Interrogating islets in health and disease with single-cell technologies

Molecular Metabolism

Volumn 6, Issue 9, 2017, Pages 991-1001

  Carrano, Andrea C ^a   Mulas, Francesca ^a   Zeng, Chun ^a   Sander, Maike ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Endocrine cell; Heterogeneity; Pancreatic islet; RNA seq; Single cell; Type 2 diabetes

Indexed keywords

CELL AGING; CELL ASSAY; CELL FUNCTION; CELL MATURATION; CELL PLASTICITY; CELL PROLIFERATION; CELL SELECTION; CELL SUBPOPULATION; DIABETES MELLITUS; GLUCOSE HOMEOSTASIS; HUMAN; NONHUMAN; PANCREAS ISLET CELL; PRIORITY JOURNAL; REVIEW; SINGLE CELL ANALYSIS; ANIMAL; CYTOLOGY; GENE EXPRESSION PROFILING; GENETICS; GLUCOSE BLOOD LEVEL; METABOLISM; NON INSULIN DEPENDENT DIABETES MELLITUS; PANCREAS ISLET; PANCREAS ISLET BETA CELL; PHYSIOLOGY; PROCEDURES;

INSULIN; PROTEOME; TRANSCRIPTOME;

ANIMALS; BLOOD GLUCOSE; DIABETES MELLITUS, TYPE 2; GENE EXPRESSION PROFILING; HUMANS; INSULIN; INSULIN-SECRETING CELLS; ISLETS OF LANGERHANS; PROTEOME; SINGLE-CELL ANALYSIS; TRANSCRIPTOME;

EID: 85019641234     PISSN: None     EISSN: 22128778     Source Type: Journal    
DOI: 10.1016/j.molmet.2017.04.012     Document Type: Review

References (117)

1. Caicedo, A., Paracrine and autocrine interactions in the human islet: more than meets the eye. Seminars in Cell & Developmental Biology 24:1 (2013), 11–21.
2. Di Cairano, E.S., Moretti, S., Marciani, P., Sacchi, V.F., Castagna, M., Davalli, A., et al. Neurotransmitters and neuropeptides: new players in the control of islet of Langerhans' cell mass and function. Journal of Cell Physiology 231:4 (2016), 756–767.
3. Roscioni, S.S., Migliorini, A., Gegg, M., Lickert, H., Impact of islet architecture on beta-cell heterogeneity, plasticity and function. Nature Reviews. Endocrinology 12:12 (2016), 695–709.
4. Salomon, D., Meda, P., Heterogeneity and contact-dependent regulation of hormone secretion by individual B cells. Experimental Cell Research 162:2 (1986), 507–520.
5. Van Schravendijk, C.F., Kiekens, R., Pipeleers, D.G., Pancreatic beta cell heterogeneity in glucose-induced insulin secretion. Journal of Biological Chemistry 267:30 (1992), 21344–21348.
6. Giordano, E., Cirulli, V., Bosco, D., Rouiller, D., Halban, P., Meda, P., B-cell size influences glucose-stimulated insulin secretion. American Journal of Physiology 265:2 Pt 1 (1993), C358–C364.
7. Stefan, Y., Meda, P., Neufeld, M., Orci, L., Stimulation of insulin secretion reveals heterogeneity of pancreatic B cells in vivo. Journal of Clinical Investigation 80:1 (1987), 175–183.
8. Giordano, E., Bosco, D., Cirulli, V., Meda, P., Repeated glucose stimulation reveals distinct and lasting secretion patterns of individual rat pancreatic B cells. Journal of Clinical Investigation 87:6 (1991), 2178–2185.
9. Pipeleers, D.G., Heterogeneity in pancreatic beta-cell population. Diabetes 41:7 (1992), 777–781.
10. Kiekens, R., In 't Veld, P., Mahler, T., Schuit, F., Van De Winkel, M., Pipeleers, D., Differences in glucose recognition by individual rat pancreatic B cells are associated with intercellular differences in glucose-induced biosynthetic activity. Journal of Clinical Investigation 89:1 (1992), 117–125.
