Real-Time DNA Sequencing from Single Polymerase Molecules
Abstract
We present single-molecule, real-time sequencing data obtained from a DNA polymerase performing uninterrupted template-directed synthesis using four distinguishable fluorescently labeled deoxyribonucleoside triphosphates (dNTPs). We detected the temporal order of their enzymatic incorporation into a growing DNA strand with zero-mode waveguide nanostructure arrays, which provide optical observation volume confinement and enable parallel, simultaneous detection of thousands of single-molecule sequencing reactions. Conjugation of fluorophores to the terminal phosphate moiety of the dNTPs allows continuous observation of DNA synthesis over thousands of bases without steric hindrance. The data report directly on polymerase dynamics, revealing distinct polymerization states and pause sites corresponding to DNA secondary structure. Sequence data were aligned with the known reference sequence to assay biophysical parameters of polymerization for each template position. Consensus sequences were generated from the single-molecule reads at 15-fold coverage, showing a median accuracy of 99.3%, with no systematic error beyond fluorophore-dependent error rates.
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The multiplicity of stationary states at a single-molecule level is supported by a recent demonstration of real-time sequencing-by-polymerization, where polymerases interconverted between two distinct velocities during DNA elongation for a given reaction condition.
“The multiplicity of stationary states at a single-molecule level is supported by the recent demonstration of a real-time sequencing-by-polymerization technique [55], where it was reported that polymerases interconverted between two distinct velocities during DNA elongation for a given reaction condition (Figures 3C and S3 of Ref. [55]).”
From Thermodynamic Basis for the Emergence of Genomes during Prebiotic Evolution (2012) · cites this paper as [55]
New genome assemblies have been arriving at a rapidly increasing pace, due to decreases in sequencing costs and improvements in third-generation sequencing technologies.
“New genome assemblies have been arriving at a rapidly increasing pace, thanks to decreases in sequencing costs and improvements in third-generation sequencing technologies1–3.”
From Progressive Cactus is a multiple-genome aligner for the thousand-genome era (2020) · cites this paper as [1]
Cites
Stem cell transcriptome profiling via massive-scale mRNA sequencing
Cloonan, N., Forrest, A. R. R., Kolle, G., Gardiner, B. B. A., Faulkner, G. J., Brown, M. K., Taylor, D. F., Steptoe, A. L., Wani, S., Bethel, G., et al. (2008) · Nature Methods · doi:10.1038/nmeth.1223 · Cited by 1,035 · cited 1× · see citing works
“Next-generation DNA sequencing methods have changed whole-genome sequencing projects into routine procedures (reviewed in Mardis, 2008) and have been adapted to other areas, such as transcriptome sequencing and epigenetics (Cloonan et al., 2008; Cokus et al., 2008; Fullwood et al., 2009; Maher et al., 2009; Yassour et…”
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Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M., & Glöckner, F. O. (2013) · Nucleic Acids Research · doi:10.1093/nar/gks808 · Cited by 8,850 · see citing works
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066 · see citing works
Coming of age: ten years of next-generation sequencing technologies
Goodwin, S., McPherson, J. D., & McCombie, W. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.49 · Cited by 4,352 · see citing works
Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies
Rhie, A., Walenz, B. P., Koren, S., & Phillippy, A. M. (2020) · Genome Biology · doi:10.1186/s13059-020-02134-9 · Cited by 3,643 · see citing works
The complete sequence of a human genome
Nurk, S., Koren, S., Rhie, A., Rautiainen, M., Bzikadze, A. V., Mikheenko, A., Vollger, M. R., Altemose, N., Uralsky, L., Gershman, A., et al. (2022) · Science · doi:10.1126/science.abj6987 · Cited by 3,136 · see citing works
