Abstract
It is difficult to identify mutagen-induced genome-wide somatic mutations using next generation sequencing; hence, mutagenic features of each mutagen and their roles in cancer development require further elucidation. We described Hawk-Seq™, a highly accurate genome sequencing method and the optimal conditions, for using it to construct libraries that would enable the accurate (c.a. 1 error/107–108 bp) and efficient survey of genome-wide mutations. Genomic mutations in gpt delta mice or Salmonella typhimurium TA100 exposed to methylnitrosourea (MNU), ethylnitrosourea (ENU), diethylnitrosamine (DEN), benzo[a]pyrene (BP), and aristolochic acid (AA) were profiled using Hawk-Seq™ to analyse positions, substitution patterns, or frequencies. The resultant vast mutation data provided high-resolution mutational signatures, including for minor mutational fractions (e.g. G:C>A:T by AA), which enabled the clarification of the mutagenic features of all mutagens. The 96-type mutational signatures of MNU, AA, and BP indicate their partial similarity to signature 11, 22, and 4 or 29, respectively. Meanwhile, signatures attributable to ENU and DEN were highly similar to each other, but not to signature 11, suggesting that the mechanisms of these agents differed from those of typical alkylating agents. Thus, Hawk-Seq™ can clarify genome-wide chemical mutagenicity profiles at extraordinary resolutions, thereby providing insight into mutagen mechanisms and their roles in cancer development.
Highlights
The analysis of genomic mutations using generation sequencing (NGS) has enabled us to generate large-scale, genome-wide catalogues of somatic mutations in human cancer patients (Meyerson et al 2010; Garraway and Lander 2013)
It is speculated that the smaller the target genome size, the higher the possibility of overlap by accident (OBA); besides, it would be affected by input DNA amount for PCR (IDAP)
We optimized Hawk-SeqTM by manipulating the IDAP with regard to these two parameters, using genomic DNA samples of S. typhimurium TA100, whose genome is the smallest among resources used for evaluating mutagenicity
Summary
The analysis of genomic mutations using generation sequencing (NGS) has enabled us to generate large-scale, genome-wide catalogues of somatic mutations in human cancer patients (Meyerson et al 2010; Garraway and Lander 2013). These large-scale cancer mutation data, which reflect the features of mutation profiles for each type of cancer, have. 2 R&D‐Analytical Science Research, Kao Corporation, 2606 Akabane, Ichikai‐Machi, Haga‐Gun, Tochigi 321‐3497, Japan enabled us to analyse mutation spectra at extraordinary resolutions and the underlying processes for the development of each type of cancer (Stratton et al 2009; Stratton 2011). The associated large-scale, genome-wide mutation data would provide clarity regarding the mutagenic features of mutagens at high resolutions, as observed during cancer research and would provide insight into their role in cancer
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
