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A complete bacterial genome assembled de novo using only nanopore sequencing data
Open accessAbstract
We have assembled de novo the Escherichia coli K-12 MG1655 chromosome in a single 4.6-Mb contig using only nanopore data. Our method has three stages: (i) overlaps are detected between reads and then corrected by a multiple-alignment process; (ii) corrected reads are assembled using the Celera Assembler; and (iii) the assembly is polished using a probabilistic model of the signal-level data. The assembly reconstructs gene order and has 99.5% nucleotide identity.
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Citations
Cites
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
QUAST: quality assessment tool for genome assemblies
Gurevich, A., Saveliev, V., Vyahhi, N., & Tesler, G. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt086 · Cited by 11,172
Biopython: freely available python tools for computational molecular biology and bioinformatics
Cock, P. J. A., Antao, T., Chang, J. T., Chapman, B. A., Cox, C. J., Dalke, A., Friedberg, I., Hamelryck, T., Kauff, F., Wilczynski, B., et al. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp163 · Cited by 6,080
progressiveMauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement
Darling, A. E., Mau, B., & Perna, N. T. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011147 · Cited by 3,848
Cited by
Mash: fast genome and metagenome distance estimation using MinHash
Ondov, B. D., Treangen, T. J., Melsted, P., Mallonee, A. B., Bergman, N. H., Koren, S., & Phillippy, A. M. (2016) · Genome biology · doi:10.1186/s13059-016-0997-x · Cited by 3,373
Performance of neural network basecalling tools for Oxford Nanopore sequencing
Wick, R. R., Judd, L. M., & Holt, K. E. (2019) · Genome Biology · doi:10.1186/s13059-019-1727-y · Cited by 3,221
Shotgun metagenomics, from sampling to analysis
Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J., & Segata, N. (2017) · Nature Biotechnology · doi:10.1038/nbt.3935 · Cited by 2,202
Self-citationNanopore sequencing and assembly of a human genome with ultra-long reads
Jain, M., Koren, S., Miga, K. H., Quick, J., Rand, A. C., Sasani, T. A., Tyson, J. R., Beggs, A. D., Dilthey, A. T., Fiddes, I. T., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4060 · Cited by 1,892
Self-citationThe Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community
Jain, M., Olsen, H. E., Paten, B., & Akeson, M. (2016) · Genome Biology · doi:10.1186/s13059-016-1103-0 · Cited by 1,588
The sequence of sequencers: The history of sequencing DNA
Heather, J. M., & Chain, B. (2016) · Genomics · doi:10.1016/j.ygeno.2015.11.003 · Cited by 1,397
“Already MinIONs have been used on their own to generate bacterial genome reference sequences [93, 94] and targeted amplicons [95,96], or used to generate a scaffold to map Illumina reads to [97,98,96], combining the ultra long read length of the nanopore technology and the high read depth and…”
MethodThree decades of nanopore sequencing
Deamer, D., Akeson, M., & Branton, D. (2016) · Nature Biotechnology · doi:10.1038/nbt.3423 · Cited by 1,292
The Third Revolution in Sequencing Technology
van Dijk, E. L., Jaszczyszyn, Y., Naquin, D., & Thermes, C. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.05.008 · Cited by 1,057
Telomere-to-telomere assembly of a complete human X chromosome
Miga, K. H., Koren, S., Rhie, A., Vollger, M. R., Gershman, A., Bzikadze, A., Brooks, S., Howe, E., Porubsky, D., Logsdon, G. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2547-7 · Cited by 765
Self-citationPiercing the dark matter: bioinformatics of long-range sequencing and mapping
Sedlazeck, F. J., Lee, H., Darby, C. A., & Schatz, M. C. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0003-4 · Cited by 530
Current challenges and best-practice protocols for microbiome analysis
Bharti, R., & Grimm, D. G. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbz155 · Cited by 592
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
Greninger, A. L., Naccache, S. N., Federman, S., Yu, G., Mbala, P., Bres, V., Stryke, D., Bouquet, J., Somasekar, S., Linnen, J. M., et al. (2015) · Genome Medicine · doi:10.1186/s13073-015-0220-9 · Cited by 558
Mapping DNA methylation with high-throughput nanopore sequencing
Rand, A. C., Jain, M., Eizenga, J. M., Musselman-Brown, A., Olsen, H. E., Akeson, M., & Paten, B. (2017) · Nature Methods · doi:10.1038/nmeth.4189 · Cited by 507
