Next-generation DNA sequencing
Abstract
DNA sequence represents a single format onto which a broad range of biological phenomena can be projected for high-throughput data collection. Over the past three years, massively parallel DNA sequencing platforms have become widely available, reducing the cost of DNA sequencing by over two orders of magnitude, and democratizing the field by putting the sequencing capacity of a major genome center in the hands of individual investigators. These new technologies are rapidly evolving, and near-term challenges include the development of robust protocols for generating sequencing libraries, building effective new approaches to data-analysis, and often a rethinking of experimental design. Next-generation DNA sequencing has the potential to dramatically accelerate biological and biomedical research, by enabling the comprehensive analysis of genomes, transcriptomes and interactomes to become inexpensive, routine and widespread, rather than requiring significant production-scale efforts.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Short-read-only assemblies often struggle with repetitive and intergenic regions, resulting in fragmented assembly and poor access to regulatory and promoter sequences.
“However, short-read-only assemblies often struggle with repetitive and intergenic regions, resulting in fragmented assembly and poor access to regulatory and promoter sequences5,6.”
From Hybrid genome assembly and annotation of Danionella translucida (2019) · cites this paper as [5]
Cites
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696 · see citing works
Base-Calling of Automated Sequencer Traces Using <i>Phred.</i> II. Error Probabilities
Ewing, B., & Green, P. (1998) · Genome Research · doi:10.1101/gr.8.3.186 · Cited by 5,439 · see citing works
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 · see citing works
Direct selection of human genomic loci by microarray hybridization
Albert, T. J., Molla, M. N., Muzny, D. M., Nazareth, L., Wheeler, D., Song, X., Richmond, T. A., Middle, C. M., Rodesch, M. J., Packard, C. J., et al. (2007) · Nature Methods · doi:10.1038/nmeth1111 · Cited by 681 · see citing works
Bainbridge, M. N., Warren, R. L., Hirst, M., Romanuik, T., Zeng, T., Go, A., Delaney, A., Griffith, M., Hickenbotham, M., Magrini, V., et al. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-246 · Cited by 222 · see citing works
Transcriptome sequencing of malignant pleural mesothelioma tumors
Sugarbaker, D. J., Richards, W. G., Gordon, G. J., Dong, L., De Rienzo, A., Maulik, G., Glickman, J. N., Chirieac, L. R., Hartman, M.-L., Taillon, B. E., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0712399105 · Cited by 155 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The impact of the gut microbiota on human health: an integrative view
Clemente, J. C., Ursell, L. K., Parfrey, L. W., & Knight, R. (2012) · Cell · doi:10.1016/j.cell.2012.01.035 · Cited by 3,710 · see citing works
Towards next-generation biodiversity assessment using DNA metabarcoding
TABERLET, P., COISSAC, E., POMPANON, F., BROCHMANN, C., & WILLERSLEV, E. (2012) · Molecular Ecology · doi:10.1111/j.1365-294x.2012.05470.x · Cited by 1,907 · see citing works
Targeted capture and massively parallel sequencing of 12 human exomes
Ng, S. B., Turner, E. H., Robertson, P. D., Flygare, S. D., Bigham, A. W., Lee, C., Shaffer, T., Wong, M., Bhattacharjee, A., Eichler, E. E., et al. (2009) · Nature · doi:10.1038/nature08250 · Cited by 2,030 · see citing works
Self-citationFrequent pathway mutations of splicing machinery in myelodysplasia
Yoshida, K., Sanada, M., Shiraishi, Y., Nowak, D., Nagata, Y., Yamamoto, R., Sato, Y., Sato-Otsubo, A., Kon, A., Nagasaki, M., et al. (2011) · Nature · doi:10.1038/nature10496 · Cited by 2,029 · see citing works
Exome sequencing identifies the cause of a mendelian disorder
Ng, S. B., Buckingham, K. J., Lee, C., Bigham, A. W., Tabor, H. K., Dent, K. M., Huff, C. D., Shannon, P. T., Jabs, E. W., Nickerson, D. A., et al. (2010) · Nature Genetics · doi:10.1038/ng.499 · Cited by 1,957 · see citing works
