TY - JOUR
T1 - De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing
AU - Zhou, Xia
AU - Pan, Jiao
AU - Wang, Yaohai
AU - Lynch, Michael
AU - Long, Hongan
AU - Zhang, Yu
N1 - Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.
PY - 2023/6/1
Y1 - 2023/6/1
N2 - 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.
AB - 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.
KW - long-read sequencing
KW - mutation accumulation
KW - mutation distribution
KW - structural variations
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U2 - 10.1093/gbe/evad106
DO - 10.1093/gbe/evad106
M3 - Article
C2 - 37293824
AN - SCOPUS:85164042552
SN - 1759-6653
VL - 15
JO - Genome biology and evolution
JF - Genome biology and evolution
IS - 6
M1 - evad106
ER -