11. Ling, Z., Chen, M.C., Smismans, A., Pavlovic, D., Schuit, F., Eizirik, D.L., et al. Intercellular differences in interleukin 1beta-induced suppression of insulin synthesis and stimulation of noninsulin protein synthesis by rat pancreatic beta-cells. Endocrinology 139:4 (1998), 1540–1545.
12. Van De Winkel, M., Pipeleers, D., Autofluorescence-activated cell sorting of pancreatic islet cells: purification of insulin-containing B-cells according to glucose-induced changes in cellular redox state. Biochemical and Biophysical Research Communications 114:2 (1983), 835–842.
13. Pipeleers, D., The biosociology of pancreatic B cells. Diabetologia 30:5 (1987), 277–291.
14. Rui, J., Deng, S., Arazi, A., Perdigoto, A.L., Liu, Z., Herold, K.C., β cells that resist immunological attack develop during progression of autoimmune diabetes in NOD mice. Cell Metabolism, 2017.
15. Grapengiesser, E., Gylfe, E., Hellman, B., Glucose-induced oscillations of cytoplasmic Ca2+ in the pancreatic beta-cell. Biochemical and Biophysical Research Communications 151:3 (1988), 1299–1304.
16. Asada, N., Shibuya, I., Iwanaga, T., Niwa, K., Kanno, T., Identification of alpha- and beta-cells in intact isolated islets of Langerhans by their characteristic cytoplasmic Ca2+ concentration dynamics and immunocytochemical staining. Diabetes 47:5 (1998), 751–757.
17. Nadal, A., Quesada, I., Soria, B., Homologous and heterologous asynchronicity between identified alpha-, beta- and delta-cells within intact islets of Langerhans in the mouse. Journal of Physiology 517:Pt 1 (1999), 85–93.
18. Herchuelz, A., Pochet, R., Pastiels, C., Van Praet, A., Heterogeneous changes in [Ca2+]i induced by glucose, tolbutamide and K+ in single rat pancreatic B cells. Cell Calcium 12:8 (1991), 577–586.
19. Hodson, D.J., Mitchell, R.K., Bellomo, E.A., Sun, G., Vinet, L., Meda, P., et al. Lipotoxicity disrupts incretin-regulated human beta cell connectivity. Journal of Clinical Investigation 123:10 (2013), 4182–4194.
20. Stozer, A., Gosak, M., Dolensek, J., Perc, M., Marhl, M., Rupnik, M.S., et al. Functional connectivity in islets of Langerhans from mouse pancreas tissue slices. PLoS Computational Biology, 9(2), 2013, e1002923.
21. Johnston, N.R., Mitchell, R.K., Haythorne, E., Pessoa, M.P., Semplici, F., Ferrer, J., et al. Beta cell hubs dictate pancreatic islet responses to glucose. Cell Metabolism 24:3 (2016), 389–401.
22. Hellerström, C., Swenne, I., The diabetic pancreas. Volk, B.W., Arquilla, E.R., (eds.), 1985, Springer, 53–79.
23. Bader, E., Migliorini, A., Gegg, M., Moruzzi, N., Gerdes, J., Roscioni, S.S., et al. Identification of proliferative and mature beta-cells in the islets of Langerhans. Nature 535:7612 (2016), 430–434.
24. Krishnamurthy, J., Ramsey, M.R., Ligon, K.L., Torrice, C., Koh, A., Bonner-Weir, S., et al. p16INK4a induces an age-dependent decline in islet regenerative potential. Nature 443:7110 (2006), 453–457.
25. Helman, A., Klochendler, A., Azazmeh, N., Gabai, Y., Horwitz, E., Anzi, S., et al. p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion. Nature Medicine 22:4 (2016), 412–420.
26. Benner, C., van der Meulen, T., Caceres, E., Tigyi, K., Donaldson, C.J., Huising, M.O., The transcriptional landscape of mouse beta cells compared to human beta cells reveals notable species differences in long non-coding RNA and protein-coding gene expression. BMC Genomics, 15, 2014, 620.
27. DiGruccio, M.R., Mawla, A.M., Donaldson, C.J., Noguchi, G.M., Vaughan, J., Cowing-Zitron, C., et al. Comprehensive alpha, beta and delta cell transcriptomes reveal that ghrelin selectively activates delta cells and promotes somatostatin release from pancreatic islets. Molecular Metabolism 5:7 (2016), 449–458.
