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Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

  • Ik Soo Kim (Department of Microbiology, Gachon University College of Medicine)
  • Received : 2022.11.04
  • Accepted : 2023.01.18
  • Published : 2023.02.28

Abstract

Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a single-cell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed single-cell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.

Keywords

Acknowledgement

This work was supported by the National Research Foundation (NRF) of Korea (2021R1F1A104962311) and the Gachon University Research Fund (GCU-202102820001).

References

  1. Abdelmoez, M.N., Iida, K., Oguchi, Y., Nishikii, H., Yokokawa, R., Kotera, H., Uemura, S., Santiago, J.G., and Shintaku, H. (2018). SINC-seq: correlation of transient gene expressions between nucleus and cytoplasm reflects single-cell physiology. Genome Biol. 19, 66.
  2. Angerer, P., Simon, L., Tritschler, S., Wolf, F.A., Fischer, D., and Theis, F.J. (2017). Single cells make big data: new challenges and opportunities in transcriptomics. Curr. Opin. Syst. Biol. 4, 85-91. https://doi.org/10.1016/j.coisb.2017.07.004
  3. Bian, S., Hou, Y., Zhou, X., Li, X., Yong, J., Wang, Y., Wang, W., Yan, J., Hu, B., Guo, H., et al. (2018). Single-cell multiomics sequencing and analyses of human colorectal cancer. Science 362, 1060-1063. https://doi.org/10.1126/science.aao3791
  4. Bhang, H.E.C., Ruddy, D.A., Krishnamurthy Radhakrishna, V., Caushi, J.X., Zhao, R., Hims, M.M., Singh, A.P., Kao, I., Rakiec, D., Shaw, P., et al. (2015). Studying clonal dynamics in response to cancer therapy using high-complexity barcoding. Nat. Med. 21, 440-448. https://doi.org/10.1038/nm.3841
  5. Buenrostro, J.D., Corces, M.R., Lareau, C.A., Wu, B., Schep, A.N., Aryee, M.J., Majeti, R., Chang, H.Y., and Greenleaf, W.J. (2018). Integrated single-cell analysis maps the continuous regulatory landscape of human hematopoietic differentiation. Cell 173, 1535-1548.e16. https://doi.org/10.1016/j.cell.2018.03.074
  6. Buenrostro, J.D., Giresi, P.G., Zaba, L.C., Chang, H.Y., and Greenleaf, W.J. (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213-1218. https://doi.org/10.1038/nmeth.2688
  7. Cao, J., Cusanovich, D.A., Ramani, V., Aghamirzaie, D., Pliner, H.A., Hill, A.J., Daza, R.M., McFaline-Figueroa, J.L., Packer, J.S., Christiansen, L., et al. (2018). Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 361, 1380-1385. https://doi.org/10.1126/science.aau0730
  8. Cao, J., Packer, J.S., Ramani, V., Cusanovich, D.A., Huynh, C., Daza, R., Qiu, X., Lee, C., Furlan, S.N., Steemers, F.J., et al. (2017). Comprehensive single-cell transcriptional profiling of a multicellular organism. Science 357, 661-667. https://doi.org/10.1126/science.aam8940
  9. Chan, M.M., Smith, Z.D., Grosswendt, S., Kretzmer, H., Norman, T.M., Adamson, B., Jost, M., Quinn, J.J., Yang, D., Jones, M.G., et al. (2019). Molecular recording of mammalian embryogenesis. Nature 570, 77-82. https://doi.org/10.1038/s41586-019-1184-5
  10. Chappell, L., Russell, A.J.C., and Voet, T. (2018). Single-cell (multi)omics technologies. Annu. Rev. Genomics Hum. Genet. 19, 15-41. https://doi.org/10.1146/annurev-genom-091416-035324
  11. Chen, A.F., Parks, B., Kathiria, A.S., Ober-Reynolds, B., Goronzy, J.J., and Greenleaf, W.J. (2022). NEAT-seq: simultaneous profiling of intra-nuclear proteins, chromatin accessibility and gene expression in single cells. Nat. Methods 19, 547-553. https://doi.org/10.1038/s41592-022-01461-y
  12. Chen, S., Lake, B.B., and Zhang, K. (2019). High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. Nat. Biotechnol. 37, 1452-1457. https://doi.org/10.1038/s41587-019-0290-0
  13. Choi, J., Chen, W., Minkina, A., Chardon, F.M., Suiter, C.C., Regalado, S.G., Domcke, S., Hamazaki, N., Lee, C., Martin, B., et al. (2022). A time-resolved, multi-symbol molecular recorder via sequential genome editing. Nature 608, 98-107. https://doi.org/10.1038/s41586-022-04922-8
  14. Choi, Y.H. and Kim, J.K. (2019). Dissecting cellular heterogeneity using single-cell RNA sequencing. Mol. Cells 42, 189-199.