Self-citationAdeno-associated virus vector as a platform for gene therapy delivery
Wang, D., Tai, P. W. L., & Gao, G. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0012-9 · Cited by 2,444 · see citing works
RNA sequencing: advances, challenges and opportunities
Ozsolak, F., & Milos, P. M. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2934 · Cited by 2,135 · see citing works
Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031 · see citing works
Wenger, A. M., Peluso, P., Rowell, W. J., Chang, P.-C., Hall, R. J., Concepcion, G. T., Ebler, J., Fungtammasan, A., Kolesnikov, A., Olson, N. D., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0217-9 · Cited by 1,841 · see citing works
Self-citationDirect detection of DNA methylation during single-molecule, real-time sequencing
Flusberg, B. A., Webster, D. R., Lee, J. H., Travers, K. J., Olivares, E. C., Clark, T. A., Korlach, J., & Turner, S. W. (2010) · Nature Methods · doi:10.1038/nmeth.1459 · Cited by 1,460 · see citing works
The sequence of sequencers: The history of sequencing DNA
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Next-Generation Sequencing Technology: Current Trends and Advancements
Satam, H., Joshi, K., Mangrolia, U., Waghoo, S., Zaidi, G., Rawool, S., Thakare, R. P., Banday, S., Mishra, A. K., Das, G., et al. (2023) · Biology · doi:10.3390/biology12070997 · Cited by 1,299 · see citing works
Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
Aird, D., Ross, M. G., Chen, W.-S., Danielsson, M., Fennell, T., Russ, C., Jaffe, D. B., Nusbaum, C., & Gnirke, A. (2011) · Genome Biology · doi:10.1186/gb-2011-12-2-r18 · Cited by 1,174 · see citing works
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177 · see citing works
Characterizing and measuring bias in sequence data
Ross, M. G., Russ, C., Costello, M., Hollinger, A., Lennon, N. J., Hegarty, R., Nusbaum, C., & Jaffe, D. B. (2013) · Genome Biology · doi:10.1186/gb-2013-14-5-r51 · Cited by 909 · see citing works
Kukurba, K. R., & Montgomery, S. B. (2015) · Cold Spring Harbor Protocols · doi:10.1101/pdb.top084970 · Cited by 924 · see citing works
Sequencing technologies and genome sequencing
Pareek, C. S., Smoczynski, R., & Tretyn, A. (2011) · Journal of Applied Genetics · doi:10.1007/s13353-011-0057-x · Cited by 868 · see citing works
REBASE--a database for DNA restriction and modification: enzymes, genes and genomes.
Roberts, R. J., Vincze, T., Posfai, J., & Macelis, D. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1046 · Cited by 728 · see citing works
A single-molecule long-read survey of the human transcriptome
Sharon, D., Tilgner, H., Grubert, F., & Snyder, M. (2013) · Nature Biotechnology · doi:10.1038/nbt.2705 · Cited by 701 · see citing works
Computational solutions to large‐scale data management and analysis
Schadt, E. E., Linderman, M. D., Sorenson, J., Lee, L., & Nolan, G. P. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2857 · Cited by 631 · see citing works
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Armstrong, J., Hickey, G., Diekhans, M., Fiddes, I. T., Novak, A. M., Deran, A., Fang, Q., Xie, D., Feng, S., Stiller, J., et al. (2020) · Nature · doi:10.1038/s41586-020-2871-y · Cited by 586 · see citing works
Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes
Shafin, K., Pesout, T., Lorig-Roach, R., Haukness, M., Olsen, H. E., Bosworth, C., Armstrong, J., Tigyi, K., Maurer, N., Koren, S., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0503-6 · Cited by 567 · see citing works
Nagarajan, N., & Pop, M. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3367 · Cited by 474 · see citing works
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Adir, O., Poley, M., Chen, G., Froim, S., Krinsky, N., Shklover, J., Shainsky‐Roitman, J., Lammers, T., & Schroeder, A. (2020) · Advanced Materials · doi:10.1002/adma.201901989 · Cited by 496 · see citing works
Annotating non-coding regions of the genome.
