extractionDNA
amplificationSequencing
LibrarySequencing Analysis
Cell isolationRNA
extractioncDNA
synthesiscDNA
amplificationSequencing
LibrarySequencing Analysis
A. Single-cell Genome
Sequencing (scDNA-seq)
Cellisolation
DNA extraction
DNA amplification
Sequencing Analysis
Micromanipulation
Fluorescent-activated
cell sorting (FACS)
Laser-capture
microdissection (LCM)
or
SequencingLibrary
B. Single-cell RNA Sequencing
(scRNA-seq)
Cell isolationRNA
extractioncDNA
synthesiscDNA
amplificationSequencing
LibrarySequencing Analysis
A. Cancer
Saadatpour et al., 2015 Sun et al., 2015
Single-cell sequencing of a tumor cellsAn overview of Single-Cell Cancer Genomics
a. Applications in cancer research
Navin, 2015
A. Resolving intratumor
heterogeneity
B. Investigating clonal
evolution in primary tumors
C. Studying invasion in early
stage cancers
D. Tracing metastatic
dissemination
E. Genomic profiling of
circulating tumor cells
F. Studying mutation rates
and mutated phenotypes;
a. Applications in cancer research
Navin, 2015
G. Understanding resistance
evolution to therapy
H. Understanding cancer
stem cells and cell
hierarchies
I. Studying cell plasticity and
epithelial-to-
mesenchymal transition
a. Applications in cancer research
B. Investigating clonal evolution in primary tumors
Single-cell processes in cancer:
a) transformation from a somatic cell into a tumor
cell;
b) clonal evolution that happens through selective
sweeps when single cells get driver mutations and
vary, conducting to intratumor heterogeneity;
c) single cells from the primary tumor intravasate
into the circulatory system and extravasate at far-
off organ sites to develop metastatic tumors;
d) the evolution of chemoresistance that takes
place when the tumor is eliminated but survived
by single tumor cells that harbor resistance
mutations and expand to rebuild the tumor mass
Navin et al., 2014
Wang et al., 2014
a. Applications in cancer research
Navin et al., 2015
In the first SCS study of
clonal evolution in ahuman tumor, SNS wasused to profile genomiccopy number inhundreds of singletumor cells from twobreast cancer patients,which revealed a
punctuated model ofcopy number evolution
Most SCS studies to datehave concentrated onintratumorheterogeneity andclonal evolution inprimary tumors
B. Neurobiology
Shapiro et al., 2013
Single-cell RNA-seq hasallowed the identificationof mosaicism in neurons
5. CONCLUSIONS AND FUTURE
PERSPECTIVES
• Single-cell genomics methods are quickly become essentialfor genomics and the rest of omics. It is new, but there areseveral discoveries and advances because of it, and in thefuture is going to obtain more results.
• Scale will growth, price will come down.
• Single cell perturbation and cell-cell interaction analysis couldbe possible.
• Techniques is being developed to engineer information intocells – spatial, temporal, lineage tagging.
• New analysis techniques are needed.
• The role of a cell is going to be more understandable (like in itsmicroenvironment).
5. CONCLUSIONS AND FUTURE
PERSPECTIVES
• Combined approaches are required: Architecture of future
integrated single-cell DNA-sequencing-based analysis.
Shapiro et al., 2013
Shapiro et al., 2013
6. REFERENCES
1. Blainey, P. C., & Quake, S. R. (2014). Dissecting genomic diversity, one cell at a time. Nature methods, 11(1), 19-21.2. Eberwine, J., Sul, J. Y., Bartfai, T., & Kim, J. (2014). The promise of single-cell sequencing. Nature methods, 11(1), 25-27.3. Kalisky, T., & Quake, S. R. (2011). Single-cell genomics. Nature methods, 8(4), 311-314.4. Macaulay, I. C., & Voet, T. (2014). Single cell genomics: advances and future perspectives.5. Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., ... & Muthuswamy, L. (2011). Tumour evolution
inferred by single-cell sequencing. Nature, 472(7341), 90-94.
6. Navin, N. E. (2014). Cancer genomics: one cell at a time. Genome Biol, 15, 452.7. Navin, N. E. (2015). The first five years of single-cell cancer genomics and beyond. Genome research, 25(10), 1499-1507.8. Nawy, T. (2014). Single-cell sequencing. Nature methods, 11(1), 18-18.9. Saadatpour, A., Lai, S., Guo, G., & Yuan, G. C. (2015). Single-Cell Analysis in Cancer Genomics. Trends in Genetics,
31(10), 576-586.10. Saliba, A. E., Westermann, A. J., Gorski, S. A., & Vogel, J. (2014). Single-cell RNA-seq: advances and future challenges.
Nucleic acids research, gku555.11. Shapiro, E., Biezuner, T., & Linnarsson, S. (2013). Single-cell sequencing-based technologies will revolutionize whole-
organism science. Nature Reviews Genetics, 14(9), 618-63012. Sun, H. J., Chen, J., Ni, B., Yang, X., & Wu, Y. Z. (2015). Recent advances and current issues in single-cell sequencing of
tumors. Cancer letters.13. Trapnell, C. (2015). Defining cell types and states with single-cell genomics. Genome research, 25(10), 1491-1498.14. Van Loo, P., & Voet, T. (2014). Single cell analysis of cancer genomes. Current opinion in genetics & development, 24,
82-91.15. Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., ... & Multani, A. (2014). Clonal evolution in breast cancer
revealed by single nucleus genome sequencing. Nature, 512(7513), 155-160.
16. Wang, Y., & Navin, N. E. (2015). Advances and Applications of Single-Cell Sequencing Technologies. Molecularcell, 58(4), 598-609.
17. Weaver, W. M., Tseng, P., Kunze, A., Masaeli, M., Chung, A. J., Dudani, J. S., ... & Di Carlo, D. (2014). Advances in high-throughput single-cell microtechnologies. Current opinion in biotechnology, 25, 114-123.
18. Wills, Q. F., & Mead, A. J. (2015). Application of Single Cell Genomics in Cancer: Promise and Challenges. Humanmolecular genetics, ddv235.
19. http://www.illumina.com/content/dam/illumina-marketing/documents/products/research_reviews/single-cell-sequencing-research-review.pdf