참고문헌
- Lipsett DB, Frisk M, Aronsen JM et al (2019) Cardiomyocyte substructure reverts to an immature phenotype during heart failure. J Physiol 597, 1833-1853 https://doi.org/10.1113/jp277273
- Eberwine J, Sul JY, Bartfai T and Kim J (2014) The promise of single-cell sequencing. Nat Methods 11, 25-27 https://doi.org/10.1038/nmeth.2769
- Olsen TK, Baryawno N (2018) Introduction to single-cell RNA sequencing. Curr Protoc Mol Biol 122, 1-14
- Tang F, Barbacioru C, Wang Y et al (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6, 377-382 https://doi.org/10.1038/nmeth.1315
- Chen G, Ning B and Shi T (2019) Single-cell RNA-seq technologies and related computational data analysis. Front Genet 10, 1-13 https://doi.org/10.3389/fgene.2019.00001
- Ziegenhain C, Vieth B, Parekh S et al (2017) Comparative analysis of single-cell RNA sequencing methods. Mol Cell 65, 631-643 e634 https://doi.org/10.1016/j.molcel.2017.01.023
- Ramskold D, Luo S, Wang YC et al (2012) Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 30, 777-782 https://doi.org/10.1038/nbt.2282
- Sasagawa Y, Nikaido I, Hayashi T et al (2013) Quartz-Seq: A highly reproducible and sensitive single-cell RNA sequencing method, reveals nongenetic gene-expression heterogeneity. Genome Biol 14, 1-17
- Qian X, Harris KD, Hauling T et al (2020) Probabilistic cell typing enables fine mapping of closely related cell types in situ. Nat Methods 17, 101-106 https://doi.org/10.1038/s41592-019-0631-4
- Stahl PL, Salmen F, Vickovic S et al (2016) Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78-82 https://doi.org/10.1126/science.aaf2403
- Tang X, Huang Y, Lei J, Luo H, Zhu X (2019) The single-cell sequencing: New developments and medical applications. Cell Biosci 9, 1-9 https://doi.org/10.1186/s13578-018-0263-x
- Rodriques SG, Stickels RR, Goeva A et al (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
- Kulkarni A, Anderson AG, Merullo DP and Konopka G (2019) Beyond bulk: a review of single cell transcriptomics methodologies and applications. Curr Opin Biotechnol 58, 129-136 https://doi.org/10.1016/j.copbio.2019.03.001
- Choi YH and Kim JK (2019) Dissecting cellular heterogeneity using single-cell RNA sequencing. Mol Cells 42, 189-199 https://doi.org/10.14348/MOLCELLS.2019.2446
- Kester L and Oudenaarden AV (2018) Single-cell transcriptomics meets lineage tracing. Cell Stem Cell 23, 166-179 https://doi.org/10.1016/j.stem.2018.04.014
- Paik DT, Cho S, Tian L, Chang HY and Wu JC (2020) Single-cell RNA sequencing in cardiovascular development, disease and medicine. Nat Rev Cardiol [Online ahead of print]
- Eberwine J, Yeh H, Miyashiro K et al (1992) Analysis of gene expression in single live neurons. Proc Natl Acad Sci U S A 89, 3010-3014 https://doi.org/10.1073/pnas.89.7.3010
- Schaum N, Karkanias J, Neff NF et al (2018) Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562, 367-372 https://doi.org/10.1038/s41586-018-0590-4
- Islam S, Kjallquist U, Moliner A et al (2012) Highly multiplexed and strand-specific single-cell RNA 5' end sequencing. Nat Protoc 7, 813-828 https://doi.org/10.1038/nprot.2012.022
- Pollen AA, Nowakowski TJ, Shuga J et al (2014) Lowcoverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol 32, 1053-1058 https://doi.org/10.1038/nbt.2967
- Svensson V, Vento-Tormo R and Teichmann SA (2018) Teichmann, exponential scaling of single-cell RNA-seq in the past decade. Nat Protoc 13, 599-604 https://doi.org/10.1038/nprot.2017.149
- Picelli S, Bjorklund AK, Faridani OR, Sagasser S, Winberg G and Sandberg R (2013) Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10, 1096-1100 https://doi.org/10.1038/nmeth.2639
- Picelli S, Faridani OR, Bjorklund AK, Winberg G, Sagasser S and Sandberg R (2014) Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9, 171-181 https://doi.org/10.1038/nprot.2014.006
- Hashimshony T, Wagner F, Sher N and Yanai I (2012) CEL-Seq: Single-cell RNA-seq by multiplexed linear amplification. Cell Rep 2, 666-673 https://doi.org/10.1016/j.celrep.2012.08.003