28. Avrahami, D., Li, C., Zhang, J., Schug, J., Avrahami, R., Rao, S., et al. Aging-dependent demethylation of regulatory elements correlates with chromatin state and improved beta cell function. Cell Metabolism 22:4 (2015), 619–632.
29. Ku, G.M., Kim, H., Vaughn, I.W., Hangauer, M.J., Myung Oh, C., German, M.S., et al. Research resource: RNA-Seq reveals unique features of the pancreatic beta-cell transcriptome. Molecular Endocrinology 26:10 (2012), 1783–1792.
30. Bramswig, N.C., Everett, L.J., Schug, J., Dorrell, C., Liu, C., Luo, Y., et al. Epigenomic plasticity enables human pancreatic alpha to beta cell reprogramming. Journal of Clinical Investigation 123:3 (2013), 1275–1284.
31. Dorrell, C., Schug, J., Canaday, P.S., Russ, H.A., Tarlow, B.D., Grompe, M.T., et al. Human islets contain four distinct subtypes of beta cells. Nature Communications, 7, 2016, 11756.
32. Nica, A.C., Ongen, H., Irminger, J.C., Bosco, D., Berney, T., Antonarakis, S.E., et al. Cell-type, allelic, and genetic signatures in the human pancreatic beta cell transcriptome. Genome Research 23:9 (2013), 1554–1562.
33. Hrvatin, S., Deng, F., O'Donnell, C.W., Gifford, D.K., Melton, D.A., MARIS: method for analyzing RNA following intracellular sorting. PLoS One, 9(3), 2014, e89459.
34. Hald, J., Galbo, T., Rescan, C., Radzikowski, L., Sprinkel, A.E., Heimberg, H., et al. Pancreatic islet and progenitor cell surface markers with cell sorting potential. Diabetologia 55:1 (2012), 154–165.
35. Pechhold, S., Stouffer, M., Walker, G., Martel, R., Seligmann, B., Hang, Y., et al. Transcriptional analysis of intracytoplasmically stained, FACS-purified cells by high-throughput, quantitative nuclease protection. Nature Biotechnology 27:11 (2009), 1038–1042.
36. Dorrell, C., Schug, J., Lin, C.F., Canaday, P.S., Fox, A.J., Smirnova, O., et al. Transcriptomes of the major human pancreatic cell types. Diabetologia 54:11 (2011), 2832–2844.
37. Gawad, C., Koh, W., Quake, S.R., Single-cell genome sequencing: current state of the science. Nature Reviews Genetics 17:3 (2016), 175–188.
38. Liu, S., Trapnell, C., Single-cell transcriptome sequencing: recent advances and remaining challenges. F1000Res, 5, 2016.
39. Su, Y., Shi, Q., Wei, W., Single cell proteomics in biomedicine: high-dimensional data acquisition, visualization and analysis. Proteomics, 2017.
40. Wang, Y.J., Golson, M.L., Schug, J., Traum, D., Liu, C., Vivek, K., et al. Single-cell mass cytometry analysis of the human endocrine pancreas. Cell Metabolism 24:4 (2016), 616–626.
41. Li, J., Klughammer, J., Farlik, M., Penz, T., Spittler, A., Barbieux, C., et al. Single-cell transcriptomes reveal characteristic features of human pancreatic islet cell types. EMBO Reports 17:2 (2016), 178–187.
42. Muraro, M.J., Dharmadhikari, G., Grun, D., Groen, N., Dielen, T., Jansen, E., et al. A single-cell transcriptome atlas of the human pancreas. Cell Systems, 3(4), 2016 385–394 e383.
43. Segerstolpe, A., Palasantza, A., Eliasson, P., Andersson, E.M., Andreasson, A.C., Sun, X., et al. Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell Metabolism 24:4 (2016), 593–607.
44. Zeng, C., Mulas, F., Sui, Y., Guan, T., Miller, N., Tan, Y., et al. Pseudotemporal ordering of single cells reveals metabolic control of postnatal beta-cell proliferation. Cell Metabolism 25:5 (2017), 1160–1175.