  15. Chung, H., Parkhurst, C.N., Magee, E.M., Phillips, D., Habibi, E., Chen, F., Yeung, B.Z., Waldman, J., Artis, D., and Regev, A. (2021). Joint single-cell measurements of nuclear proteins and RNA in vivo. Nat. Methods 18, 1204-1212. https://doi.org/10.1038/s41592-021-01278-1
  16. Clark, S.J., Argelaguet, R., Kapourani, C.A., Stubbs, T.M., Lee, H.J., AldaCatalinas, C., Krueger, F., Sanguinetti, G., Kelsey, G., Marioni, J.C., et al. (2018). scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat. Commun. 9, 781.
  17. Datlinger, P., Rendeiro, A.F., Boenke, T., Senekowitsch, M., Krausgruber, T., Barreca, D., and Bock, C. (2021). Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing. Nat. Methods 18, 635-642. https://doi.org/10.1038/s41592-021-01153-z
  18. Dey, S.S., Kester, L., Spanjaard, B., Bienko, M., and van Oudenaarden, A. (2015). Integrated genome and transcriptome sequencing of the same cell. Nat. Biotechnol. 33, 285-289. https://doi.org/10.1038/nbt.3129
  19. Di, L., Fu, Y., Sun, Y., Li, J., Liu, L., Yao, J., Wang, G., Wu, Y., Lao, K., Lee, R.W., et al. (2020). RNA sequencing by direct tagmentation of RNA/DNA hybrids. Proc. Natl. Acad. Sci. U. S. A. 117, 2886-2893. https://doi.org/10.1073/pnas.1919800117
  20. Dimitriu, M.A., Lazar-Contes, I., Roszkowski, M., and Mansuy, I.M. (2022). Single-cell multiomics techniques: from conception to applications. Front. Cell Dev. Biol. 10, 854317.
  21. Dominguez Conde, C., Xu, C., Jarvis, L.B., Rainbow, D.B., Wells, S.B., Gomes, T., Howlett, S.K., Suchanek, O., Polanski, K., King, H.W., et al. (2022). Cross-tissue immune cell analysis reveals tissue-specific features in humans. Science 376, eabl5197.
  22. Elmentaite, R., Dominguez Conde, C., Yang, L., and Teichmann, S.A. (2022). Single-cell atlases: shared and tissue-specific cell types across human organs. Nat. Rev. Genet. 23, 395-410. https://doi.org/10.1038/s41576-022-00449-w
  23. Eng, C.H.L., Lawson, M., Zhu, Q., Dries, R., Koulena, N., Takei, Y., Yun, J., Cronin, C., Karp, C., Yuan, G.C., et al. (2019). Transcriptome-scale superresolved imaging in tissues by RNA seqFISH. Nature 568, 235-239. https://doi.org/10.1038/s41586-019-1049-y
  24. Eraslan, G., Drokhlyansky, E., Anand, S., Fiskin, E., Subramanian, A., Slyper, M., Wang, J., Van Wittenberghe, N., Rouhana, J.M., Waldman, J., et al. (2022). Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. Science 376, eabl4290.
  25. Eyler, C.E., Matsunaga, H., Hovestadt, V., Vantine, S.J., van Galen, P., and Bernstein, B.E. (2020). Single-cell lineage analysis reveals genetic and epigenetic interplay in glioblastoma drug resistance. Genome Biol. 21, 174.
  26. Eze, U.C., Bhaduri, A., Haeussler, M., Nowakowski, T.J., and Kriegstein, A.R. (2021). Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia. Nat. Neurosci. 24, 584-594. https://doi.org/10.1038/s41593-020-00794-1
  27. Fang, L., Li, G., Sun, Z., Zhu, Q., Cui, H., Li, Y., Zhang, J., Liang, W., Wei, W., Hu, Y., et al. (2021). CASB: a concanavalin A-based sample barcoding strategy for single-cell sequencing. Mol. Syst. Biol. 17, e10060.
