Title | Towards population-scale long-read sequencing. |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | De Coster, W, Weissensteiner, MH, Sedlazeck, FJ |
Journal | Nat Rev Genet |
Volume | 22 |
Issue | 9 |
Pagination | 572-587 |
Date Published | 2021 Sep |
ISSN | 1471-0064 |
Keywords | Computational Biology, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Industrial Development, Sequence Analysis, DNA |
Abstract | 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. |
DOI | 10.1038/s41576-021-00367-3 |
Alternate Journal | Nat Rev Genet |
PubMed ID | 34050336 |
PubMed Central ID | PMC8161719 |
Grant List | UM1 HG008898 / HG / NHGRI NIH HHS / United States |
Towards population-scale long-read sequencing.
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