Although radiation responses are results of multiple signaling pathways, the transcriptional responses usually involve p53 and NF-��B networks. For example, TP53 was involved inthe response to high-dose radiation, which however showed less response after low-dose exposures. Microarray analysis is one of the most comprehensive approaches to identify gene expression and has led to significant advances in the knowledge of radiation-induced responses. Until now, however, limited studies have been performed to assess the RAR at the transcriptional level. Previous researchers observed RAR in three human lymphoblastoid cell lines and associated TP53-related genes with RAR. Other studies focused on the changes in gene expression Bendroflumethiazide following direct high-or low-dose radiation or following the induction of bystander effects. However, there was in sufficient systematic analysis in most of the studies. This prompted us to perform systematic studies in or der to understand the underlying mechanisms for RAR. The critical factors involved in RAR induction were the priming dose, challenging dose and time interval between the applications of the two doses. In general, RAR responses are rarely induced when the priming dose is over 200 m Gy, and are almost never induced when it is over 500m Gy. Prior to this research, we studied Carmustine various combinations of doses and time intervals, and found that a combination of a priming dose of 5c Gy, a challenging dose of 2 Gy dose and a time interval of 12 could induce a significant RAR response in AG01522 cells. In the present study, we focused on mRNA and micro RNA microarray studies, and aimed to characterize the transcriptome for RAR in AG01522 human skin fibroblasts and to examine the functional regulatory networks at the genetic level. AG01522 cells were exposed at a specific time point to a challenging dose of 2 Gy in the RAR group, or a priming dose of 5c Gy in the low-dose group. The micronucleus assay was also employed to quantify the radiation-induced chromosome aberrations.The results could provide useful information for identifying biomarkers of RAR, and thus help us better understand RAR itself and its potential implications on radiotherapy procedures. Within any given gene sets, GO-based functional analysis provides statistically enriched GO terms, describing gene products and demonstrating their relationships according to three ontology categories: biological process, molecular function and cellular component.