Volume 5 Issue 2
Dec.  2021
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Gradimir Misevic. Single cell human genomic analyses: a way to refine the knowledge of cellular heterogeneity origins in individual subject[J]. Blood&Genomics, 2021, 5(2): 83-96. doi: 10.46701/BG.2021022021112
Citation: Gradimir Misevic. Single cell human genomic analyses: a way to refine the knowledge of cellular heterogeneity origins in individual subject[J]. Blood&Genomics, 2021, 5(2): 83-96. doi: 10.46701/BG.2021022021112

Single cell human genomic analyses: a way to refine the knowledge of cellular heterogeneity origins in individual subject

doi: 10.46701/BG.2021022021112
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  • Corresponding author: Gradimir Misevic, Department of Research and Development, Gimmune GmbH, Baarerstrasse 12, 6302 Zug, Switzerland. E-mail: gradimir@gimmune.com
  • Received Date: 2021-04-15
  • Accepted Date: 2021-11-24
  • Rev Recd Date: 2021-08-20
  • Available Online: 2022-01-06
  • Publish Date: 2021-12-31
  • Single cell genomics performed on individual human subjects' tumors, neural tissues, and sperm samples revealed the existence of genetic heterogeneity arising through either mutations in exomes, deletions, recombinations, and duplications of DNA sequences, as well as aneuploidy. These genetic changes happen during cell cycles followed by cell division. The aim of this review is to strictly focus on single cell human genomics and intends to deliver information that can help to refine fundamental knowledge relating to genetic causes of cellular heterogeneity origins in both healthy and disease states. Allogenic heterogeneity as well as heterogeneity origins of cells possessing the same genome with different gene expression patterns is not the subject of this review. Future research still requires: a) improvement for complete and errorless DNA acquisition and sequencing of not only selected parts of the genome, and b) analyses of more samples that contain millions of cells. These data will deliver a more precise comparative representation of genetic diversity among single cells in an individual human subject. Consequently, we will be able to better distinguish between the role of genetic, versus epigenetic, and stochastic factors in the cellular diversity of over 30 trillion cells present in a human body.


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  • [1]
    Navin NE. The first five years of single-cell cancer genomics and beyond[J]. Genome Res, 2015, 25(10): 1499−1507. doi: 10.1101/gr.191098.115
    Human Genome Reference Program[EB/OL]. [2021-10-24]. https://www.genome.gov/Funded-Programs-Projects/Human-Genome-Reference-Program.
    Human Genome Project Results[EB/OL]. (2018-11-12) [2021-10-24]. https://www.genome.gov/human-genome-project/results.
    Genome Reference Consortium Human Build 38 patch release 13[EB/OL]. (2019-02-28) [2021-10-24]. https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26/.
    Genome Assemblies[EB/OL]. [2021-10-24]. https://www.ncbi.nlm.nih.gov/grc/data.
    Human Genome Assembly GRCh38. p13[EB/OL]. [2021-10-24]. https://www.ncbi.nlm.nih.gov/grc/human/data.
    Human (GRCh38. P13)[EB/OL]. [2021-10-24]. https://www.ensembl.org/Homo_sapiens/Info/Index.
    Cell Biology by the Numbers[EB/OL]. [2021-10-24]. http://book.bionumbers.org/.
