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Review Articles

Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities

, , & ORCID Icon
Pages 202-217 | Received 07 Aug 2022, Accepted 08 Dec 2022, Published online: 12 Feb 2023

References

  • Shen C, Li D, He R, et al. Comparative transcriptome analysis of RNA-seq data for cold-tolerant and cold-sensitive rice genotypes under cold stress. J. Plant Biol. 2014;57(6):337–348.
  • Weng JK, Ye M, Li B, et al. Co-evolution of hormone metabolism and signaling networks expands plant adaptive plasticity. Cell. 2016;166(4):881–893.
  • White JA, Todd J, Newman T, et al. A new set of arabidopsis expressed sequence tags from developing seeds. The metabolic pathway from carbohydrates to seed oil. Plant Physiol. 2000;124(4):1582–1594.
  • Lister R, O'Malley RC, Tonti-Filippini J, et al. Highly integrated single-base resolution maps of the epigenome in arabidopsis. Cell. 2008;133(3):523–536.
  • Hong JH, Savina M, Du J, et al. A sacrifice-for-survival mechanism protects root stem cell niche from chilling stress. Cell. 2017;170(1):102–113.e14.
  • Dietrich D, Pang L, Kobayashi A, et al. Root hydrotropism is controlled via a cortex-specific growth mechanism. Nat. Plants. 2017;3(6):1–8.
  • Shaw R, Tian X, Xu J. Single-cell transcriptome analysis in plants: advances and challenges. Mol Plant. 2021;14(1):115–126.
  • Ryu KH, Huang L, Kang HM, et al. Single-cell RNA sequencing resolves molecular relationships among individual plant cells. Plant Physiol. 2019;179(4):1444–1456.
  • Aldridge S, Teichmann SA. Single cell transcriptomics comes of age. Nat Commun. 2020;11(1):4.
  • Loo L, Simon JM, Xing L, et al. Single-cell transcriptomic analysis of mouse neocortical development. Nat Commun. 2019;10(1):11.
  • Hammond TR, Dufort C, Dissing-Olesen L, et al. Single-cell RNA sequencing of microglia throughout the mouse lifespan and in the injured brain reveals complex cell-state changes. Immunity. 2019;50(1):253–271.e6.
  • Chen A, Liao S, Cheng M, et al. Large field of view-spatially resolved transcriptomics at nanoscale resolution. BioRxiv. 2021. DOI:10.1101/2021.01.17.427004
  • Patiño M, Lagos WN, Patne NS, et al. Single-cell transcriptomic classification of rabies-infected cortical neurons. Proc Natl Acad Sci USA. 2022;119:2203677119.
  • Kabir MF, Karami AL, Cruz-Acuña R, et al. Single cell transcriptomic analysis reveals cellular diversity of murine esophageal epithelium. Nat Commun. 2022;13(1):15.
  • Onoda N, Kawabata A, Hasegawa K, et al. Spatial and single-cell transcriptome analysis reveals changes in gene expression in response to drug perturbation in rat kidney. DNA Res. 2022;29:007.
  • Regev A, Teichmann SA, Lander ES, Human Cell Atlas Meeting Participants, et al. Human cell atlas meeting participants. The human cell atlas. Elife. 2017;6:27041.
  • Wilbrey-Clark A, Roberts K, Teichmann SA. Cell atlas technologies and insights into tissue architecture. Biochem J. 2020;477(8):1427–1442.
  • Rhee SY, Birnbaum KD, Ehrhardt DW. Towards building a plant cell atlas. Trends Plant Sci. 2019;24(4):303–310.
  • Shulse CN, Cole BJ, Ciobanu D, et al. High-throughput single-cell transcriptome profiling of plant cell types. Cell Rep. 2019;27(7):2241–2247.e4.
  • Denyer T, Ma X, Klesen S, et al. Spatiotemporal developmental trajectories in the arabidopsis root revealed using high-throughput single-cell RNA sequencing. Dev Cell. 2019;48(6):840–852.e5.
  • Jean-Baptiste K, McFaline-Figueroa JL, Alexandre CM, et al. Dynamics of gene expression in single root cells of Arabidopsis thaliana. Plant Cell. 2019;31(5):993–1011.
