Towards population-scale long-read sequencing
Open accessAbstract
Long-read sequencing technologies have now reached a level of accuracy and yield that allows their application to variant detection at a scale of tens to thousands of samples. Concomitant with the development of new computational tools, the first population-scale studies involving long-read sequencing have emerged over the past 2 years and, given the continuous advancement of the field, many more are likely to follow. In this Review, we survey recent developments in population-scale long-read sequencing, highlight potential challenges of a scaled-up approach and provide guidance regarding experimental design. We provide an overview of current long-read sequencing platforms, variant calling methodologies and approaches for de novo assemblies and reference-based mapping approaches. Furthermore, we summarize strategies for variant validation, genotyping and predicting functional impact and emphasize challenges remaining in achieving long-read sequencing at a population scale. Long-read sequencing at the population scale presents specific challenges but is becoming increasingly accessible. In this Review, Sedlazeck and colleagues discuss the major platforms and analytical tools, considerations in project design and challenges in scaling long-read sequencing to populations.
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Yan, S. M., Sherman, R. M., Taylor, D. J., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.26.428314 · Cited by 2 · see citing works
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Curated variation benchmarks for challenging medically relevant autosomal genes
Wagner, J., Olson, N. D., Harris, L., McDaniel, J., Cheng, H., Fungtammasan, A., Hwang, Y.-C., Gupta, R., Wenger, A. M., Rowell, W. J., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01158-1 · Cited by 241 · see citing works
Self-citationComprehensive genome analysis and variant detection at scale using DRAGEN
Behera, S., Catreux, S., Rossi, M., Truong, S., Huang, Z., Ruehle, M., Visvanath, A., Parnaby, G., Roddey, C., Onuchic, V., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02382-1 · Cited by 137 · see citing works
Self-citationStructural variation across 138,134 samples in the TOPMed consortium
Jun, G., English, A., Metcalf, G., Yang, J., Chaisson, M., Pankratz, N., Menon, V., Salerno, W., Krasheninina, O., Smith, A., et al. (2023) · doi:10.21203/rs.3.rs-2515453/v1 · Cited by 24 · see citing works
Self-citation
- Authors
- De Coster, W., Weissensteiner, M. H., & Sedlazeck, F. J.
- Affiliations
- Pennsylvania State University (US)
- Baylor College of Medicine (US)
- Corresponding author
- Sedlazeck, Fritz J.
- Venue
- Nature Reviews Genetics
- Published
- 2021-05-28
- Volume
- 22
- Issue
- 9
- Pages
- 572-587
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- PMC
- PMC8161719
- OpenAlex
- W3164211868
- Semantic Scholar
- 007d7bb2c301f1bc4e480537e8542a7687195af4
- Cited by
- 323
- References
- 179
- Citations by year
- 2026: 42 · 2025: 56 · 2024: 87 · 2023: 62 · 2022: 60 · 2021: 15 · 2019: 1
- FWCI
- 6.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Fonds Wetenschappelijk Onderzoek
- Vlaamse regering
- National Institutes of Health
- National Human Genome Research Institute (UM1HG008898)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- long-read sequencing, population-scale genomics, variant calling, de novo assembly, variant validation, genotyping, functional impact prediction, sequencing platform comparison, experimental design
- MeSH terms
- Industrial Development, Humans, Genome, Human, Sequence Analysis, DNA, Computational Biology, Genomics, High-Throughput Nucleotide Sequencing
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 ›
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