  28. Fiskin, E., Lareau, C.A., Ludwig, L.S., Eraslan, G., Liu, F., Ring, A.M., Xavier, R.J., and Regev, A. (2022). Single-cell profiling of proteins and chromatin accessibility using PHAGE-ATAC. Nat. Biotechnol. 40, 374-381. https://doi.org/10.1038/s41587-021-01065-5
  29. Frei, A.P., Bava, F.A., Zunder, E.R., Hsieh, E.W.Y., Chen, S.Y., Nolan, G.P., and Gherardini, P.F. (2016). Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat. Methods 13, 269-275. https://doi.org/10.1038/nmeth.3742
  30. Frieda, K.L., Linton, J.M., Hormoz, S., Choi, J., Chow, K.H.K., Singer, Z.S., Budde, M.W., Elowitz, M.B., and Cai, L. (2017). Synthetic recording and in situ readout of lineage information in single cells. Nature 541, 107-111. https://doi.org/10.1038/nature20777
  31. Genshaft, A.S., Li, S., Gallant, C.J., Darmanis, S., Prakadan, S.M., Ziegler, C.G.K., Lundberg, M., Fredriksson, S., Hong, J., Regev, A., et al. (2016). Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction. Genome Biol. 17, 188.
  32. Gerlach, J.P., van Buggenum, J.A.G., Tanis, S.E.J., Hogeweg, M., Heuts, B.M.H., Muraro, M.J., Elze, L., Rivello, F., Rakszewska, A., van Oudenaarden, A., et al. (2019). Combined quantification of intracellular (phospho-) proteins and transcriptomics from fixed single cells. Sci. Rep. 9, 1469.
  33. Gu, C., Liu, S., Wu, Q., Zhang, L., and Guo, F. (2019). Integrative single-cell analysis of transcriptome, DNA methylome and chromatin accessibility in mouse oocytes. Cell Res. 29, 110-123. https://doi.org/10.1038/s41422-018-0125-4
  34. Han, K.Y., Kim, K.T., Joung, J.G., Son, D.S., Kim, Y.J., Jo, A., Jeon, H.J., Moon, H.S., Yoo, C.E., Chung, W., et al. (2018). SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells. Genome Res. 28, 75-87. https://doi.org/10.1101/gr.223263.117
  35. He, S., Wang, L.H., Liu, Y., Li, Y.Q., Chen, H.T., Xu, J.H., Peng, W., Lin, G.W., Wei, P.P., Li, B., et al. (2020). Single-cell transcriptome profiling of an adult human cell atlas of 15 major organs. Genome Biol. 21, 294.
  36. Hu, Y., Huang, K., An, Q., Du, G., Hu, G., Xue, J., Zhu, X., Wang, C.Y., Xue, Z., and Fan, G. (2016). Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol. 17, 88.
  37. Hu, Y., Zhong, J., Xiao, Y., Xing, Z., Sheu, K., Fan, S., An, Q., Qiu, Y., Zheng, Y., Liu, X., et al. (2020). Single-cell RNA cap and tail sequencing (scRCAT-seq) reveals subtype-specific isoforms differing in transcript demarcation. Nat. Commun. 11, 5148.
  38. Janssens, D.H., Otto, D.J., Meers, M.P., Setty, M., Ahmad, K., and Henikoff, S. (2022). CUT&Tag2for1: a modified method for simultaneous profiling of the accessible and silenced regulome in single cells. Genome Biol. 23, 81.
  39. Jiang, Y.R., Zhu, L., Cao, L.R., Wu, Q., Chen, J.B., Wang, Y., Wu, J., Zhang, T.Y., Wang, Z.L., Guan, Z.Y., et al. (2022). Simultaneous transcriptome and proteome profiling in a single mouse oocyte with a deep single-cell multiomics approach. BioRxiv, https://doi.org/10.1101/2022.08.17.504335
  40. Jovic, D., Liang, X., Zeng, H., Lin, L., Xu, F., and Luo, Y. (2022). Single-cell RNA sequencing technologies and applications: a brief overview. Clin. Transl. Med. 12, e694.
  41. Kim, I.S., Wu, J., Rahme, G.J., Battaglia, S., Dixit, A., Gaskell, E., Chen, H., Pinello, L., and Bernstein, B.E. (2020). Parallel single-cell RNA-seq and genetic recording reveals lineage decisions in developing embryoid bodies. Cell Rep. 33, 108222.