  • Turco GM, Rodriguez-Medina J, Siebert S, et al. Molecular mechanisms driving switch behavior in xylem cell differentiation. Cell Rep. 2019;28(2):342–351.e4.
  • Zhang TQ, Xu ZG, Shang GD, et al. A single-cell RNA sequencing profiles the developmental landscape of arabidopsis root. Mol Plant. 2019;12(5):648–660.
  • Farmer A, Thibivilliers S, Ryu KH, et al. The impact of chromatin remodeling on gene expression at the single cell level in Arabidopsis thaliana. bioRxiv. 2020. DOI:10.1101/2020.07.27.223156
  • Kim JY, Symeonidi E, Pang TY, et al. Distinct identities of leaf phloem cells revealed by single cell transcriptomics. Plant Cell. 2021;33(3):511–530.
  • Lopez-Anido CB, Vatén A, Smoot NK, et al. Single-cell resolution of lineage trajectories in the arabidopsis stomatal lineage and developing leaf. Dev Cell. 2021;56(7):1043–1055.e4.
  • Xia K, Sun HX, Li J, et al. The single-cell stereo-seq reveals region-specific cell subtypes and transcriptome profiling in arabidopsis leaves. Dev Cell. 2022;57(10):1299–1310.e4.
  • Crosetto N, Bienko M, Van Oudenaarden A. Spatially resolved transcriptomics and beyond. Nat Rev Genet. 2015;16(1):57–66.
  • Rodriques SG, Stickels RR, Goeva A, et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463–1467.
  • Vickovic S, Eraslan G, Salmén F, et al. High-definition spatial transcriptomics for in situ tissue profiling. Nat Methods. 2019;16(10):987–990.
  • Stickels RR, Murray E, Kumar P, et al. Sensitive spatial genome wide expression profiling at cellular resolution. BioRxiv. 2020. DOI:10.1101/2020.03.12.989806
  • Mortazavi A, Williams BA, McCue K, et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5(7):621–628.
  • Chen G, Ning B, Shi T. Single-cell RNA-seq technologies and related computational data analysis. Front Genet. 2019;10:317.
  • Kubo M, Nishiyama T, Tamada Y, et al. Single-cell transcriptome analysis of physcomitrella leaf cells during reprogramming using microcapillary manipulation. Nucleic Acids Res. 2019;47(9):4539–4553.
  • Song Q, Ando A, Jiang N, et al. Single-cell RNA-seq analysis reveals ploidy-dependent and cell-specific transcriptome changes in arabidopsis female gametophytes. Genome Biol. 2020;21(1):18.
  • Xu X, Crow M, Rice BR, et al. Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery. Dev Cell. 2021;56(4):557–568.e6.
  • Satterlee JW, Strable J, Scanlon MJ. Plant stem-cell organization and differentiation at single-cell resolution. Proc Natl Acad Sci U S A. 2020;117(52):33689–33699.
  • Roszak P, Heo JO, Blob B, et al. Analysis of phloem trajectory links tissue maturation to cell specialization. BioRxiv. 2021. DOI:10.1101/2021.01.18.427084
  • Coate JE, Farmer AD, Schiefelbein JW, et al. Expression partitioning of duplicate genes at single cell resolution in arabidopsis roots. Front Genet. 2020;11:596150.
  • Liu Q, Liang Z, Feng D, et al. Transcriptional landscape of rice roots at the single-cell resolution. Mol Plant. 2021;14(3):384–394.
  • Efroni I, Mello A, Nawy T, et al. Root regeneration triggers an embryo-like sequence guided by hormonal interactions. Cell. 2016;165(7):1721–1733.
  • Zheng GX, Terry JM, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun. 2017;8:14049–14012.
  • Shahan R, Hsu CW, Nolan TM, et al. A single-cell arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants. Dev Cell. 2022;57(4):543–560.e9.
  • Butler A, Hoffman P, Smibert P, et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol. 2018;36(5):411–420.
  • Jiao Y, Peluso P, Shi J, et al. Improved maize reference genome with single-molecule technologies. Nature. 2017;546(7659):524–527.
