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Advancement of Single-Cell Sequencing in Medulloblastoma

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Medulloblastoma

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2423))

Abstract

Single-cell sequencing is a promising attempt to investigate the genomic, transcriptomic, and multiomic level of individual cell in the larger population of cells. The outward evolution of the technique from a manual method to the automation of single-cell sequencing is cogent. Lately, single-cell sequencing is widely used in various fields of science and has applications in neurobiology, immunity, cancer, microbiology, reproduction, and digestion. This chapter introduces the reader to the details of single-cell sequencing, currently used in several small-scale and commercial platforms. The advancement of single-cell sequencing in brain cancer sheds light on questions unanswered so far in the field of oncology.

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Abbreviations

CNV :

Copy number variation

FACS :

Fluorescence activated cell sorting

FISH:

Fluorescence in situ hybridization

MALBAC :

Multiple Annealing and Looping Based Amplification Cycles

MDA :

Multiple displacement amplification

NGS :

Next-generation sequencing

RT-PCR:

Reverse transcription Polymerase Chain Reaction

scRNA-seq:

Single-cell RNA sequencing

SCS :

Single-cell sequencing

WGA:

Whole genome amplification

References

  1. Raj A, van den Bogaard P, Rifkin SA, van Oudenaarden A, Tyagi S (2008) Imaging individual mRNA molecules using multiple singly labeled probes. Nat Methods 5:877–879. https://doi.org/10.1038/nmeth.1253

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kalisky T, Blainey P, Quake SR (2011) Genomic analysis at the single-cell level. Annu Rev Genet 45:431–445. https://doi.org/10.1146/annurev-genet-102209-163607

    Article  CAS  PubMed  Google Scholar 

  3. Luo C, Keown CL, Kurihara L, Zhou J, He Y, Li J, Castanon R, Lucero J, Nery JR, Sandoval JP et al (2017) Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex. Science 357:600–604. https://doi.org/10.1126/science.aan3351

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Tang X, Huang Y, Lei J, Luo H, Zhu X (2019) The single-cell sequencing: new developments and medical applications. Cell Biosci 9:53. https://doi.org/10.1186/s13578-019-0314-y

    Article  PubMed  PubMed Central  Google Scholar 

  5. Martinez-Jimenez CP, Eling N, Chen H-C, Vallejos CA, Kolodziejczyk AA, Connor F, Stojic L, Rayner TF, Stubbington MJT, Teichmann SA et al (2017) Aging increases cell-to-cell transcriptional variability upon immune stimulation. Science 355:1433–1436. https://doi.org/10.1126/science.aah4115

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J, Tuch BB, Siddiqui A et al (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6:377–382. https://doi.org/10.1038/nmeth.1315

    Article  CAS  PubMed  Google Scholar 

  7. Single cell sequencing - Wikipedia Available online: https://en.wikipedia.org/wiki/Single_cell_sequencing. Accessed 1 Aug 2020

  8. Eberwine J, Sul JY, Bartfai T, Kim J (2014) The promise of single-cell sequencing. Nat Methods 11:25–27

    Article  CAS  PubMed  Google Scholar 

  9. Chattopadhyay P, Roederer M (2012) Cytometry: today’s technology and tomorrow’s horizons. Methods 57(3):251–258

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Macaulay IC, Voet T (2014) Single cell genomics: advances and future perspectives. PLoS Genet 10:e1004126

    Article  PubMed  PubMed Central  Google Scholar 

  11. Zong C, Lu S, Chapman A (2012) Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338(6114):1622–1626

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Alexandrov L, Stratton MR (2014) Mutational signatures: the patterns of somatic mutations hidden in cancer genomes. Curr Opin Genet Dev 24(100):52–60

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Biesecker LG, Spinner NB (2013) A genomic view of mosaicism and human disease. Nat Rev Genet 14:307–320

    Article  CAS  PubMed  Google Scholar 

  14. Nagaoka SI, Hassold TJ, Hunt PA (2012) Human aneuploidy: mechanisms and new insights into an age-old problem. Nat Rev Genet 13:493–504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Navin N, Kendall J, Troge J, Andrews P et al (2011) Tumour evolution inferred by single-cell sequencing. Nature 472(7341):90–94

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rodrigue S, Malmstrom RR, Berlin AM, Birren BW, Henn MR, Chisholm SW (2009) Whole genome amplification and de novo assembly of single bacterial cells. PLoS One 4:e6864. https://doi.org/10.1371/journal.pone.0006864