Self-citationThe 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 · see citing works
Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays
Drmanac, R., Sparks, A. B., Callow, M. J., Halpern, A. L., Burns, N. L., Kermani, B. G., Carnevali, P., Nazarenko, I., Nilsen, G. B., Yeung, G., et al. (2010) · Science · doi:10.1126/science.1181498 · Cited by 1,212 · see citing works
Comprehensive assessment of T-cell receptor β-chain diversity in αβ T cells
Robins, H. S., Campregher, P. V., Srivastava, S. K., Wacher, A., Turtle, C. J., Kahsai, O., Riddell, S. R., Warren, E. H., & Carlson, C. S. (2009) · Blood · doi:10.1182/blood-2009-04-217604 · Cited by 1,122 · see citing works
Detection of ultra-rare mutations by next-generation sequencing
Schmitt, M. W., Kennedy, S. R., Salk, J. J., Fox, E. J., Hiatt, J. B., & Loeb, L. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1208715109 · Cited by 1,047 · see citing works
Prebiotic Systems Chemistry: New Perspectives for the Origins of Life
Ruiz-Mirazo, K., Briones, C., & de la Escosura, A. (2014) · Chemical Reviews · doi:10.1021/cr2004844 · Cited by 930 · see citing works
The impact of next-generation sequencing on genomics
Zhang, J., Chiodini, R., Badr, A., & Zhang, G. (2011) · Journal of Genetics and Genomics · doi:10.1016/j.jgg.2011.02.003 · Cited by 577 · see citing works
“NGS technologies have increased the speed and throughput capacities of DNA sequencing and, as a result, dramatically reduced overall sequencing costs (Mardis, 2006, 2009; Schuster, 2008; Shendure and Ji, 2008; Ng et al., 2009a; Tucker et al., 2009; Metzker, 2010).”
BackgroundLaFramboise, T. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp552 · Cited by 467 · see citing works
Ercolini, D. (2013) · Applied and Environmental Microbiology · doi:10.1128/aem.00256-13 · Cited by 479 · see citing works
The genetics of attention deficit/hyperactivity disorder in adults, a review
on behalf of the International Multicentre persistent ADHD CollaboraTion (IMpACT), Franke, B., Faraone, S. V., Asherson, P., Buitelaar, J., Bau, C. H. D., Ramos-Quiroga, J. A., Mick, E., Grevet, E. H., Johansson, S., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2011.138 · Cited by 432 · see citing works
Personalized Medicine and the Power of Electronic Health Records
Abul-Husn, N. S., & Kenny, E. E. (2019) · Cell · doi:10.1016/j.cell.2019.02.039 · Cited by 355 · see citing works
Exome sequencing and the genetic basis of complex traits
Kiezun, A., Garimella, K., Do, R., Stitziel, N. O., Neale, B. M., McLaren, P. J., Gupta, N., Sklar, P., Sullivan, P. F., Moran, J. L., et al. (2012) · Nature Genetics · doi:10.1038/ng.2303 · Cited by 372 · see citing works
Interactions between Intestinal Microbiota and Host Immune Response in Inflammatory Bowel Disease
Zhang, M., Sun, K., Wu, Y., Yang, Y., Tso, P., & Wu, Z. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.00942 · Cited by 347 · see citing works
Barcoded nanoparticles for high throughput in vivo discovery of targeted therapeutics
Dahlman, J. E., Kauffman, K. J., Xing, Y., Shaw, T. E., Mir, F. F., Dlott, C. C., Langer, R., Anderson, D. G., & Wang, E. T. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620874114 · Cited by 335 · see citing works
Integrative analysis of the melanoma transcriptome
Berger, M. F., Levin, J. Z., Vijayendran, K., Sivachenko, A., Adiconis, X., Maguire, J., Johnson, L. A., Robinson, J., Verhaak, R. G., Sougnez, C., et al. (2010) · Genome Research · doi:10.1101/gr.103697.109 · Cited by 305 · see citing works
Historical perspective, development and applications of next-generation sequencing in plant virology
Barba, M., Czosnek, H., & Hadidi, A. (2014) · Viruses · doi:10.3390/v6010106 · Cited by 317 · see citing works
“For example, a variety of bioinformatics’ software tools for short-read sequencing used for de novo assembly of genomes and transcriptomes are available [91,92].”