45. Baron, M., Veres, A., Wolock, S.L., Faust, A.L., Gaujoux, R., Vetere, A., et al. A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure. Cell Systems, 3(4), 2016 346–360 e344.
46. Xin, Y., Okamoto, H., Kim, J., Ni, M., Adler, C., Cavino, K., et al. Single-cell RNAseq reveals that pancreatic beta-cells from very old male mice have a young gene signature. Endocrinology 157:9 (2016), 3431–3438.
47. Lawlor, N., George, J., Bolisetty, M., Kursawe, R., Sun, L., Sivakamasundari, V., et al. Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes. Genome Research 27:2 (2017), 208–222.
48. Xin, Y., Kim, J., Okamoto, H., Ni, M., Wei, Y., Adler, C., et al. RNA sequencing of single human islet cells reveals type 2 diabetes genes. Cell Metabolism 24:4 (2016), 608–615.
49. Xin, Y., Kim, J., Ni, M., Wei, Y., Okamoto, H., Lee, J., et al. Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. Proceedings of the National Academy of Sciences of the United States of America 113:12 (2016), 3293–3298.
50. Jansson, E.T., Comi, T.J., Rubakhin, S.S., Sweedler, J.V., Single cell peptide heterogeneity of rat islets of Langerhans. ACS Chemical Biology 11:9 (2016), 2588–2595.
51. Bonner-Weir, S., Aguayo-Mazzucato, C., Physiology: pancreatic beta-cell heterogeneity revisited. Nature 535:7612 (2016), 365–366.
52. Yang, Q., Graham, T.E., Mody, N., Preitner, F., Peroni, O.D., Zabolotny, J.M., et al. Serum retinol binding protein 4 contributes to insulin resistance in obesity and type 2 diabetes. Nature 436:7049 (2005), 356–362.
53. Taneera, J., Lang, S., Sharma, A., Fadista, J., Zhou, Y., Ahlqvist, E., et al. A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets. Cell Metabolism 16:1 (2012), 122–134.
54. Akerfeldt, M.C., Laybutt, D.R., Inhibition of Id1 augments insulin secretion and protects against high-fat diet-induced glucose intolerance. Diabetes 60:10 (2011), 2506–2514.
55. Zhou, P., Robles-Murguia, M., Mathew, D., Duffield, G.E., Impaired thermogenesis and a molecular signature for brown adipose tissue in Id2 null mice. Journal of Diabetes Research, 2016, 2016, 6785948.
56. Satyanarayana, A., Klarmann, K.D., Gavrilova, O., Keller, J.R., Ablation of the transcriptional regulator Id1 enhances energy expenditure, increases insulin sensitivity, and protects against age and diet induced insulin resistance, and hepatosteatosis. FASEB Journal 26:1 (2012), 309–323.
57. Cutchins, A., Harmon, D.B., Kirby, J.L., Doran, A.C., Oldham, S.N., Skaflen, M., et al. Inhibitor of differentiation-3 mediates high fat diet-induced visceral fat expansion. Arteriosclerosis Thrombosis and Vascular Biology 32:2 (2012), 317–324.
58. Meier, J.J., Butler, A.E., Saisho, Y., Monchamp, T., Galasso, R., Bhushan, A., et al. Beta-cell replication is the primary mechanism subserving the postnatal expansion of beta-cell mass in humans. Diabetes 57:6 (2008), 1584–1594.
59. Teta, M., Long, S.Y., Wartschow, L.M., Rankin, M.M., Kushner, J.A., Very slow turnover of beta-cells in aged adult mice. Diabetes 54:9 (2005), 2557–2567.
60. Spitzer, M.H., Nolan, G.P., Mass cytometry: single cells, many features. Cell 165:4 (2016), 780–791.
61. Wang, Y.J., Schug, J., Won, K.J., Liu, C., Naji, A., Avrahami, D., et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65:10 (2016), 3028–3038.
62. Wang, P., Alvarez-Perez, J.C., Felsenfeld, D.P., Liu, H., Sivendran, S., Bender, A., et al. A high-throughput chemical screen reveals that harmine-mediated inhibition of DYRK1A increases human pancreatic beta cell replication. Nature Medicine 21:4 (2015), 383–388.