  • The Arabidopsis Genome Initiative. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature. 2000;408:796–815.
  • Wendrich JR, Yang B, Vandamme N, et al. Vascular transcription factors guide plant epidermal responses to limiting phosphate conditions. Science. 2020;370(6518):4970.
  • McInnes L, Healy J, Melville J. 2018. Umap: uniform manifold approximation and projection for dimension reduction. arXiv. 2018;1802.03426.
  • Becht E, McInnes L, Healy J, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2019;37(1):38–44.
  • Dorrity MW, Alexandre CM, Hamm MO, et al. The regulatory landscape of Arabidopsis thaliana roots at single-cell resolution. Nat Commun. 2021;12(1).
  • Gala HP, Lanctot A, Jean-Baptiste K, et al. A single-cell view of the transcriptome during lateral root initiation in Arabidopsis thaliana. Plant Cell. 2021;33(7):2197–2220.
  • Hicks SC, Townes FW, Teng M, et al. Missing data and technical variability in single-cell RNA-sequencing experiments. Biostatistics. 2018;19(4):562–578.
  • Wang Y, Huan Q, Chu X, et al. Single-cell transcriptome analyses recapitulate the cellular and developmental responses to abiotic stresses in rice. BioRxiv. 2020. DOI:10.1101/2020.01.30.926329
  • Chestnut B, Casie Chetty S, Koenig AL, et al. Single-cell transcriptomic analysis identifies the conversion of zebrafish Etv2-deficient vascular progenitors into skeletal muscle. Nat Commun. 2020;11(1):1–16.
  • Klimovich A, Giacomello S, Björklund Å, et al. Prototypical pacemaker neurons interact with the resident microbiota. Proc Natl Acad Sci USA. 2020;117(30):17854–17863.
  • Hou Z, Liu Y, Zhang M, et al. High-throughput single-cell transcriptomics reveals the female germline differentiation trajectory in Arabidopsis thaliana. Commun Biol. 2021;4(1):1–16.
  • Liu G, Li J, Li JM, et al. Single-cell transcriptome reveals the redifferentiation trajectories of the early stage of de novo shoot regeneration in Arabidopsis thaliana. bioRxiv. 2022. DOI:10.1101/2022.01.01.474510
  • Birnbaum K, Shasha DE, Wang JY, et al. A gene expression map of the arabidopsis root. Science. 2003;302(5652):1956–1960.
  • Li S, Yamada M, Han X, et al. High-resolution expression map of the arabidopsis root reveals alternative splicing and lincRNA regulation. Dev Cell. 2016;39(4):508–522.
  • Liu Z, Zhou Y, Guo J, et al. Global dynamic molecular profiling of stomatal lineage cell development by single-cell RNA sequencing. Mol Plant. 2020a;13(8):1178–1193.
  • Habib N, Avraham-Davidi I, Basu A, et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat Methods. 2017;14:955–958.
  • Tian C, Du Q, Xu M, et al. Single-nucleus RNA-seq resolves spatiotemporal developmental trajectories in the tomato shoot apex. bioRxiv. 2020. DOI:10.1101/2020.09.20.305029
  • Conde D, Triozzi PM, Balmant KM, et al. A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus populus. PLOS One. 2021;16(5):e0251149.
  • Liu Y, Yang M, Deng Y, et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell. 2020b;183(6):1665–1681.e18.
  • Stickels RR, Murray E, Kumar P, et al. Highly sensitive spatial transcriptomics at near-cellular resolution with slide-seqV2. Nat Biotechnol. 2021;39(3):313–319.
  • Chen D, Sun J, Zhu J, et al. Single cell atlas for 11 non-model mammals, reptiles and birds. Nat Commun. 2021;12(1):17.
  • Bergenstråhle J, Larsson L, Lundeberg J. Seamless integration of image and molecular analysis for spatial transcriptomics workflows. BMC Genom. 2020;21:1–7.
  • Ståhl PL, Salmén F, Vickovic S, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353(6294):78–82.
  • Liang S-B, Fu L-W. Application of single-cell technology in cancer research. Biotechnol Adv. 2017;35(4):443–449.
