Co-detection and sequencing of genes and transcripts from the same single cells facilitated by a microfluidics platform

Scientific Reports

Volumn 4, Issue , 2014, Pages

  Han, Lin ^a   Zi, Xiaoyuan ^a,b,c   Garmire, Lana X ^d   Wu, Yu ^a   Weissman, Sherman M ^b,e   Pan, Xinghua ^b   Fan, Rong ^a,e  

^a Yale University   (United States)

^b YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c SECOND MILITARY MEDICAL UNIVERSITY   (China)

^d UNIVERSITY OF HAWAII CANCER CENTER   (United States)

^e YALE CANCER CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA; MESSENGER RNA;

BIOSYNTHESIS; CHRONIC MYELOID LEUKEMIA; GENE EXPRESSION REGULATION; GENETIC EPIGENESIS; GENETICS; GENOMICS; HUMAN; MICROFLUIDICS; PATHOLOGY; SINGLE CELL ANALYSIS; TUMOR CELL LINE;

CELL LINE, TUMOR; DNA; EPIGENESIS, GENETIC; GENE EXPRESSION REGULATION, NEOPLASTIC; GENOMICS; HUMANS; LEUKEMIA, MYELOGENOUS, CHRONIC, BCR-ABL POSITIVE; MICROFLUIDICS; RNA, MESSENGER; SINGLE-CELL ANALYSIS;

EID: 84923365432     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep06485     Document Type: Article

References (49)