  42. Kumar, V., Ramnarayanan, K., Sundar, R., Padmanabhan, N., Srivastava, S., Koiwa, M., Yasuda, T., Koh, V., Huang, K.K., Tay, S.T., et al. (2022). Singlecell atlas of lineage states, tumor microenvironment, and subtype-specific expression programs in gastric cancer. Cancer Discov. 12, 670-691. https://doi.org/10.1158/2159-8290.CD-21-0683
  43. Lee, D.S., Luo, C., Zhou, J., Chandran, S., Rivkin, A., Bartlett, A., Nery, J.R., Fitzpatrick, C., O'Connor, C., Dixon, J.R., et al. (2019). Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nat. Methods 16, 999-1006. https://doi.org/10.1038/s41592-019-0547-z
  44. Lee, J., Hyeon, D.Y., and Hwang, D. (2020). Single-cell multiomics: technologies and data analysis methods. Exp. Mol. Med. 52, 1428-1442. https://doi.org/10.1038/s12276-020-0420-2
  45. Lee, S., Kim, J., and Park, J.E. (2021). Single-cell toolkits opening a new era for cell engineering. Mol. Cells 44, 127-135. https://doi.org/10.14348/molcells.2021.0002
  46. Li, G., Liu, Y., Zhang, Y., Kubo, N., Yu, M., Fang, R., Kellis, M., and Ren, B. (2019). Joint profiling of DNA methylation and chromatin architecture in single cells. Nat. Methods 16, 991-993. https://doi.org/10.1038/s41592-019-0502-z
  47. Liu, L., Liu, C., Quintero, A., Wu, L., Yuan, Y., Wang, M., Cheng, M., Leng, L., Xu, L., Dong, G., et al. (2019). Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity. Nat. Commun. 10, 470.
  48. Loveless, T.B., Grotts, J.H., Schechter, M.W., Forouzmand, E., Carlson, C.K., Agahi, B.S., Liang, G., Ficht, M., Liu, B., Xie, X., et al. (2021). Lineage tracing and analog recording in mammalian cells by single-site DNA writing. Nat. Chem. Biol. 17, 739-747. https://doi.org/10.1038/s41589-021-00769-8
  49. Lu, B., Dong, L., Yi, D., Zhang, M., Zhu, C., Li, X., and Yi, C. (2020). Transposase-assisted tagmentation of RNA/DNA hybrid duplexes. Elife 9, e54919.
  50. Lu, Y., Yang, A., Quan, C., Pan, Y., Zhang, H., Li, Y., Gao, C., Lu, H., Wang, X., Cao, P., et al. (2022). A single-cell atlas of the multicellular ecosystem of primary and metastatic hepatocellular carcinoma. Nat. Commun. 13, 4594.
  51. Luo, C., Liu, H., Xie, F., Armand, E.J., Siletti, K., Bakken, T.E., Fang, R., Doyle, W.I., Stuart, T., Hodge, R.D., et al. (2022). Single nucleus multi-omics identifies human cortical cell regulatory genome diversity. Cell Genom. 2, 100106.
  52. Ma, S., Zhang, B., LaFave, L.M., Earl, A.S., Chiang, Z., Hu, Y., Ding, J., Brack, A., Kartha, V.K., Tay, T., et al. (2020). Chromatin potential identified by shared single-cell profiling of RNA and chromatin. Cell 183, 1103-1116.e20. https://doi.org/10.1016/j.cell.2020.09.056
  53. Macaulay, I.C., Haerty, W., Kumar, P., Li, Y.I., Hu, T.X., Teng, M.J., Goolam, M., Saurat, N., Coupland, P., Shirley, L.M., et al. (2015). G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat. Methods 12, 519-522. https://doi.org/10.1038/nmeth.3370
  54. Macosko, E.Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A.R., Kamitaki, N., Martersteck, E.M., 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
  55. McGinnis, C.S., Patterson, D.M., Winkler, J., Conrad, D.N., Hein, M.Y., Srivastava, V., Hu, J.L., Murrow, L.M., Weissman, J.S., 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
  56. Mimitou, E.P., Cheng, A., Montalbano, A., Hao, S., Stoeckius, M., Legut, M., Roush, T., Herrera, A., Papalexi, E., Ouyang, Z., et al. (2019). Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat. Methods 16, 409-412. https://doi.org/10.1038/s41592-019-0392-0
  57. Mimitou, E.P., Lareau, C.A., Chen, K.Y., Zorzetto-Fernandes, A.L., Hao, Y., Takeshima, Y., Luo, W., Huang, T.S., Yeung, B.Z., Papalexi, E., et al. (2021). Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat. Biotechnol. 39, 1246-1258. https://doi.org/10.1038/s41587-021-00927-2