  • Choi H, Lee EJ, Shin JS, et al. Spatiotemporal characterization of glial cell activation in an ALZHEIMER’S disease model by spatially resolved transcriptome. Biorxiv. 2021. DOI:10.1101/2021.06.28.450154
  • Zheng B, Fang L. Spatially resolved transcriptomics provide a new method for cancer research. J Exp Clin Cancer Res. 2022;41:1–12.
  • Giacomello S, Salmén F, Terebieniec BK, et al. Spatially resolved transcriptome profiling in model plant species. Nat Plants. 2017;3(6):1–11.
  • Lubeck E, Coskun AF, Zhiyentayev T, et al. Single-cell in situ RNA profiling by sequential hybridization. Nat Methods. 2014;11(4):360–361.
  • Moffitt JR, Hao J, Wang G, et al. High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization. Proc Natl Acad Sci USA. 2016;113(39):11046–11051.
  • Pour M, Yanai I. New adventures in spatial transcriptomics. Dev Cell. 2022;57(10):1209–1210.
  • Giacomello S, Lundeberg J. Preparation of plant tissue to enable spatial transcriptomics profiling using barcoded microarrays. Nat Protoc. 2018;13(11):2425–2446.
  • Nystedt B, Street NR, Wetterbom A, et al. The Norway spruce genome sequence and conifer genome evolution. Nature. 2013;497(7451):579–584.
  • Street NR, Sjödin A, Bylesjö M, et al. A cross-species transcriptomics approach to identify genes involved in leaf development. BMC Genom. 2008;9:1–18.
  • Ruan YL. Sucrose metabolism: gateway to diverse carbon use and sugar signaling. Annu Rev Plant Biol. 2014;65:33–67.
  • Asp M, Giacomello S, Larsson L, et al. A spatiotemporal organ-wide gene expression and cell atlas of the developing human heart. Cell. 2019;179(7):1647–1660.e19.
  • Abdullah AS, Moffat CS, Lopez-Ruiz FJ, et al. Host–multi-pathogen warfare: pathogen interactions in co-infected plants. Front Plant Sci. 2017;8:1806.
  • Zhang L, Zhang M, Huang S, et al. A highly conserved core bacterial microbiota with nitrogen-fixation capacity inhabits the xylem sap in maize plants. Nat Commun. 2022a;13(1):1–13.
  • Zhao J, Lu Z, Wang L, et al. Plant responses to heat stress: physiology, transcription, noncoding RNAs, and epigenetics. IJMS. 2020;22(1):117.
  • Zhang H, Zhu J, Gong Z, et al. Abiotic stress responses in plants. Nat Rev Genet. 2022b;23(2):104–119.
  • MacLean AM, Bravo A, Harrison MJ. Plant signaling and metabolic pathways enabling arbuscular mycorrhizal symbiosis. Plant Cell. 2017;29(10):2319–2335.
  • Imdahl F, Vafadarnejad E, Homberger C, et al. Single-cell RNA-sequencing reports growth-condition-specific global transcriptomes of individual bacteria. Nat Microbiol. 2020;5(10):1202–1206.
  • Kuchina A, Brettner LM, Paleologu L, et al. Microbial single-cell RNA sequencing by split-Pool barcoding. Science. 2021;371(6531):5257.
  • Liu Z, Guo C, Wu R, et al. Identification of the regulators of epidermis development under drought-and salt-stressed conditions by single-cell RNA-Seq. IJMS. 2022;23(5):2759.
  • Cole B, Bergmann D, Blaby-Haas CE, et al. Plant single-cell solutions for energy and the environment. Commun Biol. 2021;4(1):12.
  • Marand AP, Chen Z, Gallavotti A, et al. A cis-regulatory atlas in maize at single-cell resolution. Cell. 2021;184(11):3041–3055.e21.
  • Ortiz-Ramírez C, Araujo PCD, Zhang S, et al. Ground tissue circuitry regulates organ complexity in cereal roots. BioRxiv. 2021. DOI:10.1101/2021.04.28.441892
  • Shao X, Liao J, Lu X, et al. scCATCH: automatic annotation on cell types of clusters from single-cell RNA sequencing data. Iscience. 2020;23(3):100882.