BackgroundDetecting Liquid Remnants of Solid Tumors: Circulating Tumor DNA Minimal Residual Disease
Moding, E. J., Nabet, B. Y., Alizadeh, A. A., & Diehn, M. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0634 · Cited by 325 · see citing works
Genomics, Intellectual Disability, and Autism
Mefford, H. C., Batshaw, M. L., & Hoffman, E. P. (2012) · New England Journal of Medicine · doi:10.1056/nejmra1114194 · Cited by 329 · see citing works
The evolution of Ebola virus: Insights from the 2013-2016 epidemic
Holmes, E. C., Dudas, G., Rambaut, A., & Andersen, K. G. (2016) · Nature · doi:10.1038/nature19790 · Cited by 314 · see citing works
Fouhy, F., Clooney, A. G., Stanton, C., Claesson, M. J., & Cotter, P. D. (2016) · BMC Microbiology · doi:10.1186/s12866-016-0738-z · Cited by 310 · see citing works
Tang, S., Wang, X., Li, W., Yang, X., Li, Z., Liu, W., Li, C., Zhu, Z., Wang, L., Wang, J., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.04.012 · Cited by 304 · see citing works
- Invited Review - African Indigenous Cattle: Unique Genetic Resources in a Rapidly Changing World
Mwai, O., Hanotte, O., Kwon, Y.-J., & Cho, S. (2015) · Asian-Australasian Journal of Animal Sciences · doi:10.5713/ajas.15.0002r · Cited by 300 · see citing works
Allali, I., Arnold, J. W., Roach, J., Cadenas, M. B., Butz, N., Hassan, H. M., Koci, M., Ballou, A., Mendoza, M., Ali, R., et al. (2017) · BMC Microbiology · doi:10.1186/s12866-017-1101-8 · Cited by 298 · see citing works
Genomic views of STAT function in CD4+ T helper cell differentiation
O'Shea, J. J., Lahesmaa, R., Vahedi, G., Laurence, A., & Kanno, Y. (2011) · Nature Reviews Immunology · doi:10.1038/nri2958 · Cited by 295 · see citing works
Application of 'next-generation' sequencing technologies to microbial genetics
MacLean, D., Jones, J. D. G., & Studholme, D. J. (2009) · Nature Reviews Microbiology · doi:10.1038/nrmicro2088 · Cited by 293 · see citing works
Reddy, S. T., Ge, X., Miklos, A. E., Hughes, R. A., Kang, S. H., Hoi, K. H., Chrysostomou, C., Hunicke-Smith, S. P., Iverson, B. L., Tucker, P. W., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1673 · Cited by 292 · see citing works
Microbiome dynamics of human epidermis following skin barrier disruption
Zeeuwen, P. L., Boekhorst, J., van den Bogaard, E. H., de Koning, H. D., van de Kerkhof, P. M., Saulnier, D. M., van Swam, I. I., van Hijum, S. A., Kleerebezem, M., Schalkwijk, J., et al. (2012) · Genome Biology · doi:10.1186/gb-2012-13-11-r101 · Cited by 274 · see citing works
Tandy-Connor, S., Guiltinan, J., Krempely, K., LaDuca, H., Reineke, P., Gutierrez, S., Gray, P., & Tippin Davis, B. (2018) · Genetics in Medicine · doi:10.1038/gim.2018.38 · Cited by 273 · see citing works
Next is now: new technologies for sequencing of genomes, transcriptomes, and beyond
Lister, R., Gregory, B. D., & Ecker, J. R. (2009) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2008.11.004 · Cited by 274 · see citing works
Drilon, A., Wang, L., Arcila, M. E., Balasubramanian, S., Greenbowe, J. R., Ross, J. S., Stephens, P., Lipson, D., Miller, V. A., Kris, M. G., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-2683 · Cited by 274 · see citing works
The Gut Microbiome: A New Frontier in Autism Research
Mulle, J. G., Sharp, W. G., & Cubells, J. F. (2013) · Current Psychiatry Reports · doi:10.1007/s11920-012-0337-0 · Cited by 262 · see citing works