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Tang F, Barbacioru C, Bao S, Lee C et al (2010) Tracing the derivation of embryonic stem cells from the inner cell mass by single-cell RNA-Seq analysis. Cell Stem Cell 6(5):468–478

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Jaitin D, Kenigsberg E et al (2014) Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343(6172):776–779

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zeisel A, Muñoz-Manchado AB, Codeluppi S, Lönnerberg P, La Manno G, Juréus A, Marques S, Munguba H, He L, Betsholtz C et al (2015) Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347:1138–1142. https://doi.org/10.1126/science.aaa1934

    Article  CAS  PubMed  Google Scholar 

  20. Grün D, Lyubimova A, Kester L, Wiebrands K, Basak O et al (2015) Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 525(7568):251–255

    Article  PubMed  Google Scholar 

  21. Shalek A, Satija R, Adiconis X, Gertner R et al (2013) Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498(7453):236–240

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Shalek A, Satija R, Shuga J, Trombetta J, Gennert D et al (2014) Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510(7505):363–369

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, Cahill DP, Nahed BV, Curry WT, Martuza RL, Louis DN, Rozenblatt-Rosen O, Suvà ML, Regev A, Bernstein BE (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344(6190):1396–1401

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Tirosh I, Suvà ML (2018) Dissecting human gliomas by single-cell RNA sequencing. Neuro Oncol 20(1):37–43

    Article  CAS  PubMed  Google Scholar 

  25. Müller S, Liu SJ, Di Lullo E, Malatesta M, Pollen AA, Nowakowski TJ, Kohanbash G, Aghi M, Kriegstein AR, Lim DA et al (2016) Single-cell sequencing maps gene expression to mutational phylogenies in PDGF - and EGF -driven gliomas. Mol Syst Biol 12:889. https://doi.org/10.15252/msb.20166969

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, Cahill DP, Nahed BV, Curry WT, Martuza RL et al (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344:1396–1401. https://doi.org/10.1126/science.1254257

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Tirosh I, Venteicher A, Hebert C, Escalante L et al (2016) Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539(7628):309–313

    Article  PubMed  PubMed Central  Google Scholar 

  28. Choi JR, Yong KW, Choi JY, Cowie AC (2020) Single-cell RNA sequencing and its combination with protein and DNA analyses. Cell 9:1130

    Article  Google Scholar 

  29. Hashimshony T, Wagner F, Sher N, Yanai I (2012) CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep 2:666–673. https://doi.org/10.1016/j.celrep.2012.08.003

    Article  CAS  PubMed  Google Scholar 

  30. Hashimshony T, Senderovich N, Avital G, Klochendler A, de Leeuw Y, Anavy L, Gennert D, Li S, Livak KJ, Rozenblatt-Rosen O et al (2016) CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq. Genome Biol 17:77. https://doi.org/10.1186/s13059-016-0938-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM et al (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–1214. https://doi.org/10.1016/j.cell.2015.05.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, Peshkin L, Weitz DA, Kirschner MW (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187–1201. https://doi.org/10.1016/j.cell.2015.04.044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Diego AD, Kenigsberg E, Keren-Shaul H, Elefant N, Paul F, Zaretsky I, Mildner A, Cohen N, Jung S, Tanay A, Amit I (2014) Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343(6172):776–779. https://doi.org/10.1126/science.1247651

  34. Soumillon M, Cacchiarelli D, Semrau S, van Oudenaarden A, Mikkelsen TS (2014) Characterization of directed differentiation by high-throughput single-cell RNA-Seq. bioRxiv 003236. https://doi.org/10.1101/003236

  35. Gierahn TM, Wadsworth MH, Hughes TK, Bryson BD, Butler A, Satija R, Fortune S, Christopher Love J, Shalek AK (2017) Seq-well: portable, low-cost rna sequencing of single cells at high throughput. Nat Methods 14:395–398. https://doi.org/10.1038/nmeth.4179

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Picelli S, Björklund ÅK, Faridani OR, Sagasser S, Winberg G, Sandberg R (2013) Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096–1098. https://doi.org/10.1038/nmeth.2639

    Article  CAS  PubMed  Google Scholar 

  37. Islam S, Zeisel A, Joost S, La Manno G, Zajac P, Kasper M, Lönnerberg P, Linnarsson S (2014) Quantitative single-cell RNA-seq with unique molecular identifiers. Nat Methods 11:163–166. https://doi.org/10.1038/nmeth.2772

    Article  CAS  PubMed  Google Scholar 

  38. Vitak SA, Torkenczy KA, Rosenkrantz JL, Fields AJ, Christiansen L, Wong MH, Carbone L, Steemers FJ, Adey A (2017) Sequencing thousands of single-cell genomes with combinatorial indexing. Nat Methods 14:302–308. https://doi.org/10.1038/nmeth.4154

