Identification of master regulator candidates for diabetes progression in Goto-Kakizaki Rat by a computational procedure

Recently, we have identified 39 candidates of active regulatory networks for the diabetes progression in Goto-Kakizaki (GK) rat by using the network screening, which were well consistent with the previous knowledge of regulatory relationship between transcription factors (TFs) and their regulated genes. In addition, we have developed a computational procedure for identifying transcriptional master regulators (MRs) related to special biological phenomena, such as diseases, in conjunction of the network screening and inference. Here, we apply our procedure to identify the MR candidates for diabetes progression in GK rat. First, active TF-gene relationships for three periods in GK rat were detected by the network screening and the network inference, in consideration of TFs with specificity and coverage, and finally only 5 TFs were identified as the candidates of MRs. The limited number of the candidates of MRs promises to perform experiments to verify them.