The authors performed microRNA and mRNA expression profiling of 90 lymphoblastoid cell lines and adopted correlation coefficient analysis to discover postive- or negative-correlation miRNA-mRNA pairs. For genes with significant correlation, they used TargetScan to check prediction, GO tool (http://discover.nci.nih.gov/gominer/) to check overpresented biological process genes and chromosomal location for the suspect that co-located genes and microRNAs tend to be correlated. They also pointed out the fact that miRNA mainly affects the protein level, which could be one of the reasons they did not observe any evidence of concordance in most miRNA sets.

"Experiments with DNA-PKcs-deficient cell lines and a specific DNA-PKcs inhibitor demonstrate that both the general repression of mRNA translation and the preferential translation of specific mRNAs depend on DNA-PKcs activity, and therefore our data establish a link between a key DNA damage signaling component and protein synthesis."

By incorporating three commonly used and accurate miRNA prediction algorithms, TargetScan, PITA and PicTar, MMIA integrates miRNA and mRNA expression data with predicted miRNA target information for analyzing miRNA-associated phenotypes and biological functions by gene set analysis, in addition to analysis of miRNA primary transcript gene promoters.

Our data support a model in which the RNase-L-mediated degradation of RP mRNAs inhibits translation, and may contribute to its antiproliferative, senescence inducing and tumor suppressor activities.