Zhang, W., Chen, J., Yang, Y., Tang, Y., Shang, J., & Shen, B. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017915 · Cited by 250 · see citing works
Analysis of High-Throughput Ancient DNA Sequencing Data
Kircher, M. (2012) · Methods in Molecular Biology · doi:10.1007/978-1-61779-516-9_23 · Cited by 236 · see citing works
Big data in digital healthcare: lessons learnt and recommendations for general practice
Agrawal, R., & Prabakaran, S. (2020) · Heredity · doi:10.1038/s41437-020-0303-2 · Cited by 218 · see citing works
Minty, J. J., Lesnefsky, A. A., Lin, F., Chen, Y., Zaroff, T. A., Veloso, A. B., Xie, B., McConnell, C. A., Ward, R. J., Schwartz, D. R., et al. (2011) · Microbial Cell Factories · doi:10.1186/1475-2859-10-18 · Cited by 185 · see citing works
Multifunctional sequence-defined macromolecules for chemical data storage.
Martens, S., Landuyt, A., Espeel, P., Devreese, B., Dawyndt, P., & Du Prez, F. (2018) · Nature Communications · doi:10.1038/s41467-018-06926-3 · Cited by 180 · see citing works
Oxidative stress is not a major contributor to somatic mitochondrial DNA mutations
Itsara, L. S., Kennedy, S. R., Fox, E. J., Yu, S., Hewitt, J. J., Sanchez-Contreras, M., Cardozo-Pelaez, F., & Pallanck, L. J. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1003974 · Cited by 173 · see citing works
The power of multiplexed functional analysis of genetic variants
Gasperini, M., Starita, L., & Shendure, J. (2016) · Nature Protocols · doi:10.1038/nprot.2016.135 · Cited by 160 · see citing works
Self-citationMajor Histocompatibility Complex (MHC) Markers in Conservation Biology
Ujvari, B., & Belov, K. (2011) · International Journal of Molecular Sciences · doi:10.3390/ijms12085168 · Cited by 154 · see citing works
Schären, M., Drong, C., Kiri, K., Riede, S., Gardener, M., Meyer, U., Hummel, J., Urich, T., Breves, G., & Dänicke, S. (2017) · Journal of Dairy Science · doi:10.3168/jds.2016-11994 · Cited by 149 · see citing works
Massively Parallel Sequencing for Genetic Diagnosis of Hearing Loss: The New Standard of Care
Shearer, A. E., & Smith, R. J. H. (2015) · Otolaryngology–Head and Neck Surgery · doi:10.1177/0194599815591156 · Cited by 144 · see citing works
Comparative studies of <i>de novo</i> assembly tools for next-generation sequencing technologies
Lin, Y., Li, J., Shen, H., Zhang, L., Papasian, C. J., & Deng, H. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr319 · Cited by 126 · see citing works
Detection of selective sweeps in structured populations: a comparison of recent methods
Vatsiou, A. I., Bazin, E., & Gaggiotti, O. E. (2016) · Molecular Ecology · doi:10.1111/mec.13360 · Cited by 111 · see citing works
Bone Remodeling and the Microbiome
Pacifici, R. (2018) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a031203 · Cited by 101 · see citing works
Single cell transcriptomics in neuroscience: cell classification and beyond
Tasic, B. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.04.021 · Cited by 83 · see citing works
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 · see citing works
Han, L., Zi, X., Garmire, L. X., Wu, Y., Weissman, S. M., Pan, X., & Fan, R. (2014) · Scientific Reports · doi:10.1038/srep06485 · Cited by 83 · see citing works
Analyzing Schizophrenia by DNA Microarrays