  • Pliner HA, Shendure J, Trapnell C. Supervised classification enables rapid annotation of cell atlases. Nat Methods. 2019;16(10):983–986.
  • Lin Y, Cao Y, Kim HJ, et al. scClassify: sample size estimation and multiscale classification of cells using single and multiple reference. Mol Syst Biol. 2020;16(6):9389.
  • Fu R, Gillen AE, Sheridan RM, et al. Clustifyr: an R package for automated single-cell RNA sequencing cluster classification. F1000Res. 2020;9:223.
  • Kimmel JC, Kelley DR. Semisupervised adversarial neural networks for single-cell classification. Genome Res. 2021;31(10):1781–1793.
  • Alberts B, Johnson A, Lewis J, et al. 2002. Molecular biology of the cell. 4th edition. New York: Garland Science; The Plant Cell Wall.
  • Sheen J. Signal transduction in maize and arabidopsis mesophyll protoplasts. Plant Physiol. 2001;127(4):1466–1475.
  • Nakazono M, Qiu F, Borsuk LA, et al. Laser-capture microdissection, a tool for the global analysis of gene expression in specific plant cell types: identification of genes expressed differentially in epidermal cells or vascular tissues of maize. Plant Cell. 2003;15(3):583–596.
  • Ohtsu K, Smith MB, Emrich SJ, et al. Global gene expression analysis of the shoot apical meristem of maize (Zea mays L.). Plant J. 2007;52(3):391–404.
  • Turco GM, Kajala K, Kunde‐Ramamoorthy G, et al. DNA methylation and gene expression regulation associated with vascularization in Sorghum bicolor. New Phytol. 2017;214(3):1213–1229.
  • Rodriguez-Villalon A, Brady SM. Single cell RNA sequencing and its promise in reconstructing plant vascular cell lineages. Curr Opin Plant Biol. 2019;48:47–56.
  • La Manno G, Soldatov R, Zeisel A, et al. RNA velocity of single cells. Nature. 2018;560(7719):494–498.
  • Bergen V, Lange M, Peidli S, et al. Generalizing RNA velocity to transient cell states through dynamical modeling. Nat Biotechnol. 2020;38(12):1408–1414.
  • Trapnell C, Cacchiarelli D, Grimsby J, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol. 2014;32(4):381–386.
  • Setty M, Kiseliovas V, Levine J, et al. Characterization of cell fate probabilities in single-cell data with palantir. Nat Biotechnol. 2019;37(4):451–460.
  • Lange M, Bergen V, Klein M, et al. CellRank for directed single-cell fate mapping. Nat Methods. 2022;19(2):159–170.
  • Dann E, Henderson NC, Teichmann SA, et al. Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol. 2022;40(2):245–253.
  • Korsunsky I, Millard N, Fan J, et al. Fast, sensitive and accurate integration of single-cell data with harmony. Nat Methods. 2019;16(12):1289–1296.
  • Stuart T, Butler A, Hoffman P, et al. Comprehensive integration of single-cell data. Cell. 2019;177(7):1888–1902.e21.
  • Kang JB, Nathan A, Weinand K, et al. Efficient and precise single-cell reference atlas mapping with symphony. Nat Commun. 2021;12(1):21.
  • Satija R, Farrell JA, Gennert D, et al. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol. 2015;33(5):495–502.
  • Wolf FA, Angerer P, Theis FJ. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 2018;19(1):5.
  • Pereira WJ, Almeida FM, Conde D, et al. Asc-Seurat: analytical single-cell Seurat-based web application. BMC Bioinform. 2021;22:1–14.
  • Tarashansky AJ, Musser JM, Khariton M, et al. Mapping single-cell atlases throughout metazoa unravels cell type evolution. Elife. 2021;10:e66747.
  • Fujii T, Matsuda S, Tejedor ML, et al. Direct metabolomics for plant cells by live single-cell mass spectrometry. Nat Protoc. 2015;10(9):1445–1456.
  • Kang M, Choi Y, Kim H, et al. Single-cell RNA-sequencing of Nicotiana attenuata corolla cells reveals the biosynthetic pathway of a floral scent. New Phytol. 2022;234(2):527–544.