    Shafin K, Pesout T, Lorig-Roach R, et al. Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes[J]. Nat Biotechnol, 2020, 38(9): 1044−1053. doi: 10.1038/s41587-020-0503-6
    Baslan T, Kendall J, Rodgers L, et al. Genome-wide copy number analysis of single cells[J]. Nat Protoc, 2012, 7(6): 1024−1041. doi: 10.1038/nprot.2012.039
    Bianconi E, Piovesan A, Facchin F, et al. An estimation of the number of cells in the human body[J]. Ann Hum Biol, 2013, 40(6): 463−471. doi: 10.3109/03014460.2013.807878
    Sender R, Fuchs S, Milo R. Revised estimates for the number of human and bacteria cells in the body[J]. PLoS Biol, 2016, 14(8): e1002533. doi: 10.1371/journal.pbio.1002533
    Vickaryous MK, Hall BK. Human cell type diversity, evolution, development, and classification with special reference to cells derived from the neural crest[J]. Biol Rev Camb Philos Soc, 2006, 81(3): 425−455. doi: 10.1017/S1464793106007068
    Misevic G, Garbarino E. Glycan-to-glycan binding: molecular recognition through polyvalent interactions mediates specific cell adhesion[J]. Molecules, 2021, 26(2): 397. doi: 10.3390/molecules26020397
    Svensson V, Beltrame EDV, Pachter L. A curated database reveals trends in single-cell transcriptomics[J]. Database(Oxford), 2020: baaa073.
    Bagnoli JJWB, Ziegenhain C, Janjic A, et al. McSCRB-seq protocol: version 2[EB/OL]. (2018-05-22) [2021-10-24]. https://www.protocols.io/view/mcscrb-seq-protocol-p9kdr4w.
    ScRNASeqDB[EB/OL]. [2021-10-24]. https://bioinfo.uth.edu/scrnaseqdb/.
    Gene Expression Ominbus[EB/OL]. [2021-10-24]. https://www.ncbi.nlm.nih.gov/geo/.
    Picelli S, Faridani OR, Björklund ÅK, et al. Full-length RNA-seq from single cells using Smart-seq2[J]. Nat Protoc, 2014, 9(1): 171−181. doi: 10.1038/nprot.2014.006
    The Human Protein Atlas[EB/OL]. [2021-10-24]. https://www.proteinatlas.org/.
    Uhlén M, Fagerberg L, Hallström BM, et al. Proteomics Tissue-based map of the human proteome[J]. Science, 2015, 347(6220): 1260419. doi: 10.1126/science.1260419
    Leung D, Jung I, Rajagopal N, et al. Integrative analysis of haplotype-resolved epigenomes across human tissues[J]. Nature, 2015, 518(7539): 350−354. doi: 10.1038/nature14217
    Stevens WBC, Netea MG, Kater AP, et al. 'Trained immunity': consequences for lymphoid malignancies[J]. Haematologica, 2016, 101(12): 1460−1468. doi: 10.3324/haematol.2016.149252
    Kawamura YI, Toyota M, Kawashima R, et al. DNA hypermethylation contributes to incomplete synthesis of carbohydrate determinants in gastrointestinal cancer[J]. Gastroenterology, 2008, 135(1): 142−151. doi: 10.1053/j.gastro.2008.03.031
    Saeed S, Quintin J, Kerstens HHD, et al. Epigenetic programming of monocyte-to-macrophage differentiation and trained innate immunity[J]. Science, 2014, 345(6204): 1251086. doi: 10.1126/science.1251086
    Álvarez-Errico D, Vento-Tormo R, Sieweke M, et al. Epigenetic control of myeloid cell differentiation, identity and function[J]. Nat Rev Immunol, 2015, 15(1): 7−17. doi: 10.1038/nri3777
    Stefan M, Wei C, Lombardi A, et al. Genetic-epigenetic dysregulation of thymic TSH receptor gene expression triggers thyroid autoimmunity[J]. Proc Natl Acad Sci, 2014, 111(34): 12562−12567. doi: 10.1073/pnas.1408821111
    Zou Y, Sunshine MJ, Taniuchi I, et al. Epigenetic silencing of CD4 in T cells committed to the cytotoxic lineage[J]. Nat Genet, 2001, 29(3): 332−336. doi: 10.1038/ng750
    Antony P, Rose M, Heidenreich A, et al. Epigenetic inactivation of ST6GAL1 in human bladder cancer[J]. BMC Cancer, 2014, 14: 901. doi: 10.1186/1471-2407-14-901
    Lo PK, Zhou Q. Emerging techniques in single-cell epigenomics and their applications to cancer research[J]. J Clin Genom, 2018, 1(1). doi: 10.4172/JCG.1000103
    Jerne NK, Köhler GJF, Milstein C. The Nobel Prize in physiology or medicine 1984[EB/OL] (2010-09-06) [2021-10-24]. https://www.nobelprize.org/prizes/medicine/1984/speedread/.
