Plants (May 2021)

Application of Gamma Ray-Responsive Genes for Transcriptome-Based Phytodosimetry in Rice

  • Jin-Hong Kim,
  • Kwon Hwangbo,
  • Eujin Lee,
  • Shubham Kumar Dubey,
  • Moon-Soo Chung,
  • Byung-Yeoup Chung,
  • Sungbeom Lee

DOI
https://doi.org/10.3390/plants10050968
Journal volume & issue
Vol. 10, no. 5
p. 968

Abstract

Read online

Transcriptome-based dose–response curves were recently applied to the phytodosimetry of gamma radiation in a dicot plant, Arabidopsis thaliana, as an alternative biological assessment of genotoxicity using DNA damage response (DDR) genes. In the present study, we characterized gamma ray-responsive marker genes for transcriptome-based phytodosimetry in a monocot plant, rice (Oryza sativa L.), and compared different phytodosimetry models between rice and Arabidopsis using gamma-H2AX, comet, and quantitative transcriptomic assays. The transcriptome-based dose–response curves of four marker genes (OsGRG, OsMutS, OsRAD51, and OsRPA1) were reliably fitted to quadratic or exponential decay equations (r2 > 0.99). However, the single or integrated dose–response curves of these genes were distinctive from the conventional models obtained by the gamma-H2AX or comet assays. In comparison, rice displayed a higher dose-dependency in the comet signal and OsRAD51 transcription, while the gamma-H2AX induction was more dose-dependent in Arabidopsis. The dose-dependent transcriptions of the selected gamma-ray-inducible marker genes, including OsGRG, OsMutS, OsRAD51, and OsRPA1 in rice and AtGRG, AtPARP1, AtRAD51, and AtRPA1E in Arabidopsis, were maintained similarly at different vegetative stages. These results suggested that the transcriptome-based phytodosimetry model should be further corrected with conventional genotoxicity- or DDR-based models despite the high reliability or dose-dependency of the model. In addition, the relative weighting of each gene in the integrated transcriptome-based dose–response model using multiple genes needs to be considered based on the trend and amplitude of the transcriptional change.

Keywords