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LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules

Nucleic acid sequence analyses are fundamental to all aspects of biological research, spanning aging, mitochondrial DNA (mtDNA) and cancer, as well as microbial and viral evolution. Over the past several years, significant improvements in DNA sequencing, including consensus sequence analysis, have p...

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Autores principales: Annis, Sofia, Fleischmann, Zoë, Logan, Robert, Mullin-Bernstein, Zachary, Franco, Melissa, Saürich, Josefin, Tilly, Jonathan L., Woods, Dori C., Khrapko, Konstantin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202536/
https://www.ncbi.nlm.nih.gov/pubmed/32345770
http://dx.doi.org/10.18632/aging.103171
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author Annis, Sofia
Fleischmann, Zoë
Logan, Robert
Mullin-Bernstein, Zachary
Franco, Melissa
Saürich, Josefin
Tilly, Jonathan L.
Woods, Dori C.
Khrapko, Konstantin
author_facet Annis, Sofia
Fleischmann, Zoë
Logan, Robert
Mullin-Bernstein, Zachary
Franco, Melissa
Saürich, Josefin
Tilly, Jonathan L.
Woods, Dori C.
Khrapko, Konstantin
author_sort Annis, Sofia
collection PubMed
description Nucleic acid sequence analyses are fundamental to all aspects of biological research, spanning aging, mitochondrial DNA (mtDNA) and cancer, as well as microbial and viral evolution. Over the past several years, significant improvements in DNA sequencing, including consensus sequence analysis, have proven invaluable for high-throughput studies. However, all current DNA sequencing platforms have limited utility for studies of complex mixtures or of individual long molecules, the latter of which is crucial to understanding evolution and consequences of single nucleotide variants and their combinations. Here we report a new technology termed LUCS (Long-molecule UMI-driven Consensus Sequencing), in which reads from third-generation sequencing are aggregated by unique molecular identifiers (UMIs) specific for each individual DNA molecule. This enables in-silico reconstruction of highly accurate consensus reads of each DNA molecule independent of other molecules in the sample. Additionally, use of two UMIs enables detection of artificial recombinants (chimeras). As proof of concept, we show that application of LUCS to assessment of mitochondrial genomes in complex mixtures from single cells was associated with an error rate of 1X10(-4) errors/nucleotide. Thus, LUCS represents a major step forward in DNA sequencing that offers high-throughput capacity and high-accuracy reads in studies of long DNA templates and nucleotide variants in heterogenous samples.
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spelling pubmed-72025362020-05-11 LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules Annis, Sofia Fleischmann, Zoë Logan, Robert Mullin-Bernstein, Zachary Franco, Melissa Saürich, Josefin Tilly, Jonathan L. Woods, Dori C. Khrapko, Konstantin Aging (Albany NY) Research Paper Nucleic acid sequence analyses are fundamental to all aspects of biological research, spanning aging, mitochondrial DNA (mtDNA) and cancer, as well as microbial and viral evolution. Over the past several years, significant improvements in DNA sequencing, including consensus sequence analysis, have proven invaluable for high-throughput studies. However, all current DNA sequencing platforms have limited utility for studies of complex mixtures or of individual long molecules, the latter of which is crucial to understanding evolution and consequences of single nucleotide variants and their combinations. Here we report a new technology termed LUCS (Long-molecule UMI-driven Consensus Sequencing), in which reads from third-generation sequencing are aggregated by unique molecular identifiers (UMIs) specific for each individual DNA molecule. This enables in-silico reconstruction of highly accurate consensus reads of each DNA molecule independent of other molecules in the sample. Additionally, use of two UMIs enables detection of artificial recombinants (chimeras). As proof of concept, we show that application of LUCS to assessment of mitochondrial genomes in complex mixtures from single cells was associated with an error rate of 1X10(-4) errors/nucleotide. Thus, LUCS represents a major step forward in DNA sequencing that offers high-throughput capacity and high-accuracy reads in studies of long DNA templates and nucleotide variants in heterogenous samples. Impact Journals 2020-04-28 /pmc/articles/PMC7202536/ /pubmed/32345770 http://dx.doi.org/10.18632/aging.103171 Text en Copyright © 2020 Annis et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Annis, Sofia
Fleischmann, Zoë
Logan, Robert
Mullin-Bernstein, Zachary
Franco, Melissa
Saürich, Josefin
Tilly, Jonathan L.
Woods, Dori C.
Khrapko, Konstantin
LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules
title LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules
title_full LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules
title_fullStr LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules
title_full_unstemmed LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules
title_short LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules
title_sort lucs: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual dna molecules
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202536/
https://www.ncbi.nlm.nih.gov/pubmed/32345770
http://dx.doi.org/10.18632/aging.103171
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