  • Schreiber L. Transport barriers made of cutin, suberin and associated waxes. Trends Plant Sci. 2010;15(10):546–553.
  • Cohen H, Fedyuk V, Wang C, et al. SUBERMAN regulates developmental suberization of the arabidopsis root endodermis. 2020;102:431–447.
  • Kumar G, Shekh A, Jakhu S, et al. Bioengineering of microalgae: recent advances, perspectives, and regulatory challenges for industrial application. Front Bioeng Biotechnol. 2020;8:914.
  • Sudmant PH, Alexis MS, Burge CB. Meta-analysis of RNA-seq expression data across species, tissues and studies. Genome Biol. 2015;16(1):11.
  • Watanabe K, Umićević Mirkov M, de Leeuw CA, et al. Genetic mapping of cell type specificity for complex traits. Nat Commun. 2019;10(1):13.
  • Buettner F, Natarajan KN, Casale FP, et al. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat Biotechnol. 2015;33(2):155–160.
  • Chen S, Lake BB, Zhang K. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. Nat Biotechnol. 2019;37(12):1452–1457.
  • Petryszak R, Keays M, Tang YA, et al. Expression atlas update—an integrated database of gene and protein expression in humans, animals and plants. Nucleic Acids Res. 2016;44(D1):D746–D752.
  • Waese J, Fan J, Pasha A, et al. ePlant: visualizing and exploring multiple levels of data for hypothesis generation in plant biology. Plant Cell. 2017;29(8):1806–1821.
  • Xing QR, El Farran CA, Zeng YY, et al. Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility. Genome Res. 2020;30(7):1027–1039.
  • Ma S, Zhang B, LaFave LM, et al. Chromatin potential identified by shared single-cell profiling of RNA and chromatin. Cell. 2020;183(4):1103–1116.e20.
  • Haque A, Engel J, Teichmann SA, et al. Practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. Genome Med. 2017;9(1):75.
  • Hwang B, Lee JH, Bang D. Single-cell RNA sequencing technologies and bioinformatics pipelines. Exp Mol Med. 2018;50(8):1–14.
  • Przytycki PF, Pollard KS. CellWalker integrates single-cell and bulk data to resolve regulatory elements across cell types in complex tissues. Genome Biol. 2021;22(1):61.
  • Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods. 2009;6(5):377–382.
  • Islam S, Kjällquist U, Moliner A, et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res. 2011;21(7):1160–1167.
  • Islam S, Kjällquist U, Moliner A, et al. Highly multiplexed and strand-specific single-cell RNA 5′ end sequencing. Nat Protoc. 2012;7(5):813–828.
  • Ramsköld D, Luo S, Wang YC, et al. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol. 2012;30(8):777–782.
  • Hashimshony T, Wagner F, Sher N, et al. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep. 2012;2(3):666–673.
  • Sasagawa Y, Nikaido I, Hayashi T, et al. Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity. Genome Biol. 2013;14(4):R31–17.
  • Picelli S, Björklund ÅK, Faridani OR, et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods. 2013;10(11):1096–1098.
  • Jaitin DA, Kenigsberg E, Keren-Shaul H, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science. 2014;343(6172):776–779.
  • Macosko EZ, Basu A, Satija R, et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell. 2015;161(5):1202–1214.
  • Fan X, Zhang X, Wu X, et al. Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos. Genome Biol. 2015;16(1):17.
  • Fan HC, Fu GK, Fodor SP. Combinatorial labeling of single cells for gene expression cytometry. Science. 2015;347(6222):1258367.
  • Klein AM, Mazutis L, Akartuna I, et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell. 2015;161(5):1187–1201.
  • Macaulay IC, Haerty W, Kumar P, et al. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods. 2015;12(6):519–522.
  • Dey SS, Kester L, Spanjaard B, et al. Integrated genome and transcriptome sequencing of the same cell. Nat Biotechnol. 2015;33(3):285–289.
  • Hashimshony T, Senderovich N, Avital G, et al. CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq. Genome Biol. 2016;17(1):1–7.
  • Hu P, Zhang W, Xin H, et al. Single cell isolation and analysis. Front Cell Dev Biol. 2016a;4:116.