    Doherty PC, Zinkernagel RM. The Nobel Prize in physiology or medicine 1996[EB/OL]. (2010-09-06) [2021-10-24].https://www.nobelprize.org/prizes/medicine/1996/speedread/.
    Susumu T. The Nobel Prize in physiology or medicine 1987[EB/OL]. (2010-09-06) [2021-10-24]. https://www.nobelprize.org/prizes/medicine/1987/speedread/.
    Gao R, Davis A, McDonald TO, et al. Punctuated copy number evolution and clonal stasis in triple-negative breast cancer[J]. Nat Genet, 2016, 48(10): 1119−1130. doi: 10.1038/ng.3641
    Taylor AM, Shih J, Ha G, et al. Genomic and functional approaches to understanding cancer aneuploidy[J]. Cancer Cell, 2018, 33(4): 676−689.e3. doi: 10.1016/j.ccell.2018.03.007
    Davoli T, Uno H, Wooten EC, et al. Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy[J]. Science, 2017, 355(6322): eaaf8399. doi: 10.1126/science.aaf8399
    Wakeman JA, Hmadcha A, Soria B, et al. The immortal strand hypothesis: still non-randomly segregating opinions[J]. Biomol Concepts, 2012, 3(3): 203−211. doi: 10.1515/bmc-2011-0053
    McVean GAT, Myers SR, Hunt S, et al. The fine-scale structure of recombination rate variation in the human genome[J]. Science, 2004, 304(5670): 581−584. doi: 10.1126/science.1092500
    Coufal NG, Garcia-Perez JL, Peng GE, et al. L1 retrotransposition in human neural progenitor cells[J]. Nature, 2009, 460(7259): 1127−1131. doi: 10.1038/nature08248
    Ando Y, Kwon ATJ, Shin JW. An era of single-cell genomics consortia[J]. Exp Mol Med, 2020, 52(9): 1409−1418. doi: 10.1038/s12276-020-0409-x
    How big are genomes? [EB/OL]. [2021-10-24]. http://book.bionumbers.org/.
    Navin N, Kendall J, Troge J, et al. Tumour evolution inferred by single-cell sequencing[J]. Nature, 2011, 472(7341): 90−94. doi: 10.1038/nature09807
    What is the macromolecular composition of the cell? [EB/OL]. [2021-10-24]. http://book.bionumbers.org/how-many-proteins-are-in-a-cell/.