63. Shen, W., Taylor, B., Jin, Q., Nguyen-Tran, V., Meeusen, S., Zhang, Y.Q., et al. Inhibition of DYRK1A and GSK3B induces human beta-cell proliferation. Nature Communications, 6, 2015, 8372.
64. Wei, R., Hong, T., Lineage reprogramming: a promising road for pancreatic beta cell regeneration. Trends in Endocrinology and Metabolism 27:3 (2016), 163–176.
65. Thorel, F., Nepote, V., Avril, I., Kohno, K., Desgraz, R., Chera, S., et al. Conversion of adult pancreatic alpha-cells to beta-cells after extreme beta-cell loss. Nature 464:7292 (2010), 1149–1154.
66. Li, J., Casteels, T., Frogne, T., Ingvorsen, C., Honore, C., Courtney, M., et al. Artemisinins target GABAA receptor signaling and impair alpha cell identity. Cell, 168(1–2), 2017 86–100 e115.
67. Ben-Othman, N., Vieira, A., Courtney, M., Record, F., Gjernes, E., Avolio, F., et al. Long-term GABA administration induces alpha cell-mediated beta-like cell neogenesis. Cell, 168(1–2), 2017 73–85 e11.
68. Klochendler, A., Caspi, I., Corem, N., Moran, M., Friedlich, O., Elgavish, S., et al. The genetic program of pancreatic beta-cell replication in vivo. Diabetes 65:7 (2016), 2081–2093.
69. Leiter, E.H., Premdas, F., Harrison, D.E., Lipson, L.G., Aging and glucose homeostasis in C57BL/6J male mice. FASEB Journal 2:12 (1988), 2807–2811.
70. Jermendy, A., Toschi, E., Aye, T., Koh, A., Aguayo-Mazzucato, C., Sharma, A., et al. Rat neonatal beta cells lack the specialised metabolic phenotype of mature beta cells. Diabetologia 54:3 (2011), 594–604.
71. Sharma, R.B., O'Donnell, A.C., Stamateris, R.E., Ha, B., McCloskey, K.M., Reynolds, P.R., et al. Insulin demand regulates beta cell number via the unfolded protein response. Journal of Clinical Investigation 125:10 (2015), 3831–3846.
72. Asplund, K., Westman, S., Hellerstrom, C., Glucose stimulation of insulin secretion from the isolated pancreas of foetal and newborn rats. Diabetologia 5:4 (1969), 260–262.
73. Lavine, R.L., Chick, W.L., Like, A.A., Makdisi, T.W., Glucose tolerance and insulin secretion in neonatal and adult mice. Diabetes 20:3 (1971), 134–139.
74. van de Bunt, M., Manning Fox, J.E., Dai, X., Barrett, A., Grey, C., Li, L., et al. Transcript expression data from human islets links regulatory signals from genome-wide association studies for type 2 diabetes and glycemic traits to their downstream effectors. PLoS Genetics, 11(12), 2015, e1005694.
75. Fadista, J., Vikman, P., Laakso, E.O., Mollet, I.G., Esguerra, J.L., Taneera, J., et al. Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism. Proceedings of the National Academy of Sciences of the United States of America 111:38 (2014), 13924–13929.
76. Ichii, H., Inverardi, L., Pileggi, A., Molano, R.D., Cabrera, O., Caicedo, A., et al. A novel method for the assessment of cellular composition and beta-cell viability in human islet preparations. American Journal of Transplantation 5:7 (2005), 1635–1645.
77. Kloppel, G., Lohr, M., Habich, K., Oberholzer, M., Heitz, P.U., Islet pathology and the pathogenesis of type 1 and type 2 diabetes mellitus revisited. Survey and Synthesis of Pathology Research 4:2 (1985), 110–125.
78. Yoon, K.H., Ko, S.H., Cho, J.H., Lee, J.M., Ahn, Y.B., Song, K.H., et al. Selective beta-cell loss and alpha-cell expansion in patients with type 2 diabetes mellitus in Korea. Journal of Clinical Endocrinology and Metabolism 88:5 (2003), 2300–2308.