  • Angermueller C, Clark SJ, Lee HJ, et al. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat Methods. 2016;13(3):229–232.
  • Hu Y, Huang K, An Q, et al. Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol. 2016b;17(1):11.
  • Genshaft AS, Li S, Gallant CJ, et al. Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction. Genome Biol. 2016;17(1):15.
  • Frei AP, Bava FA, Zunder ER, et al. Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat Methods. 2016;13(3):269–275.
  • Gierahn TM, Wadsworth MH, Hughes TK, et al. Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nat Methods. 2017;14(4):395–398.
  • Goldstein LD, Chen YJJ, Dunne J, et al. Massively parallel Nanowell-based single-cell gene expression profiling. BMC Genom. 2017;18:1–10.
  • Sheng K, Cao W, Niu Y, et al. Effective detection of variation in single-cell transcriptomes using MATQ-seq. Nat Methods. 2017;14(3):267–270.
  • Cao J, Packer JS, Ramani V, et al. Comprehensive single-cell transcriptional profiling of a multicellular organism. Science. 2017;357(6352):661–667.
  • Stoeckius M, Hafemeister C, Stephenson W, et al. Simultaneous epitope and transcriptome measurement in single cells. Nat Methods. 2017;14(9):865–868.
  • Peterson VM, Zhang KX, Kumar N, et al. Multiplexed quantification of proteins and transcripts in single cells. Nat Biotechnol. 2017;35(10):936–939.
  • Rosenberg AB, Roco CM, Muscat RA, et al. SPLiT-seq reveals cell types and lineages in the developing brain and spinal cord. Science. 2018;360(6385):176–182.
  • Cao J, Cusanovich DA, Ramani V, et al. Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science. 2018;361(6409):1380–1385.
  • Clark SJ, Argelaguet R, Kapourani CA, et al. scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat Commun. 2018;9(1):1–9.
  • Sasagawa Y, Danno H, Takada H, et al. Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads. Genome Biol. 2018;19(1):24.
  • Han KY, Kim KT, Joung JG, et al. SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells. Genome Res. 2018;28(1):75–87.
  • Rodriguez-Meira A, Buck G, Clark SA, et al. Unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA sequencing. Mol Cell. 2019;73(6):1292–1305.e8.
  • Zhu C, Yu M, Huang H, et al. An ultra-high-throughput method for single-cell joint analysis of open chromatin and transcriptome. Nat Struct Mol Biol. 2019;26(11):1063–1070.
  • Gerlach J, van Buggenum JA, Tanis SE, et al. Combined quantification of intracellular (phospho-) proteins and transcriptomics from fixed single cells. Sci Rep. 2019;9(1):10.
  • Mimitou EP, Cheng A, Montalbano A, et al. Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat Methods. 2019;16(5):409–412.
  • Hagemann-Jensen M, Ziegenhain C, Chen P, et al. Single-cell RNA counting at allele and isoform resolution using smart-seq3. Nat Biotechnol. 2020;38(6):708–714.
  • Zhang TQ, Chen Y, Liu Y, et al. Single-cell transcriptome atlas and chromatin accessibility landscape reveal differentiation trajectories in the rice root. Nat Commun. 2021;12(1):1–12.
  • Wang Y, Huan Q, Li K, et al. Single-cell transcriptome atlas of the leaf and root of rice seedlings. J Genet Genomics. 2021;48(10):881–898.
  • Bezrutczyk M, Zöllner NR, Kruse CP, et al. Evidence for phloem loading via the abaxial bundle sheath cells in maize leaves. Plant Cell. 2021;33(3):531–547.
  • Xie J, Li M, Zeng J, et al. Single-cell RNA sequencing profiles of stem-differentiating xylem in poplar. Plant Biotechnol J. 2022;20(3):417–419.
  • Liu C, Leng J, Li Y, et al. A spatiotemporal atlas of organogenesis in the development of orchid flowers. Nucleic Acids Res. 2022c;50(17):9724–9737.
  • Apelt F, Mavrothalassiti E, Gupta S, et al. Shoot and root single cell sequencing reveals tissue- and daytime-specific transcriptome profiles. Plant Physiol. 2022;188(2):861–878.

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