Alexander, R. P., Fang, G., Rozowsky, J., Snyder, M., & Gerstein, M. B. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2814 · Cited by 464 · see citing works
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Fan, H. C., Fu, G. K., & Fodor, S. P. A. (2015) · Science · doi:10.1126/science.1258367 · Cited by 455 · see citing works
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Zepeda-Rivera, M., Minot, S. S., Bouzek, H., Wu, H., Blanco-Míguez, A., Manghi, P., Jones, D. S., LaCourse, K. D., Wu, Y., McMahon, E. F., et al. (2024) · Nature · doi:10.1038/s41586-024-07182-w · Cited by 451 · see citing works
Goriely, A., & Wilkie, A. O. M. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.12.017 · Cited by 365 · see citing works
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Treutlein, B., Gokce, O., Quake, S. R., & Südhof, T. C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403244111 · Cited by 348 · see citing works
Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells
Gupta, I., Collier, P. G., Haase, B., Mahfouz, A., Joglekar, A., Floyd, T., Koopmans, F., Barres, B., Smit, A. B., Sloan, S. A., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4259 · Cited by 343 · see citing works
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Laszlo, A. H., Derrington, I. M., Brinkerhoff, H., Langford, K. W., Nova, I. C., Samson, J. M., Bartlett, J. J., Pavlenok, M., & Gundlach, J. H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1310240110 · Cited by 321 · see citing works
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Clark, S. J., Lee, H. J., Smallwood, S. A., Kelsey, G., & Reik, W. (2016) · Genome Biology · doi:10.1186/s13059-016-0944-x · Cited by 310 · see citing works
Self-citationDefining a personal, allele-specific, and single-molecule long-read transcriptome
Tilgner, H., Grubert, F., Sharon, D., & Snyder, M. P. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400447111 · Cited by 266 · see citing works
Tilgner, H., Jahanbani, F., Blauwkamp, T., Moshrefi, A., Jaeger, E., Chen, F., Harel, I., Bustamante, C. D., Rasmussen, M., & Snyder, M. P. (2015) · Nature Biotechnology · doi:10.1038/nbt.3242 · Cited by 223 · see citing works
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Lee, M.-H., Siddoway, B., Kaeser, G. E., Segota, I., Rivera, R., Romanow, W. J., Liu, C. S., Park, C., Kennedy, G., Long, T., et al. (2018) · Nature · doi:10.1038/s41586-018-0718-6 · Cited by 210 · see citing works
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Paszkiewicz, K., & Studholme, D. J. (2010) · Briefings in Bioinformatics · doi:10.1093/bib/bbq020 · Cited by 204 · see citing works
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Nicolae, M., Mangul, S., Măndoiu, I. I., & Zelikovsky, A. (2011) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-6-9 · Cited by 178 · see citing works
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Greninger, A. L., Chen, E. C., Sittler, T., Scheinerman, A., Roubinian, N., Yu, G., Kim, E., Pillai, D. R., Guyard, C., Mazzulli, T., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013381 · Cited by 193 · see citing works
Impact of next generation sequencing techniques in food microbiology.
Mayo, B., Rachid, C., Alegria, A., Leite, A., Peixoto, R., & Delgado, S. (2014) · Current Genomics · doi:10.2174/1389202915666140616233211 · Cited by 188 · see citing works
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Barski, A., & Zhao, K. (2009) · Journal of Cellular Biochemistry · doi:10.1002/jcb.22077 · Cited by 169 · see citing works
Maguire, F., Jia, B., Gray, K. L., Lau, W. Y. V., Beiko, R. G., & Brinkman, F. S. L. (2020) · Microbial Genomics · doi:10.1099/mgen.0.000436 · Cited by 152 · see citing works
Łabaj, P. P., Leparc, G. G., Linggi, B. E., Markillie, L. M., Wiley, H. S., & Kreil, D. P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr247 · Cited by 141 · see citing works
Microalgae with Artificial Intelligence: A Digitalized Perspective on Genetics, Systems and Products
Teng, S. Y., Yew, G. Y., Sukačová, K., Show, P. L., Máša, V., & Chang, J.-S. (2020) · Biotechnology Advances · doi:10.1016/j.biotechadv.2020.107631 · Cited by 145 · see citing works
Brown, S. D., Nagaraju, S., Utturkar, S., De Tissera, S., Segovia, S., Mitchell, W., Land, M. L., Dassanayake, A., & Köpke, M. (2014) · Biotechnology for Biofuels · doi:10.1186/1754-6834-7-40 · Cited by 145 · see citing works
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Hardwick, S. A., Hu, W., Joglekar, A., Fan, L., Collier, P. G., Foord, C., Balacco, J., Lanjewar, S., Sampson, M. M., Koopmans, F., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01231-3 · Cited by 119 · see citing works