- Hashimshony T, Senderovich N, Avital G et al (2016) CEL-Seq2: Sensitive highly-multiplexed single-cell RNA-Seq. Genome Biol 17, 1-7 https://doi.org/10.1186/s13059-015-0866-z
- Hochgerner H, Lonnerberg P, Hodge R et al (2017) STRTseq-2i: Dual-index 5' single cell and nucleus RNA-seq on an addressable microwell array. Sci Rep 7, 1-8 https://doi.org/10.1038/s41598-016-0028-x
- Klein AM, Mazutis L, Akartuna I et al (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187-1201 https://doi.org/10.1016/j.cell.2015.04.044
- Zhang X, Li T, Liu F et al (2019) Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-seq systems. Mol Cell 73, 130-142e135 https://doi.org/10.1016/j.molcel.2018.10.020
- Goldstein LD, Chen YJ, Dunne J et al (2017) Massively parallel nanowell-based single-cell gene expression profiling. BMC Genomics 18, 1-10 https://doi.org/10.1186/s12864-016-3406-7
- Zhang X, Li T, Liu F et al (2019) Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-seq systems. Mol Cell 73, 130-142.e135 https://doi.org/10.1016/j.molcel.2018.10.020
- Macosko EZ, Basu A, Satija R 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
- Habib N, Avraham-Davidi I, Basu A et al (2017) Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat Methods 14, 955-958 https://doi.org/10.1038/nmeth.4407
- Zheng GXY, Terry JM, Belgrader P et al (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8, 14049 https://doi.org/10.1038/ncomms14049
- Jaitin DA, Kenigsberg E, Keren-Shaul H et al (2014) Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343, 776-779 https://doi.org/10.1126/science.1247651
- Keren-Shaul H, Kenigsberg E, Jaitin DA et al (2019) MARSseq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing. Nat Protoc 14, 1841-1862 https://doi.org/10.1038/s41596-019-0164-4
- Rosenberg AB, Roco CM, Muscat RA 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
- Asp M, Bergenstrahle J and Lundeberg J (2020) Spatially resolved transcriptomes - next generation tools for tissue exploration. Bioessays e1900221 [Online ahead of print]
- Stickels RR, Murray E, Kumar P et al (2020) Sensitive spatial genome wide expression profiling at cellular resolution. bioRxiv https://doi.org/10.1101/2020.03.12.989806
- Li G, Tian L, Goodyer W et al (2019) Single cell expression analysis reveals anatomical and cell cycle-dependent transcriptional shifts during heart development. Development 146, dev173476 https://doi.org/10.1242/dev.173476
- Su T, Stanley G, Sinha R et al (2018) Single-cell analysis of early progenitor cells that build coronary arteries. Nature 559, 356-362 https://doi.org/10.1038/s41586-018-0288-7
- Hulin A, Hortells L, Gomez-Stallons MV et al (2019) Maturation of heart valve cell populations during postnatal remodeling. Development 146, dev173047 https://doi.org/10.1242/dev.173047
- Soysa TY, Ranade SS, Okawa S et al (2019) Single-cell analysis of cardiogenesis reveals basis for organ-level developmental defects. Nature 572, 120-124 https://doi.org/10.1038/s41586-019-1414-x
- Skelly DA, Squiers GT, McLellan MA et al (2018) Singlecell transcriptional profiling reveals cellular diversity and intercommunication in the mouse heart. Cell Rep 22, 600-610 https://doi.org/10.1016/j.celrep.2017.12.072
- Schafer S, Viswanathan S, Widjaja AA et al (2017) IL-11 is a crucial determinant of cardiovascular fibrosis. Nature 552, 110-115 https://doi.org/10.1038/nature24676
- See Kelvin, Tan WLW, Lim EH et al (2017) Single cardiomyocyte nuclear transcriptomes reveal a lincRNA-regulated de-differentiation and cell cycle stress-response in vivo. Nat Commun 8, 225 https://doi.org/10.1038/s41467-017-00319-8
- Nomura S, Satoh M, Fujita T et al (2018) Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure. Nat Commun 9, 4435 https://doi.org/10.1038/s41467-018-06639-7
- Gaspar I, Ephrussi A (2015) Strength in numbers: quantitative single-molecule RNA detection assays. Wiley Interdiscip Rev Dev Biol 4, 135-150 https://doi.org/10.1002/wdev.170
- Westoby J, Artemov P, Hemberg M and Ferguson-Smith A (2020) Obstacles to detecting isoforms using full-length scRNA-seq data. Genome Biol 21, 1-19 https://doi.org/10.1186/s13059-019-1906-x