High information content assays for genetic toxicology testing: A report of the International Workshops on Genotoxicity Testing (IWGT)

Mutat Res Genet Toxicol Environ Mutagen. 2019 Nov;847:403022. doi: 10.1016/j.mrgentox.2019.02.003. Epub 2019 Feb 21.


We live in an era of 'big data', where the volume, velocity, and variety of the data being generated is increasingly influencing the way toxicological sciences are practiced. With this in mind, a workgroup was formed for the 2017 International Workshops on Genotoxicity Testing (IWGT) to consider the use of high information content data in genetic toxicology assessments. Presentations were given on adductomics, global transcriptional profiling, error-reduced single-molecule sequencing, and cellular phenotype-based assays, which were identified as methodologies that are relevant to present-day genetic toxicology assessments. Presenters and workgroup members discussed the state of the science for these methodologies, their potential use in genetic toxicology, current limitations, and the future work necessary to advance their utility and application. The session culminated with audience-assisted SWOT (strength, weakness, opportunities, and threats) analyses. The summary report described herein is structured similarly. A major conclusion of the workgroup is that while conventional regulatory genetic toxicology testing has served the public well over the last several decades, it does not provide the throughput that has become necessary in modern times, and it does not generate the mechanistic information that risk assessments ideally take into consideration. The high information content assay platforms that were discussed in this session, as well as others under development, have the potential to address aspect(s) of these issues and to meet new expectations in the field of genetic toxicology.

Keywords: Adductomics; Error-reduced sequencing; Genetic toxicology; High information content; New technologies; Transcriptomics.

Publication types

  • Introductory Journal Article

MeSH terms

  • Animals
  • Big Data
  • Cell Line
  • DNA Adducts / analysis
  • DNA Barcoding, Taxonomic / methods
  • DNA Damage
  • Data Mining
  • Drug Evaluation, Preclinical
  • Gene Expression Profiling / methods
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Image Processing, Computer-Assisted
  • Mass Spectrometry / methods
  • Meta-Analysis as Topic
  • Mice
  • Mutagenicity Tests / methods*
  • Mutagenicity Tests / standards
  • Phenotype
  • Single Molecule Imaging
  • Toxicology / methods
  • Transcriptome


  • DNA Adducts