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Xie, J., Mao, Q., Tai, P. W. L., He, R., Ai, J., Su, Q., Zhu, Y., Ma, H., Li, J., Gong, S., et al. (2017) · Molecular Therapy · doi:10.1016/j.ymthe.2017.03.028 · Cited by 102 · see citing works
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Rupp, O., MacDonald, M. L., Li, S., Dhiman, H., Polson, S., Griep, S., Heffner, K., Hernandez, I., Brinkrolf, K., Jadhav, V., et al. (2018) · Biotechnology and Bioengineering · doi:10.1002/bit.26722 · Cited by 107 · see citing works
Tai, P. W. L., Xie, J., Fong, K., Seetin, M., Heiner, C., Su, Q., Weiand, M., Wilmot, D., Zapp, M. L., & Gao, G. (2018) · Molecular Therapy - Methods & Clinical Development · doi:10.1016/j.omtm.2018.02.002 · Cited by 102 · see citing works
Self-citationChin, E. L., da Silva, C., & Hegde, M. (2013) · BMC Genetics · doi:10.1186/1471-2156-14-6 · Cited by 92 · see citing works
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Tilgner, H., Jahanbani, F., Gupta, I., Collier, P., Wei, E., Rasmussen, M., & Snyder, M. (2018) · Genome Research · doi:10.1101/gr.230516.117 · Cited by 71 · see citing works
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Kruk, S. S., Decker, M., Staude, I., Schlecht, S., Greppmair, M., Neshev, D. N., & Kivshar, Y. S. (2014) · ACS Photonics · doi:10.1021/ph500288u · Cited by 83 · see citing works
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Karlsson, K., & Linnarsson, S. (2017) · BMC Genomics · doi:10.1186/s12864-017-3528-6 · Cited by 76 · see citing works
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Kervio, E., Hochgesand, A., Steiner, U. E., & Richert, C. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914872107 · Cited by 62 · see citing works
Hsu, H.-L., Brown, A., Loveland, A. B., Lotun, A., Xu, M., Luo, L., Xu, G., Li, J., Ren, L., Su, Q., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17047-1 · Cited by 63 · see citing works
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Liu, J., Li, Q., Hu, Y., Yu, Y., Zheng, K., Li, D., Qin, L., & Yu, X. (2024) · Science · doi:10.1126/science.adq8191 · Cited by 57 · see citing works
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Nam, J. H., Cho, Y. S., Rackerby, B., Goddik, L., & Park, S. H. (2021) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-021-11201-5 · Cited by 53 · see citing works
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Puri, P., & Sanyal, A. J. (2018) · Clinics in Liver Disease · doi:10.1016/j.cld.2017.08.009 · Cited by 33 · see citing works
Thermodynamic Basis for the Emergence of Genomes during Prebiotic Evolution
Woo, H.-J., Vijaya Satya, R., & Reifman, J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002534 · Cited by 6 · see citing works
- Authors
- Eid, J., Fehr, A., Gray, J., Luong, K., Lyle, J., Otto, G., Peluso, P., Rank, D., Baybayan, P., Bettman, B., Bibillo, A., Bjornson, K., Chaudhuri, B., Christians, F., Cicero, R., Clark, S., Dalal, R., deWinter, A., Dixon, J., Foquet, M., Gaertner, A., Hardenbol, P., Heiner, C., Hester, K., Holden, D., Kearns, G., Kong, X., Kuse, R., Lacroix, Y., Lin, S., Lundquist, P., Ma, C., Marks, P., Maxham, M., Murphy, D., Park, I., Pham, T., Phillips, M., Roy, J., Sebra, R., Shen, G., Sorenson, J., Tomaney, A., Travers, K., Trulson, M., Vieceli, J., Wegener, J., Wu, D., Yang, A., Zaccarin, D., Zhao, P., Zhong, F., Korlach, J., & Turner, S.
- Affiliations
- Pacific Biosciences (United States) (US)
- Pacific Biosciences, 1505 Adams Drive, Menlo Park, CA 94025, USA.
- Corresponding author
- Eid, John
- Fehr, Adrian
- Gray, Jeremy
- Luong, Khai
- Lyle, John
- Otto, Geoff
- Peluso, Paul
- Rank, David
- Korlach, Jonas
- Turner, Stephen
- ORCID
- Venue
- Science
- Published
- 2009-01-02
- Volume
- 323
- Issue
- 5910
- Pages
- 133-138
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2132341951
- Cited by
- 3,732
- References
- 1
- Citations by year
- 2026: 127 · 2025: 167 · 2024: 227 · 2023: 183 · 2022: 231 · 2021: 261 · 2020: 228 · 2019: 248 · 2018: 240 · 2017: 269 · 2016: 270 · 2015: 260 · 2014: 199 · 2013: 204 · 2012: 184
- FWCI
- 58.76
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Human Genome Research Institute (R01HG003710)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Nucleic Acid Chemistry
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Keywords
- single-molecule DNA sequencing, DNA polymerase, real-time sequencing, zero-mode waveguides, DNA secondary structure, polymerization dynamics, consensus sequence, fluorescent labeling, template synthesis
- MeSH terms
- Base Sequence, Deoxyribonucleotides, DNA, DNA-Directed DNA Polymerase, DNA, Circular, DNA, Single-Stranded, Enzymes, Immobilized, Fluorescent Dyes, Kinetics, Spectrometry, Fluorescence, Consensus Sequence, Sequence Analysis, DNA, Nanostructures
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