79. Butler, A.E., Janson, J., Soeller, W.C., Butler, P.C., Increased beta-cell apoptosis prevents adaptive increase in beta-cell mass in mouse model of type 2 diabetes: evidence for role of islet amyloid formation rather than direct action of amyloid. Diabetes 52:9 (2003), 2304–2314.
80. Flamez, D., Roland, I., Berton, A., Kutlu, B., Dufrane, D., Beckers, M.C., et al. A genomic-based approach identifies FXYD domain containing ion transport regulator 2 (FXYD2)gammaa as a pancreatic beta cell-specific biomarker. Diabetologia 53:7 (2010), 1372–1383.
81. Eto, K., Tsubamoto, Y., Terauchi, Y., Sugiyama, T., Kishimoto, T., Takahashi, N., et al. Role of NADH shuttle system in glucose-induced activation of mitochondrial metabolism and insulin secretion. Science 283:5404 (1999), 981–985.
82. Seron, K., Couturier, C., Belouzard, S., Bacart, J., Monte, D., Corset, L., et al. Endospanins regulate a postinternalization step of the leptin receptor endocytic pathway. Journal of Biological Chemistry 286:20 (2011), 17968–17981.
83. Talchai, C., Xuan, S., Lin, H.V., Sussel, L., Accili, D., Pancreatic beta cell dedifferentiation as a mechanism of diabetic beta cell failure. Cell 150:6 (2012), 1223–1234.
84. Wang, Z., York, N.W., Nichols, C.G., Remedi, M.S., Pancreatic beta cell dedifferentiation in diabetes and redifferentiation following insulin therapy. Cell Metabolism 19:5 (2014), 872–882.
85. Cinti, F., Bouchi, R., Kim-Muller, J.Y., Ohmura, Y., Sandoval, P.R., Masini, M., et al. Evidence of beta-cell dedifferentiation in human type 2 diabetes. Journal of Clinical Endocrinology and Metabolism 101:3 (2016), 1044–1054.
86. Brennecke, P., Anders, S., Kim, J.K., Kolodziejczyk, A.A., Zhang, X., Proserpio, V., et al. Accounting for technical noise in single-cell RNA-seq experiments. Nature Methods 10:11 (2013), 1093–1095.
87. Risso, D., Ngai, J., Speed, T.P., Dudoit, S., Normalization of RNA-seq data using factor analysis of control genes or samples. Nature Biotechnology 32:9 (2014), 896–902.
88. Leek, J.T., svaseq: removing batch effects and other unwanted noise from sequencing data. Nucleic Acids Research, 42(21), 2014.
89. Stegle, O., Teichmann, S.A., Marioni, J.C., Computational and analytical challenges in single-cell transcriptomics. Nature Reviews Genetics 16:3 (2015), 133–145.
90. Shin, J., Berg, D.A., Zhu, Y., Shin, J.Y., Song, J., Bonaguidi, M.A., et al. Single-cell RNA-seq with waterfall reveals molecular cascades underlying adult neurogenesis. Cell Stem Cell 17:3 (2015), 360–372.
91. Buettner, F., Natarajan, K.N., Casale, F.P., Proserpio, V., Scialdone, A., Theis, F.J., et al. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nature Biotechnology 33:2 (2015), 155–160.
92. Johnson, W.E., Li, C., Rabinovic, A., Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8:1 (2007), 118–127.
93. Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nature Biotechnology 32:4 (2014), 381–386.
94. Ji, Z., Ji, H., TSCAN: pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis. Nucleic Acids Research, 44(13), 2016, e117.
95. Amir el, A.D., Davis, K.L., Tadmor, M.D., Simonds, E.F., Levine, J.H., Bendall, S.C., et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nature Biotechnology 31:6 (2013), 545–552.
96. Bendall, S.C., Davis, K.L., Amir el, A.D., Tadmor, M.D., Simonds, E.F., Chen, T.J., et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157:3 (2014), 714–725.
97. Krishnaswamy, S., Spitzer, M.H., Mingueneau, M., Bendall, S.C., Litvin, O., Stone, E., et al. Systems biology. Conditional density-based analysis of T cell signaling in single-cell data. Science, 346(6213), 2014, 1250689.
98. Newell, E.W., Cheng, Y., Mass cytometry: blessed with the curse of dimensionality. Nature Immunology 17:8 (2016), 890–895.