Real-time selective sequencing using nanopore technology
Loose, M., Malla, S., & Stout, M. (2016) · Nature Methods · doi:10.1038/nmeth.3930 · Cited by 399
Segmental duplications and their variation in a complete human genome
Vollger, M. R., Guitart, X., Dishuck, P. C., Mercuri, L., Harvey, W. T., Gershman, A., Diekhans, M., Sulovari, A., Munson, K. M., Lewis, A. P., et al. (2022) · Science · doi:10.1126/science.abj6965 · Cited by 350
Tyler, A. D., Mataseje, L., Urfano, C. J., Schmidt, L., Antonation, K. S., Mulvey, M. R., & Corbett, C. R. (2018) · Scientific Reports · doi:10.1038/s41598-018-29334-5 · Cited by 294
Singh, M., Al-Eryani, G., Carswell, S., Ferguson, J. M., Blackburn, J., Barton, K., Roden, D., Luciani, F., Giang Phan, T., Junankar, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11049-4 · Cited by 308
Paternally inherited cis-regulatory structural variants are associated with autism
Brandler, W. M., Antaki, D., Gujral, M., Kleiber, M. L., Whitney, J., Maile, M. S., Hong, O., Chapman, T. R., Tan, S., Tandon, P., et al. (2018) · Science · doi:10.1126/science.aan2261 · Cited by 209
Transposable element detection from whole genome sequence data
Ewing, A. D. (2015) · Mobile DNA · doi:10.1186/s13100-015-0055-3 · Cited by 155
A comprehensive evaluation of long read error correction methods
Zhang, H., Jain, C., & Aluru, S. (2020) · BMC Genomics · doi:10.1186/s12864-020-07227-0 · Cited by 150
Technology dictates algorithms: recent developments in read alignment
Alser, M., Rotman, J., Deshpande, D., Taraszka, K., Shi, H., Baykal, P. I., Yang, H. T., Xue, V., Knyazev, S., Singer, B. D., et al. (2021) · Genome Biology · doi:10.1186/s13059-021-02443-7 · Cited by 144
A survey of k-mer methods and applications in bioinformatics
Moeckel, C., Mareboina, M., Konnaris, M. A., Chan, C. S. Y., Mouratidis, I., Montgomery, A., Chantzi, N., Pavlopoulos, G. A., & Georgakopoulos-Soares, I. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.05.025 · Cited by 131
“One caveat of these methods is that they suffer from significantly higher error rates, necessitating novel methods of error correction [94 – 96].”
MethodProfiling bacterial communities by MinION sequencing of ribosomal operons
Kerkhof, L. J., Dillon, K. P., Häggblom, M. M., & McGuinness, L. R. (2017) · Microbiome · doi:10.1186/s40168-017-0336-9 · Cited by 115
From Omics to Multi-Omics: A Review of Advantages and Tradeoffs
Hayes, C. N., Nakahara, H., Ono, A., Tsuge, M., & Oka, S. (2024) · Genes · doi:10.3390/genes15121551 · Cited by 119
Advances in genomics for adapting crops to climate change
Scheben, A., Yuan, Y., & Edwards, D. (2016) · Current Plant Biology · doi:10.1016/j.cpb.2016.09.001 · Cited by 117
High Throughput Sequencing for Detection of Foodborne Pathogens
Sekse, C., Holst-Jensen, A., Dobrindt, U., Johannessen, G. S., Li, W., Spilsberg, B., & Shi, J. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02029 · Cited by 98
Schmid, M., Frei, D., Patrignani, A., Schlapbach, R., Frey, J. E., Remus-Emsermann, M. N. P., & Ahrens, C. H. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky726 · Cited by 92
Next-Generation Sequencing: Advantages, Disadvantages, and Future
Ari, Ş., & Arikan, M. (2016) · Plant Omics: Trends and Applications · doi:10.1007/978-3-319-31703-8_5 · Cited by 84
QuipuNet: Convolutional Neural Network for Single-Molecule Nanopore Sensing
Misiunas, K., Ermann, N., & Keyser, U. F. (2018) · Nano Letters · doi:10.1021/acs.nanolett.8b01709 · Cited by 82
A Unique Clade of SARS-CoV-2 Viruses is Associated with Lower Viral Loads in Patient Upper Airways
Lorenzo-Redondo, R., Nam, H. H., Roberts, S. C., Simons, L. M., Jennings, L. J., Qi, C., Achenbach, C. J., Hauser, A. R., Ison, M. G., Hultquist, J. F., et al. (2020) · doi:10.1101/2020.05.19.20107144 · Cited by 111
A Reference Genome Assembly of Simmental Cattle, Bos taurus taurus
Heaton, M. P., Smith, T. P. L., Bickhart, D. M., Vander Ley, B. L., Kuehn, L. A., Oppenheimer, J., Shafer, W. R., Schuetze, F. T., Stroud, B., McClure, J. C., et al. (2021) · Journal of Heredity · doi:10.1093/jhered/esab002 · Cited by 52
Metadata
- Authors
- Loman, N. J., Quick, J., & Simpson, J. T.
- Venue
- Nature Methods
- Published
- 2015-06-15
- Volume
- 12
- Issue
- 8
- Pages
- 733-735
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W1519765314
- Cited by
- 1,294
- References
- 4
- FWCI
- 36.54
- Type
- journal article
- Language
- en
- Open access
- green
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