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Chen C, Xing D, Tan L, Li H, Zhou G, Huang L, Xie XS (2017) Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI). Science 356:189–194. https://doi.org/10.1126/science.aak9787

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Guo F, Li L, Li J, Wu X, Hu B, Zhu P, Wen L, Tang F (2017) Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells. Cell Res 27:967–988. https://doi.org/10.1038/cr.2017.82

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Casasent AK, Schalck A, Gao R, Sei E, Long A, Pangburn W, Casasent T, Meric-Bernstam F, Edgerton ME, Navin NE (2018) Multiclonal invasion in breast tumors identified by topographic single cell sequencing. Cell 172:205–217.e12. https://doi.org/10.1016/j.cell.2017.12.007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Demaree B, Weisgerber D, Lan F, Abate AR (2018) An ultrahigh-throughput microfluidic platform for single-cell genome sequencing. J Vis Exp 2018:57598. https://doi.org/10.3791/57598

    Article  CAS  Google Scholar 

  43. Han X, Wang R, Zhou Y, Fei L, Sun H, Lai S, Saadatpour A, Zhou Z, Chen H, Ye F et al (2018) Mapping the Mouse Cell Atlas by Microwell-Seq. Cell 172:1091–1107.e17. https://doi.org/10.1016/j.cell.2018.02.001

    Article  CAS  PubMed  Google Scholar 

  44. Rosenberg AB, Roco CM, Muscat RA, Kuchina A, Sample P, Yao Z, Graybuck LT, Peeler DJ, Mukherjee S, Chen W et al (2018) Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science 360:176–182. https://doi.org/10.1126/science.aam8999

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ramsköld D, Luo S, Wang Y, Li R, Deng Q et al (2012) Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 30(8):777–782

    Article  PubMed  PubMed Central  Google Scholar 

  46. Picelli S, Faridani OR, Björklund ÅK, Winberg G, Sagasser S, Sandberg R (2014) Full-length RNA-seq from single cells using smart-seq2. Nat Protoc 9:171–181. https://doi.org/10.1038/nprot.2014.006

    Article  CAS  PubMed  Google Scholar 

  47. Keren-Shaul H, Kenigsberg E, Jaitin D, David E (2019) MARS-seq2. 0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing. Nat Protoc 14(6):1841–1862

    Article  CAS  PubMed  Google Scholar 

  48. Sasagawa Y, Nikaido I, Hayashi T, Danno H, Uno KD, Imai T, Ueda HR (2013) Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals nongenetic gene-expression heterogeneity. Genome Biol 14:R31. https://doi.org/10.1186/gb-2013-14-4-r31

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Sasagawa Y, Danno H, Takada H, Ebisawa M, Tanaka K, Hayashi T, Kurisaki A, Nikaido I (2018) Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads. Genome Biol 19:29. https://doi.org/10.1186/s13059-018-1407-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Fan X, Zhang X, Wu X, Guo H, Hu Y, Tang F, Huang Y (2015) Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos. Genome Biol 16:148. https://doi.org/10.1186/s13059-015-0706-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Sheng K, Cao W et al (2017) Effective detection of variation in single-cell transcriptomes using MATQ-seq. Nat Methods 14:267–270. https://doi.org/10.1038/nmeth.4145

    Article  CAS  PubMed  Google Scholar 

  52. Streets AM, Zhang X, Cao C, Pang Y, Wu X, Xiong L, Yang L, Fu Y, Zhao L, Tang F, Huang Y (2014) Microfluidic single-cell whole-transcriptome sequencing. Proc Natl Acad Sci U S A 111(19):7048–7053

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Kimmerling R, Szeto G, Li J, Genshaft A (2016) A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages. Nat Commun 7:10220

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Sarma M, Lee J, Ma S, Li S, Lu C (2019) A diffusion-based microfluidic device for single-cell RNA-seq. Lab Chip 19(7):1247–1256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Cheng Y, Chen Y, Lin E, Brien R, Jung S et al (2019) Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells. Nat Commun 10(1):2163