  58. Nomura, S. (2021). Single-cell genomics to understand disease pathogenesis. J. Hum. Genet. 66, 75-84. https://doi.org/10.1038/s10038-020-00844-3
  59. Park, S., Mali, N.M., Kim, R., Choi, J.W., Lee, J., Lim, J., Park, J.M., Park, J.W., Kim, D., Kim, T., et al. (2021). Clonal dynamics in early human embryogenesis inferred from somatic mutation. Nature 597, 393-397. https://doi.org/10.1038/s41586-021-03786-8
  60. Perkel, J.M. (2021). Single-cell analysis enters the multiomics age. Nature 595, 614-616. https://doi.org/10.1038/d41586-021-01994-w
  61. Peterson, V.M., Zhang, K.X., Kumar, N., Wong, J., Li, L., Wilson, D.C., Moore, R., McClanahan, T.K., Sadekova, S., and Klappenbach, J.A. (2017). Multiplexed quantification of proteins and transcripts in single cells. Nat. Biotechnol. 35, 936-939. https://doi.org/10.1038/nbt.3973
  62. Picelli, S., Faridani, O.R., Bjorklund, A.K., Winberg, G., Sagasser, S., and Sandberg, R. (2014). Full-length RNA-seq from single cells using Smartseq2. Nat. Protoc. 9, 171-181. https://doi.org/10.1038/nprot.2014.006
  63. Prakadan, S.M., Shalek, A.K., and Weitz, D.A. (2017). Scaling by shrinking: empowering single-cell 'omics' with microfluidic devices. Nat. Rev. Genet. 18, 345-361. https://doi.org/10.1038/nrg.2017.15
  64. Raj, B., Gagnon, J.A., and Schier, A.F. (2018). Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT. Nat. Protoc. 13, 2685-2713. https://doi.org/10.1038/s41596-018-0058-x
  65. Reyes, M., Billman, K., Hacohen, N., and Blainey, P.C. (2019). Simultaneous profiling of gene expression and chromatin accessibility in single cells. Adv. Biosyst. 3, 1900065.
  66. Rodriguez-Meira, A., Buck, G., Clark, S.A., Povinelli, B.J., Alcolea, V., Louka, E., McGowan, S., Hamblin, A., Sousos, N., Barkas, N., et al. (2019). Unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA sequencing. Mol. Cell 73, 1292-1305.e8. https://doi.org/10.1016/j.molcel.2019.01.009
  67. Rodriques, S.G., Stickels, R.R., Goeva, A., Martin, C.A., Murray, E., Vanderburg, C.R., Welch, J., Chen, L.M., Chen, F., and Macosko, E.Z. (2019). Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463-1467. https://doi.org/10.1126/science.aaw1219
  68. Rooijers, K., Markodimitraki, C.M., Rang, F.J., de Vries, S.S., Chialastri, A., de Luca, K.L., Mooijman, D., Dey, S.S., and Kind, J. (2019). Simultaneous quantification of protein-DNA contacts and transcriptomes in single cells. Nat. Biotechnol. 37, 766-772. https://doi.org/10.1038/s41587-019-0150-y
  69. Rosenberg, A.B., Roco, C.M., Muscat, R.A., Kuchina, A., Sample, P., Yao, Z., Graybuck, L.T., Peeler, D.J., 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
  70. Rubin, A.J., Parker, K.R., Satpathy, A.T., Qi, Y., Wu, B., Ong, A.J., Mumbach, M.R., Ji, A.L., Kim, D.S., Cho, S.W., et al. (2019). Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks. Cell 176, 361-376.e17. https://doi.org/10.1016/j.cell.2018.11.022
  71. Shalek, A.K., Satija, R., Adiconis, X., Gertner, R.S., Gaublomme, J.T., Raychowdhury, R., Schwartz, S., Yosef, N., Malboeuf, C., Lu, D., et al. (2013). Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498, 236-240. https://doi.org/10.1038/nature12172
  72. Stoeckius, M., Hafemeister, C., Stephenson, W., Houck-Loomis, B., Chattopadhyay, P.K., Swerdlow, H., Satija, R., and Smibert, P. (2017). Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865-868. https://doi.org/10.1038/nmeth.4380
  73. Strzelecka, P.M., Ranzoni, A.M., and Cvejic, A. (2018). Dissecting human disease with single-cell omics: application in model systems and in the clinic. Dis. Model. Mech. 11, dmm036525.