Horváth, S., Janka, Z., & Mirnics, K. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.07.017 · Cited by 64 · see citing works
Recent advances in microfluidic methods in cancer liquid biopsy
Iliescu, F. S., Poenar, D. P., Yu, F., Ni, M., Chan, K. H., Cima, I., Taylor, H. K., Cima, I., & Iliescu, C. (2019) · Biomicrofluidics · doi:10.1063/1.5087690 · Cited by 51 · see citing works
Hu, H., Wrogemann, K., Kalscheuer, V., Tzschach, A., Richard, H., Haas, S. A., Menzel, C., Bienek, M., Froyen, G., Raynaud, M., et al. (2009) · The HUGO Journal · doi:10.1007/s11568-010-9137-y · Cited by 49 · see citing works
Hause, R. J., Stark, A. L., Antao, N. N., Gorsic, L. K., Chung, S. H., Brown, C. D., Wong, S. S., Gill, D. F., Myers, J. L., To, L. A., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.07.005 · Cited by 43 · see citing works
Yang, H., Hu, L., Hurek, T., & Reinhold-Hurek, B. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-705 · Cited by 42 · see citing works
The mouth, the anus, and the blastopore—open questions about questionable openings
Hejnol, A., & Martindale, M. Q. (2009) · Animal Evolution · doi:10.1093/acprof:oso/9780199549429.003.0004 · Cited by 37 · see citing works
A Ubiquitous Machine Learning Accelerator with Automatic Parallelization on FPGA
Wang, C., Gong, L., Li, X., & Zhou, X. (2020) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2020.2990924 · Cited by 37 · see citing works
Genome-wide DNA methylation in suicide victims revealing impact on gene expression
Kouter, K., Zupanc, T., & Videtič Paska, A. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.04.077 · Cited by 36 · see citing works
Hybrid genome assembly and annotation of Danionella translucida
Kadobianskyi, M., Schulze, L., Schuelke, M., & Judkewitz, B. (2019) · Scientific Data · doi:10.1038/s41597-019-0161-z · Cited by 36 · see citing works
Genomic, phylogenetic, and cell biological insights into metazoan origins
Nichols, S. A., Dayel, M. J., & King, N. (2009) · Animal Evolution · doi:10.1093/acprof:oso/9780199549429.003.0003 · Cited by 24 · see citing works
Rebimbas, R., Glória, I., Chegão, J., Al-Rawi, M., Mousakhani Ganjeh, A., & Saraiva, J. A. (2026) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2026.03.003
- Authors
- Shendure, J., & Ji, H.
- Affiliations
- University of Washington (US)
- Stanford Medicine (US)
- Corresponding author
- Shendure, Jay
- Ji, Hanlee
- Venue
- Nature Biotechnology
- Published
- 2008-10
- Volume
- 26
- Issue
- 10
- Pages
- 1135-1145
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2061680337
- Cited by
- 4,509
- References
- 6
- Citations by year
- 2026: 71 · 2025: 146 · 2024: 176 · 2023: 133 · 2022: 159 · 2021: 180 · 2020: 203 · 2019: 188 · 2018: 270 · 2017: 284 · 2016: 302 · 2015: 330 · 2014: 372 · 2013: 367 · 2012: 382
- FWCI
- 128.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- DigitalCommons-IMSA (Illinois Mathematics and Science Academy) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- next-generation sequencing, sequencing cost reduction, library preparation, sequencing data analysis, experimental design, genome analysis, gene expression profiling, interactome analysis
- MeSH terms
- Chromosome Mapping, Forecasting, Sequence Alignment, Sequence Analysis, DNA, Genomics
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