    Lynch M, Marinov GK. The bioenergetic costs of a gene[J]. Proc Natl Acad Sci, 2015, 112(51): 15690−15695. doi: 10.1073/pnas.1514974112
    Gross A, Schoendube J, Zimmermann S, et al. Technologies for single-cell isolation[J]. Int J Mol Sci, 2015, 16(8): 16897−16919. doi: 10.3390/ijms160816897
    Hu P, Zhang W, Xin H, et al. Single cell isolation and analysis[J]. Front Cell Dev Biol, 2016, 4: 116. doi: 10.3389/fcell.2016.00116
    Zong C, Lu S, Chapman AR, et al. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell[J]. Science, 2012, 338(6114): 1622−1626. doi: 10.1126/science.1229164
    Paolillo C, Londin E, Fortina P. Single-cell genomics[J]. Clin Chem, 2019, 65(8): 972−985. doi: 10.1373/clinchem.2017.283895
    Wang Y, Waters J, Leung ML, et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing[J]. Nature, 2014, 512(7513): 155−160. doi: 10.1038/nature13600
    Grün D, Oudenaarden AV. Design and analysis of single-cell sequencing experiments[J]. Cell, 2015, 163(4): 799−810. doi: 10.1016/j.cell.2015.10.039
    Zahn H, Steif A, Laks E, et al. Scalable whole-genome single-cell library preparation without preamplification[J]. Nat Methods, 2017, 14(2): 167−173. doi: 10.1038/nmeth.4140
    Eirew P, Steif A, Khattra J, et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution[J]. Nature, 2015, 518(7539): 422−426. doi: 10.1038/nature13952
    Kim C, Gao R, Sei E, et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing[J]. Cell, 2018, 173(4): 879−893.e13. doi: 10.1016/j.cell.2018.03.041
    Nagasawa S, Kuze Y, Maeda I, et al. Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast[J]. Commun Biol, 2021, 4(1): 438. doi: 10.1038/s42003-021-01959-9
    Li Y, Xu X, Song L, et al. Single-cell sequencing analysis characterizes common and cell-lineage-specific mutations in a muscle-invasive bladder cancer[J]. Gigascience, 2012, 1(1): 12. doi: 10.1186/2047-217X-1-12
    Xu X, Hou Y, Yin X, et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor[J]. Cell, 2012, 148(5): 886−895. doi: 10.1016/j.cell.2012.02.025
    Tan KT, Kim HJ, Carrot-Zhang J, et al. Haplotype-resolved germline and somatic alterations in renal medullary carcinomas[J]. Genome Med, 2021, 13(1): 114. doi: 10.1186/s13073-021-00929-4
    Duan M, Hao JF, Cui SJ, et al. Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing[J]. Cell Res, 2018, 28(3): 359−373. doi: 10.1038/cr.2018.11
    Hou Y, Song L, Zhu P, et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm[J]. Cell, 2012, 148(5): 873−885. doi: 10.1016/j.cell.2012.02.028
    Jan M, Snyder TM, Corces-Zimmerman MR, et al. Clonal evolution of preleukemic hematopoietic stem cells precedes human acute myeloid leukemia[J]. Sci Transl Med, 2012, 4(149): 149ra118. doi: 10.1126/scitranslmed.3004315
    Majeti R. Clonal evolution of pre-leukemic hematopoietic stem cells precedes human acute myeloid leukemia[J]. Best Pract Res Clin Haematol, 2014, 27(3–4): 229−234. doi: 10.1016/j.beha.2014.10.003
    Morita K, Wang F, Jahn K, et al. Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics[J]. Nat Commun, 2020, 11(1): 5327. doi: 10.1038/s41467-020-19119-8
    Francis JM, Zhang CZ, Maire CL, et al. EGFR variant heterogeneity in glioblastoma resolved through single-nucleus sequencing[J]. Cancer Discov, 2014, 4(8): 956−971. doi: 10.1158/2159-8290.CD-13-0879
    Gawad C, Koh W, Quake SR. Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics[J]. Proc Natl Acad Sci, 2014, 111(50): 17947−17952. doi: 10.1073/pnas.1420822111
    Wang H, Meng D, Guo H, et al. Single-cell sequencing, an advanced technology in lung cancer research[J]. Onco Targets Ther, 2021, 14: 1895−1909. doi: 10.2147/OTT.S295102
    Lohr JG, Stojanov P, Carter SL, et al. Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy[J]. Cancer Cell, 2014, 25(1): 91−101. doi: 10.1016/j.ccr.2013.12.015
