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De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing
Spontaneous mutations power evolution, whereas large-scale structural variations (SVs) remain poorly studied, primarily because of the lack of long-read sequencing techniques and powerful analytical tools. Here, we explore the SVs of Escherichia coli by running 67 wild-type (WT) and 37 mismatch repa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10292909/ https://www.ncbi.nlm.nih.gov/pubmed/37293824 http://dx.doi.org/10.1093/gbe/evad106 |
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author | Zhou, Xia Pan, Jiao Wang, Yaohai Lynch, Michael Long, Hongan Zhang, Yu |
author_facet | Zhou, Xia Pan, Jiao Wang, Yaohai Lynch, Michael Long, Hongan Zhang, Yu |
author_sort | Zhou, Xia |
collection | PubMed |
description | Spontaneous mutations power evolution, whereas large-scale structural variations (SVs) remain poorly studied, primarily because of the lack of long-read sequencing techniques and powerful analytical tools. Here, we explore the SVs of Escherichia coli by running 67 wild-type (WT) and 37 mismatch repair (MMR)–deficient (ΔmutS) mutation accumulation lines, each experiencing more than 4,000 cell divisions, by applying Nanopore long-read sequencing and Illumina PE150 sequencing and verifying the results by Sanger sequencing. In addition to precisely repeating previous mutation rates of base-pair substitutions and insertion and deletion (indel) mutation rates, we do find significant improvement in insertion and deletion detection using long-read sequencing. The long-read sequencing and corresponding software can particularly detect bacterial SVs in both simulated and real data sets with high accuracy. These lead to SV rates of 2.77 × 10(−4) (WT) and 5.26 × 10(−4) (MMR-deficient) per cell division per genome, which is comparable with previous reports. This study provides the SV rates of E. coli by applying long-read sequencing and SV detection programs, revealing a broader and more accurate picture of spontaneous mutations in bacteria. |
format | Online Article Text |
id | pubmed-10292909 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-102929092023-06-27 De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing Zhou, Xia Pan, Jiao Wang, Yaohai Lynch, Michael Long, Hongan Zhang, Yu Genome Biol Evol Article Spontaneous mutations power evolution, whereas large-scale structural variations (SVs) remain poorly studied, primarily because of the lack of long-read sequencing techniques and powerful analytical tools. Here, we explore the SVs of Escherichia coli by running 67 wild-type (WT) and 37 mismatch repair (MMR)–deficient (ΔmutS) mutation accumulation lines, each experiencing more than 4,000 cell divisions, by applying Nanopore long-read sequencing and Illumina PE150 sequencing and verifying the results by Sanger sequencing. In addition to precisely repeating previous mutation rates of base-pair substitutions and insertion and deletion (indel) mutation rates, we do find significant improvement in insertion and deletion detection using long-read sequencing. The long-read sequencing and corresponding software can particularly detect bacterial SVs in both simulated and real data sets with high accuracy. These lead to SV rates of 2.77 × 10(−4) (WT) and 5.26 × 10(−4) (MMR-deficient) per cell division per genome, which is comparable with previous reports. This study provides the SV rates of E. coli by applying long-read sequencing and SV detection programs, revealing a broader and more accurate picture of spontaneous mutations in bacteria. Oxford University Press 2023-06-09 /pmc/articles/PMC10292909/ /pubmed/37293824 http://dx.doi.org/10.1093/gbe/evad106 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Zhou, Xia Pan, Jiao Wang, Yaohai Lynch, Michael Long, Hongan Zhang, Yu De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing |
title |
De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing |
title_full |
De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing |
title_fullStr |
De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing |
title_full_unstemmed |
De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing |
title_short |
De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing |
title_sort | de novo structural variations of escherichia coli detected by nanopore long-read sequencing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10292909/ https://www.ncbi.nlm.nih.gov/pubmed/37293824 http://dx.doi.org/10.1093/gbe/evad106 |
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