1. Crick, F. Central Dogma of Molecular Biology. Nature 227, 561 (1970).
2. Sustar, P. Crick's notion of genetic information and the 'central dogma' of molecular biology. Brit J Philos Sci 58, 13-24 (2007).
3. Greenbaum, D., Colangelo, C., Williams, K. & Gerstein, M. Comparing protein abundance and mRNA expression levels on a genomic scale. Genome Biol 4 (2003).
4. Yeung, E. S. Genome-wide Correlation between mRNA and Protein in a Single Cell. Angew Chem Int Edit 50, 583-585 (2011).
5. Cai, L., Friedman, N. & Xie, X. S. Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358-362 (2006).
6. Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376-380 (2012).
7. Peter, I. S. & Davidson, E. H. A gene regulatory network controlling the embryonic specification of endoderm. Nature 474, 635-U110 (2011).
8. Smith, J., Theodoris, C. & Davidson, E. H. A gene regulatory network subcircuit drives a dynamic pattern of gene expression. Science 318, 794-797 (2007).
9. Dawson, M. A. & Kouzarides, T. Cancer Epigenetics: From Mechanism to Therapy. Cell 150, 12-27 (2012).
10. Luco, R. F., Allo, M., Schor, I. E., Kornblihtt, A. R. & Misteli, T. Epigenetics in Alternative Pre-mRNA Splicing. Cell 144, 16-26 (2011).
11. Goldberg, A. D., Allis, C. D. & Bernstein, E. Epigenetics: A landscape takes shape. Cell 128, 635-638 (2007).
12. Dove, A. Epigenetics: The Final Frontier? Science 326, 303-305 (2009).
13. Berger, S. L. Chromatin and gene regulation-Molecular mechanisms in epigenetics. Science 300, 252-254 (2003).
14. Jones, P. A. & Takai, D. The role of DNA methylation in mammalian epigenetics. Science 293, 1068-1070 (2001).
15. Altschuler, S. J. & Wu, L. F. Cellular Heterogeneity: Do Differences Make a Difference? Cell 141, 559-563 (2010).
16. Niepel, M., Spencer, S. L. & Sorger, P. K. Non-genetic cell-to-cell variability and the consequences for pharmacology. Curr Opin Chem Biol 13, 556-561 (2009).
17. Blake, W. J., Kaern, M., Cantor, C. R. & Collins, J. J. Noise in eukaryotic gene expression. Nature 422, 633-637 (2003).
18. Bahar, R. et al. Increased cell-to-cell variation in gene expression in ageing mouse heart. Nature 441, 1011-1014 (2006).
19. Sigal, A. et al. Variability and memory of protein levels in human cells. Nature 444, 643-646 (2006).
20. Chang, H. H., Hemberg, M., Barahona, M., Ingber, D. E. & Huang, S. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 453, 544-U510 (2008).
21. Eldar, A. & Elowitz, M. B. Functional roles for noise in genetic circuits. Nature 467, 167-173 (2010).
22. Li, G. W. & Xie, X. S. Central dogma at the single-molecule level in living cells. Nature 475, 308-315 (2011).
23. Gupta, P. B. et al. Stochastic State Transitions Give Rise to Phenotypic Equilibrium in Populations of Cancer Cells. Cell 146, 633-644 (2011).
24. Perkel, J. M. Sangerwho? Sequencing the Next Generation. Science 324, 275-279 (2009).
25. Foo, J. N., Liu, J. J. & Tan, E. K. Next-generation sequencing diagnostics for neurological diseases/disorders: from a clinical perspective. Hum Genet 132, 721-734 (2013).
26. Mardis, E. R. Next-generation DNA sequencing methods. Annu Rev Genom Hum Genet 9, 387-402 (2008).
27. Lizardi, P. M. Next-generation sequencing-by-hybridization. Nat Biotechnol 26, 649-650 (2008).
28. Shendure, J. & Ji, H. L. Next-generation DNA sequencing. Nat Biotechnol 26, 1135-1145 (2008).
29. Smith, D. R. et al. Rapid whole-genome mutational profiling using next-generation sequencing technologies. Genome Res 18, 1638-1642 (2008).
30. White, A. K. et al. High-throughput microfluidic single-cell RT-qPCR. Proc Natl Acad Sci U S A 108, 13999-14004 (2011).
31. Bontoux, N. et al. Integrating whole transcriptome assays on a lab-on-a-chip for single cell gene profiling. Lab Chip 8, 443-450 (2008).
32. Huang, B. et al. Counting low-copy number proteins in a single cell. Science 315, 81-84 (2007).
33. Zhong, J. F. et al. A microfluidic processor for gene expression profiling of single human embryonic stem cells. Lab chip 8, 68-74 (2008).
34. Zeng, Y., Novak, R., Shuga, J., Smith, M. T. & Mathies, R. A. High-Performance Single Cell Genetic Analysis Using Microfluidic Emulsion Generator Arrays. Anal Chem 82, 3183-3190 (2010).
35. Andersson, H. & van den Berg, A. Microtechnologies and nanotechnologies for single-cell analysis. Curr Opin Biotech 15, 44-49 (2004).
36. El-Ali, J., Sorger, P. K. & Jensen, K. F. Cells on chips. Nature 442, 403-411 (2006).
37. Toriello, N. M. et al. Integrated microfluidic bioprocessor for single-cell gene expression analysis. Proc Natl Acad Sci U S A 105, 20173-20178 (2008).
38. Novak, R. et al. Single-Cell Multiplex Gene Detection and Sequencing with Microfluidically Generated Agarose Emulsions. Angew Chem Int Edit 50, 390-395 (2011).
39. Marcy, Y. et al. Nanoliter reactors improve multiple displacement amplification of genomes from single cells. PLoS Genet 3, 1702-1708 (2007).
40. Wang, J. B., Fan, H. C., Behr, B. & Quake, S. R. Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm. Cell 150, 402-412 (2012).
41. Whitesides, G. M., Ostuni, E., Takayama, S., Jiang, X. Y. & Ingber, D. E. Soft lithography in biology and biochemistry. Annu Rev Biomed Eng 3, 335-373 (2001).
42. Unger, M. A., Chou, H. P., Thorsen, T., Scherer, A. & Quake, S. R. Monolithic microfabricated valves and pumps by multilayer soft lithography. Science 288, 113-116 (2000).
43. Pan, X. H. et al. A procedure for highly specific, sensitive, and unbiased whole-genome amplification. Proc Natl Acad Sci U S A 105, 15499-15504 (2008).
44. Pan, X. H. et al. Two methods for full-length RNA sequencing for low quantities of cells and single cells. Proc Natl Acad Sci U S A 110, 594-599 (2013).
45. Roozemond, R. C. Ultramicrochemical Determination of Nucleic-Acids in Individual Cells Using Zeiss Umsp-1 Microspectrophotometer-Application to Isolated Rat Hepatocytes of Different Ploidy Classes. Histochem J 8, 625-638 (1976).
46. Uemura, E. Age-Related-Changes in Neuronal Rna-Content in Rhesus-Monkeys (Macaca-Mulatta). Brain Res Bull 5, 117-119 (1980).
47. Kumar, G., Garnova, E., Reagin, M. & Vidali, A. Improved multiple displacement amplification with phi 29 DNA polymerase for genotyping of single human cells. Biotechniques 44, 879-1 (2008).
48. Boon, W. C. et al. Increasing cDNA yields from single-cell quantities of mRNA in standard laboratory reverse transcriptase reactions using acoustic microstreaming. J Vis Exp e3144 (2011).
49. Aumann, T. D. et al. SK channel function regulates the dopamine phenotype of neurons in the substantia nigra pars compacta. Exp Neurol 213, 419-430 (2008).