  74. Suo, C., Dann, E., Goh, I., Jardine, L., Kleshchevnikov, V., Park, J.E., Botting, R.A., Stephenson, E., Engelbert, J., Tuong, Z.K., et al. (2022). Mapping the developing human immune system across organs. Science 376, eabo0510.
  75. Swanson, E., Lord, C., Reading, J., Heubeck, A.T., Genge, P.C., Thomson, Z., Weiss, M.D.A., Li, X.J., Savage, A.K., Green, R.R., et al. (2021). Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq. Elife 10, e63632.
  76. Tabula Sapiens Consortium, Jones, R.C., Karkanias, J., Krasnow, M.A., Pisco, A.O., Quake, S.R., Salzman, J., Yosef, N., Bulthaup, B., Brown, P., et al. (2022). The Tabula Sapiens: a multiple-organ, single-cell transcriptomic atlas of humans. Science 376, eabl4896.
  77. Tang, X., Huang, Y., Lei, J., Luo, H., and Zhu, X. (2019). The single-cell sequencing: new developments and medical applications. Cell Biosci. 9, 53.
  78. Unterman, A., Sumida, T.S., Nouri, N., Yan, X., Zhao, A.Y., Gasque, V., Schupp, J.C., Asashima, H., Liu, Y., Cosme, C., Jr., et al. (2022). Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19. Nat. Commun. 13, 440.
  79. Wang, D. and Bodovitz, S. (2010). Single cell analysis: the new frontier in 'omics'. Trends Biotechnol. 28, 281-290. Wang, Y., Yuan, P., Yan, Z., Yang, M., Huo, Y., Nie, Y., Zhu, X., Qiao, J., and https://doi.org/10.1016/j.tibtech.2010.03.002
  80. Yan, L. (2021). Single-cell multiomics sequencing reveals the functional regulatory landscape of early embryos. Nat. Commun. 12, 1247.
  81. Wei, C.J.Y. and Zhang, K. (2020). RETrace: simultaneous retrospective lineage tracing and methylation profiling of single cells. Genome Res. 30, 602-610. https://doi.org/10.1101/gr.255851.119
  82. Weinreb, C., Rodriguez-Fraticelli, A., Camargo, F.D., and Klein, A.M. (2020). Lineage tracing on transcriptional landscapes links state to fate during differentiation. Science 367, eaaw3381.
  83. Weinreb, C., Wolock, S., Tusi, B.K., Socolovsky, M., and Klein, A.M. (2018). Fundamental limits on dynamic inference from single-cell snapshots. Proc. Natl. Acad. Sci. U. S. A. 115, E2467-E2476. https://doi.org/10.1073/pnas.1714723115
  84. Williams, C.G., Lee, H.J., Asatsuma, T., Vento-Tormo, R., and Haque, A. (2022). An introduction to spatial transcriptomics for biomedical research. Genome Med. 14, 68.
  85. Xing, Q.R., Farran, C.A.E., Zeng, Y.Y., Yi, Y., Warrier, T., Gautam, P., Collins, J.J., Xu, J., Droge, P., Koh, C.G., et al. (2020). Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility. Genome Res. 30, 1027-1039. https://doi.org/10.1101/gr.257840.119
  86. Xu, W., Yang, W., Zhang, Y., Chen, Y., Hong, N., Zhang, Q., Wang, X., Hu, Y., Song, K., Jin, W., et al. (2022). ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells. Nat. Methods 19, 1243-1249. https://doi.org/10.1038/s41592-022-01601-4
  87. Yan, R., Gu, C., You, D., Huang, Z., Qian, J., Yang, Q., Cheng, X., Zhang, L., Wang, H., Wang, P., et al. (2021). Decoding dynamic epigenetic landscapes in human oocytes using single-cell multi-omics sequencing. Cell Stem Cell 28, 1641-1656.e7. https://doi.org/10.1016/j.stem.2021.04.012
  88. Zhang, L., Yu, X., Zheng, L., Zhang, Y., Li, Y., Fang, Q., Gao, R., Kang, B., Zhang, Q., Huang, J.Y., et al. (2018). Lineage tracking reveals dynamic relationships of T cells in colorectal cancer. Nature 564, 268-272. https://doi.org/10.1038/s41586-018-0694-x
  89. Zhu, C., Yu, M., Huang, H., Juric, I., Abnousi, A., Hu, R., Lucero, J., Behrens, M.M., Hu, M., and Ren, B. (2019). An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome. Nat. Struct. Mol. Biol. 26, 1063-1070. https://doi.org/10.1038/s41594-019-0323-x