99. Raj, A., van den Bogaard, P., Rifkin, S.A., van Oudenaarden, A., Tyagi, S., Imaging individual mRNA molecules using multiple singly labeled probes. Nature Methods 5:10 (2008), 877–879.
100. Lyubimova, A., Itzkovitz, S., Junker, J.P., Fan, Z.P., Wu, X., van Oudenaarden, A., Single-molecule mRNA detection and counting in mammalian tissue. Nature Protocols 8:9 (2013), 1743–1758.
101. Nilsson, M., Malmgren, H., Samiotaki, M., Kwiatkowski, M., Chowdhary, B.P., Landegren, U., Padlock probes: circularizing oligonucleotides for localized DNA detection. Science 265:5181 (1994), 2085–2088.
102. Lizardi, P.M., Huang, X., Zhu, Z., Bray-Ward, P., Thomas, D.C., Ward, D.C., Mutation detection and single-molecule counting using isothermal rolling-circle amplification. Nature Genetics 19:3 (1998), 225–232.
103. Kern, D., Collins, M., Fultz, T., Detmer, J., Hamren, S., Peterkin, J.J., et al. An enhanced-sensitivity branched-DNA assay for quantification of human immunodeficiency virus type 1 RNA in plasma. Journal of Clinical Microbiology 34:12 (1996), 3196–3202.
104. Battich, N., Stoeger, T., Pelkmans, L., Image-based transcriptomics in thousands of single human cells at single-molecule resolution. Nature Methods 10:11 (2013), 1127–1133.
105. Crosetto, N., Bienko, M., van Oudenaarden, A., Spatially resolved transcriptomics and beyond. Nature Reviews Genetics 16:1 (2015), 57–66.
106. Lovatt, D., Ruble, B.K., Lee, J., Dueck, H., Kim, T.K., Fisher, S., et al. Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue. Nature Methods 11:2 (2014), 190–196.
107. Giesen, C., Wang, H.A., Schapiro, D., Zivanovic, N., Jacobs, A., Hattendorf, B., et al. Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nature Methods 11:4 (2014), 417–422.
108. Pettit, J.B., Tomer, R., Achim, K., Richardson, S., Azizi, L., Marioni, J., Identifying cell types from spatially referenced single-cell expression datasets. PLoS Computational Biology, 10(9), 2014, e1003824.
109. Stergachis, A.B., Neph, S., Reynolds, A., Humbert, R., Miller, B., Paige, S.L., et al. Developmental fate and cellular maturity encoded in human regulatory DNA landscapes. Cell 154:4 (2013), 888–903.
110. Wang, A., Yue, F., Li, Y., Xie, R., Harper, T., Patel, N.A., et al. Epigenetic priming of enhancers predicts developmental competence of hESC-derived endodermal lineage intermediates. Cell Stem Cell 16:4 (2015), 386–399.
111. Consortium, E.P., An integrated encyclopedia of DNA elements in the human genome. Nature 489:7414 (2012), 57–74.
112. Rotem, A., Ram, O., Shoresh, N., Sperling, R.A., Goren, A., Weitz, D.A., et al. Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nature Biotechnology 33:11 (2015), 1165–1172.
113. Nagano, T., Lubling, Y., Stevens, T.J., Schoenfelder, S., Yaffe, E., Dean, W., et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature 502:7469 (2013), 59–64.
114. Buenrostro, J.D., Wu, B., Litzenburger, U.M., Ruff, D., Gonzales, M.L., Snyder, M.P., et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523:7561 (2015), 486–490.
115. Nagano, T., Lubling, Y., Yaffe, E., Wingett, S.W., Dean, W., Tanay, A., et al. Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell. Nature Protocols 10:12 (2015), 1986–2003.
116. Dey, S.S., Kester, L., Spanjaard, B., Bienko, M., van Oudenaarden, A., Integrated genome and transcriptome sequencing of the same cell. Nature Biotechnology 33:3 (2015), 285–289.
117. Macaulay, I.C., Haerty, W., Kumar, P., Li, Y.I., Hu, T.X., Teng, M.J., et al. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nature Methods 12:6 (2015), 519–522.