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SMURF-seq: efficient copy number profiling on long-read sequencers

We present SMURF-seq, a protocol to efficiently sequence short DNA molecules on a long-read sequencer by randomly ligating them to form long molecules. Applying SMURF-seq using the Oxford Nanopore MinION yields up to 30 fragments per read, providing an average of 6.2 and up to 7.5 million mappable f...

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Detalles Bibliográficos
Autores principales: Prabakar, Rishvanth K., Xu, Liya, Hicks, James, Smith, Andrew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615205/
https://www.ncbi.nlm.nih.gov/pubmed/31287019
http://dx.doi.org/10.1186/s13059-019-1732-1
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author Prabakar, Rishvanth K.
Xu, Liya
Hicks, James
Smith, Andrew D.
author_facet Prabakar, Rishvanth K.
Xu, Liya
Hicks, James
Smith, Andrew D.
author_sort Prabakar, Rishvanth K.
collection PubMed
description We present SMURF-seq, a protocol to efficiently sequence short DNA molecules on a long-read sequencer by randomly ligating them to form long molecules. Applying SMURF-seq using the Oxford Nanopore MinION yields up to 30 fragments per read, providing an average of 6.2 and up to 7.5 million mappable fragments per run, increasing information throughput for read-counting applications. We apply SMURF-seq on the MinION to generate copy number profiles. A comparison with profiles from Illumina sequencing reveals that SMURF-seq attains similar accuracy. More broadly, SMURF-seq expands the utility of long-read sequencers for read-counting applications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1732-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-66152052019-07-18 SMURF-seq: efficient copy number profiling on long-read sequencers Prabakar, Rishvanth K. Xu, Liya Hicks, James Smith, Andrew D. Genome Biol Method We present SMURF-seq, a protocol to efficiently sequence short DNA molecules on a long-read sequencer by randomly ligating them to form long molecules. Applying SMURF-seq using the Oxford Nanopore MinION yields up to 30 fragments per read, providing an average of 6.2 and up to 7.5 million mappable fragments per run, increasing information throughput for read-counting applications. We apply SMURF-seq on the MinION to generate copy number profiles. A comparison with profiles from Illumina sequencing reveals that SMURF-seq attains similar accuracy. More broadly, SMURF-seq expands the utility of long-read sequencers for read-counting applications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1732-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-08 /pmc/articles/PMC6615205/ /pubmed/31287019 http://dx.doi.org/10.1186/s13059-019-1732-1 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Prabakar, Rishvanth K.
Xu, Liya
Hicks, James
Smith, Andrew D.
SMURF-seq: efficient copy number profiling on long-read sequencers
title SMURF-seq: efficient copy number profiling on long-read sequencers
title_full SMURF-seq: efficient copy number profiling on long-read sequencers
title_fullStr SMURF-seq: efficient copy number profiling on long-read sequencers
title_full_unstemmed SMURF-seq: efficient copy number profiling on long-read sequencers
title_short SMURF-seq: efficient copy number profiling on long-read sequencers
title_sort smurf-seq: efficient copy number profiling on long-read sequencers
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615205/
https://www.ncbi.nlm.nih.gov/pubmed/31287019
http://dx.doi.org/10.1186/s13059-019-1732-1
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