Beatriz Lara Amaro

Genomics

Official Master's Degree

in Advanced Genetics

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

Macaulay et al., 2014

C. Key step

5. APPLICATIONS. Cancer biology

Wang et al., 2015

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

5. APPLICATIONS. Neurobiology

Wang et al., 2015

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

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