    Lohr JG, Adalsteinsson VA, Cibulskis K, et al. Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer[J]. Nat Biotechnol, 2014, 32(5): 479−484. doi: 10.1038/nbt.2892
    Heitzer E, Auer M, Gasch C, et al. Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing[J]. Cancer Res, 2013, 73(10): 2965−2975. doi: 10.1158/0008-5472.CAN-12-4140
    Ni X, Zhuo M, Su Z, et al. Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients[J]. Proc Natl Acad Sci, 2013, 110(52): 21083−21088. doi: 10.1073/pnas.1320659110
    Satas G, Zaccaria S, Mon G, et al. Scarlet: single-cell tumor phylogeny inference with copy-number constrained mutation losses[J]. Cell Syst, 2020, 10(4): 323−332.e8. doi: 10.1016/j.cels.2020.04.001
    Wang RJ, Lin DY, Jiang YC. Scope: a normalization and copy-number estimation method for single-cell DNA sequencing[J]. Cell Syst, 2020, 10(5): 445−452.e6. doi: 10.1016/j.cels.2020.03.005
    Chen ZW, Gong FZ, Wan L, et al. RobustClone: a robust PCA method for tumor clone and evolution inference from single-cell sequencing data[J]. Bioinformatics, 2020, 36(11): 3299−3306. doi: 10.1093/bioinformatics/btaa172
    Zaccaria S, Raphael BJ. Characterizing allele- and haplotype-specific copy numbers in single cells with CHISEL[J]. Nat Biotechnol, 2021, 39(2): 207−214. doi: 10.1038/s41587-020-0661-6
    Myers MA, Zaccaria S, Raphael BJ. Identifying tumor clones in sparse single-cell mutation data[J]. Bioinformatics, 2020, 36: i186−i193. doi: 10.1093/bioinformatics/btaa449
    Ferronika P, Bos HVD, Taudt A, et al. Copy number alterations assessed at the single-cell level revealed mono- and polyclonal seeding patterns of distant metastasis in a small-cell lung cancer patient[J]. Ann Oncol, 2017, 28(7): 1668−1670. doi: 10.1093/annonc/mdx182
    Kaur P, Campo D, Porras TB, et al. A pilot study for the feasibility of exome-sequencing in circulating tumor cells versus single metastatic biopsies in breast cancer[J]. Int J Mol Sci, 2020, 21(14): 1−29. doi: 10.3390/ijms21144826
    Keller L, Pantel K. Unravelling tumour heterogeneity by single-cell profiling of circulating tumour cells[J]. Nat Rev Cancer, 2019, 19(10): 553−567. doi: 10.1038/s41568-019-0180-2
    Liu RY, Gao QS, Foltz SM, et al. Co-evolution of tumor and immune cells during progression of multiple myeloma[J]. Nat Commun, 2021, 12(1): 2559. doi: 10.1038/s41467-021-22804-x
    Wu CY, Lau BT, Kim HS, et al. Integrative single-cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer[J]. Nat Biotechnol, 2021, 39(10): 1259−1269. doi: 10.1038/s41587-021-00911-w
    Nieto P, Elosua-Bayes M, Trincado JL, et al. A single-cell tumor immune atlas for precision oncology[J]. Genome Res, 2021, 31(10): 1913−1926. doi: 10.1101/gr.273300.120
    Cai X, Evrony GD, Lehmann HS, et al. Single-cell, genome-wide sequencing identifies clonal somatic copy-number variation in the human brain[J]. Cell Rep, 2015, 10(4): 645. doi: 10.1016/j.celrep.2015.01.028
    McConnell MJ, Lindberg MR, Brennand KJ, et al. Mosaic copy number variation in human neurons[J]. Science, 2013, 342(6158): 632−637. doi: 10.1126/science.1243472
    Rehen SK, McConnell MJ, Kaushal D, et al. Chromosomal variation in neurons of the developing and adult mammalian nervous system[J]. Proc Natl Acad Sci, 2001, 98(23): 13361−13366. doi: 10.1073/pnas.231487398
    Knouse KA, Wu J, Whittaker CA, et al. Single cell sequencing reveals low levels of aneuploidy across mammalian tissues[J]. Proc Natl Acad Sci, 2014, 111(37): 13409−13414. doi: 10.1073/pnas.1415287111
    Wang J, Fan HC, Behr B, et al. Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm[J]. Cell, 2012, 150(2): 402−412. doi: 10.1016/j.cell.2012.06.030
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