De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing

Xia Zhou, Jiao Pan, Yaohai Wang, Michael Lynch, Hongan Long, Yu Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article numberevad106
JournalGenome biology and evolution
Volume15
Issue number6
DOIs
StatePublished - Jun 1 2023

Keywords

  • long-read sequencing
  • mutation accumulation
  • mutation distribution
  • structural variations

ASJC Scopus subject areas

  • General Medicine

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