The DOI matches its Crossref record.
Rapid Amplification of Plasmid and Phage DNA Using Phi29 DNA Polymerase and Multiply-Primed Rolling Circle Amplification
Open accessAbstract
We describe a simple method of using rolling circle amplification to amplify vector DNA such as M13 or plasmid DNA from single colonies or plaques. Using random primers and φ29 DNA polymerase, circular DNA templates can be amplified 10,000-fold in a few hours. This procedure removes the need for lengthy growth periods and traditional DNA isolation methods. Reaction products can be used directly for DNA sequencing after phosphatase treatment to inactivate unincorporated nucleotides. Amplified products can also be used for in vitro cloning, library construction, and other molecular biology applications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Real-Time DNA Sequencing from Single Polymerase Molecules
Eid, J., Fehr, A., Gray, J., Luong, K., Lyle, J., Otto, G., Peluso, P., Rank, D., Baybayan, P., Bettman, B., et al. (2009) · Science · doi:10.1126/science.1162986 · Cited by 3,732
Milani, C., Duranti, S., Bottacini, F., Casey, E., Turroni, F., Mahony, J., Belzer, C., Delgado Palacio, S., Arboleya Montes, S., Mancabelli, L., et al. (2017) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.00036-17 · Cited by 1,950
Comprehensive human genome amplification using multiple displacement amplification
Dean, F. B., Hosono, S., Fang, L., Wu, X., Faruqi, A. F., Bray-Ward, P., Sun, Z., Zong, Q., Du, Y., Du, J., et al. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082089499 · Cited by 1,467
Self-citationSingle-cell genome sequencing: current state of the science
Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334
Genome-Wide Detection of Single-Nucleotide and Copy-Number Variations of a Single Human Cell
Zong, C., Lu, S., Chapman, A. R., & Xie, X. S. (2012) · Science · doi:10.1126/science.1229164 · Cited by 1,154
The human microbiome: Our second genome
Grice, E. A., & Segre, J. A. (2012) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-090711-163814 · Cited by 759
Aging and neurodegeneration are associated with increased mutations in single human neurons
Lodato, M. A., Rodin, R. E., Bohrson, C. L., Coulter, M. E., Barton, A. R., Kwon, M., Sherman, M. A., Vitzthum, C. M., Luquette, L. J., Yandava, C. N., et al. (2018) · Science · doi:10.1126/science.aao4426 · Cited by 635
Somatic mutation in single human neurons tracks developmental and transcriptional history
Lodato, M. A., Woodworth, M. B., Lee, S., Evrony, G. D., Mehta, B. K., Karger, A., Lee, S., Chittenden, T. W., D’Gama, A. M., Cai, X., et al. (2015) · Science · doi:10.1126/science.aab1785 · Cited by 570
Single-cell analysis tools for drug discovery and development
Heath, J. R., Ribas, A., & Mischel, P. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2015.16 · Cited by 473
Advancement of the emerging field of RNA nanotechnology
Jasinski, D., Haque, F., Binzel, D. W., & Guo, P. (2017) · ACS Nano · doi:10.1021/acsnano.6b05737 · Cited by 352
High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome
Zheng, W., Zhao, S., Yin, Y., Zhang, H., Needham, D. M., Evans, E. D., Dai, C. L., Lu, P. J., Alm, E. J., & Weitz, D. A. (2022) · Science · doi:10.1126/science.abm1483 · Cited by 283
Mobile genes in the human microbiome are structured from global to individual scales
Brito, I. L., Yilmaz, S., Huang, K., Xu, L., Jupiter, S. D., Jenkins, A. P., Naisilisili, W., Tamminen, M., Smillie, C. S., Wortman, J. R., et al. (2016) · Nature · doi:10.1038/nature18927 · Cited by 288
“Genomes were then amplified using Multiple Displacement Amplification 31 for 16 hours at 30ºC using high-purity Φ 29 polymerase expressed in Escherichia coli strain BL21_DE3.”
Siegl, A., Kamke, J., Hochmuth, T., Piel, J., Richter, M., Liang, C., Dandekar, T., & Hentschel, U. (2011) · The ISME Journal · doi:10.1038/ismej.2010.95 · Cited by 276
Somatic genomic changes in single Alzheimer’s disease neurons
Miller, M. B., Huang, A. Y., Kim, J., Zhou, Z., Kirkham, S. L., Maury, E. A., Ziegenfuss, J. S., Reed, H. C., Neil, J. E., Rento, L., et al. (2022) · Nature · doi:10.1038/s41586-022-04640-1 · Cited by 223
Comparison of microbial DNA enrichment tools for metagenomic whole genome sequencing
Thoendel, M., Jeraldo, P. R., Greenwood-Quaintance, K. E., Yao, J. Z., Chia, N., Hanssen, A. D., Abdel, M. P., & Patel, R. (2016) · Journal of Microbiological Methods · doi:10.1016/j.mimet.2016.05.022 · Cited by 150
Recent advances in single-cell sequencing technologies
Wen, L., & Tang, F. (2022) · Precision Clinical Medicine · doi:10.1093/pcmedi/pbac002 · Cited by 127
Hommelsheim, C. M., Frantzeskakis, L., Huang, M., & Ülker, B. (2014) · Scientific Reports · doi:10.1038/srep05052 · Cited by 121
Advancements toward a systems level understanding of the human oral microbiome
McLean, J. S. (2014) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2014.00098 · Cited by 108
Lodato, M. A., & Walsh, C. A. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz191 · Cited by 56
Volozonoka, L., Miskova, A., & Gailite, L. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23094819 · Cited by 52
Analyzing somatic mutations by single-cell whole-genome sequencing
Zhang, L., Lee, M., Maslov, A. Y., Montagna, C., Vijg, J., & Dong, X. (2024) · Nature Protocols · doi:10.1038/s41596-023-00914-8 · Cited by 26
Zhu, Q., Niu, Y., Gundry, M., & Zong, C. (2021) · Science Advances · doi:10.1126/sciadv.abf3329 · Cited by 18
Metadata
- Authors
- Dean, F. B., Nelson, J. R., Giesler, T. L., & Lasken, R. S.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2001-06-01
- Volume
- 11
- Issue
- 6
- Pages
- 1095-1099
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- OpenAlex
- W1968762427
- Cited by
- 1,067
- References
- 0
- Type
- posted content
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
