Towards population-scale long-read sequencing.

Nat Rev Genet

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.

Published: September 2021


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Article 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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161719PMC
http://dx.doi.org/10.1038/s41576-021-00367-3DOI Listing

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