Transcriptome-based biological dosimetry of gamma radiation in Arabidopsis using DNA damage response genes

Publication date: January 2018
Source:Journal of Environmental Radioactivity, Volume 181
Author(s): Tae Ho Ryu, Jin Kyu Kim, Jeong-Il Kim, Jin-Hong Kim
Plants are used as representative reference biota for the biological assessment of environmental risks such as ionizing radiation due to their immobility. This study proposed a faster, more economical, and more effective method than conventional cytogenetic methods for the biological dosimetry of ionizing radiation in plants (phytodosimetry). We compared various dose-response curves for the radiation-induced DNA damage response (DDR) in Arabidopsis thaliana after relatively "low-dose" gamma irradiation (3, 6, 12, 24, and 48 Gy) below tens of Gy using comet (or single-cell gel electrophoresis), gamma-H2AX, and transcriptomic assays of seven DDR genes (AGO2, BRCA1, GRG, PARP1, RAD17, RAD51, and RPA1E) using quantitative real time PCR. The DDR signal from the comet assay was saturated at 6 Gy, while the gamma-H2AX signal increased up to 48 Gy, following a linear-quadratic dose-response model. The transcriptional changes in the seven DDR genes were fitted to linear or supra-linear quadratic equations with significant dose-dependency. The dose-dependent transcriptional changes were maintained similarly until 24 h after irradiation. The integrated transcriptional dose-response model of AGO2, BRCA1, GRG, and PARP1 was very similar to that of gamma-H2AX, while the transcriptional changes in the BRCA1, GRG, and PARP1 DDR genes revealed significant dependency on the dose-rate, ecotype, and radiation dose. These results suggest that the transcriptome-based dose-response model fitted to a quadratic equation could be used practically for phytodosimetry instead of conventional cytogenetic models, such as the comet and gamma-H2AX assays. The effects of dose-rate and ecotype on the transcriptional changes of DDR genes should also be considered to improve the transcriptome-based phytodosimetry model.



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