    Article  PubMed  PubMed Central  Google Scholar 

  56. Rotem A, Ram O, Shoresh N, Sperling RA, Schnall-Levin M, Zhang H, Basu A, Bernstein BE, Weitz DA (2015) High-throughput single-cell labeling (Hi-SCL) for RNA-Seq using drop-based microfluidics. PLoS One 10:e0116328. https://doi.org/10.1371/journal.pone.0116328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Zheng G, Terry J, Belgrader P, Ryvkin P et al (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. McGinnis CS, Patterson DM, Winkler J, Conrad DN, Hein MY, Srivastava V, Hu JL, Murrow LM, Weissman JS, Werb Z et al (2019) MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices. Nat Methods 16:619–626. https://doi.org/10.1038/s41592-019-0433-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Yuan J, Sheng J, Sims PA (2018) SCOPE-Seq: a scalable technology for linking live cell imaging and single-cell RNA sequencing. Genome Biol 19:227. https://doi.org/10.1186/s13059-018-1607-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Fan H, Fu G, Fodor S (2015) Combinatorial labeling of single cells for gene expression cytometry. Science 347(6222):1258367

    Article  PubMed  Google Scholar 

  61. Dura B, Choi J, Zhang K, Damsky W (2019) scFTD-seq: freeze-thaw lysis based, portable approach toward highly distributed single-cell 3′ mRNA profiling. Nucleic Acids Res 47(3):e16

    Article  PubMed  Google Scholar 

  62. Wen L, Tang F (2018) Boosting the power of single-cell analysis. Nat Biotechnol 36:408–409

    Article  CAS  PubMed  Google Scholar 

  63. Kleihues P, Sobin LH (2000) World Health Organization classification of tumors. Cancer 88:2887–2887. https://doi.org/10.1002/1097-0142(20000615)88:12<2887::AID-CNCR32>3.0.CO;2-F

    Article  CAS  PubMed  Google Scholar 

  64. Bao S, Wu Q, McLendon RE, Hao Y, Shi Q, Hjelmeland AB, Dewhirst MW, Bigner DD, Rich JN (2006) Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature 444:756–760. https://doi.org/10.1038/nature05236

    Article  CAS  PubMed  Google Scholar 

  65. Dagogo-Jack I, Shaw AT (2018) Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol 15:81–94

    Article  CAS  PubMed  Google Scholar 

  66. Singh SK, Hawkins C, Clarke ID, Squire JA, Bayani J, Hide T, Henkelman RM, Cusimano MD, Dirks PB (2004) Identification of human brain tumour initiating cells. Nature 432:396–401. https://doi.org/10.1038/nature03128

    Article  CAS  PubMed  Google Scholar 

  67. Vescovi AL, Galli R, Reynolds BA (2006) Brain tumour stem cells. Nat Rev Cancer 6:425–436

    Article  CAS  PubMed  Google Scholar 

  68. Meyer M, Reimand J, Lan X, Head R, Zhu X, Kushida M, Bayani J, Pressey JC, Lionel AC, Clarke ID et al (2015) Single cell-derived clonal analysis of human glioblastoma links functional and genomic heterogeneity. Proc Natl Acad Sci U S A 112:851–856. https://doi.org/10.1073/pnas.1320611111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Couturier CP, Ayyadhury S, Le PU, Nadaf J, Monlong J, Riva G, Allache R, Baig S, Yan X, Bourgey M et al (2020) Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11:1–19. https://doi.org/10.1038/s41467-020-17186-5

    Article  CAS  Google Scholar 

  70. Venteicher AS, Tirosh I, Hebert C, Yizhak K, Neftel C, Filbin MG, Hovestadt V, Escalante LE, Shaw ML, Rodman C et al (2017) Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. Science 355:eaai8478. https://doi.org/10.1126/science.aai8478

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Darmanis S, Sloan SA, Croote D, Mignardi M, Chernikova S, Samghababi P, Zhang Y, Neff N, Kowarsky M, Caneda C et al (2017) Single-cell RNA-Seq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma. Cell Rep 21:1399–1410. https://doi.org/10.1016/j.celrep.2017.10.030

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Li Q, Cheng Z, Zhou L, Darmanis S, Neff N, Okamoto J (2019) Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing. Neuron 101(2):207–223.e10

    Article  CAS  PubMed  Google Scholar 

  73. Kharchenko PV, Silberstein L, Scadden DT (2014) Bayesian approach to single-cell differential expression analysis. Nat Methods 11:740–742. https://doi.org/10.1038/nmeth.2967

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Verma, D., Nayak, N., Singh, A., Singh, A.K., Garg, N. (2022). Advancement of Single-Cell Sequencing in Medulloblastoma. In: Dey, A., Malhotra, A., Garg, N. (eds) Medulloblastoma. Methods in Molecular Biology, vol 2423. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1952-0_7

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  • DOI: https://doi.org/10.1007/978-1-0716-1952-0_7

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