PMC:99051 / 24485-26109 JSONTXT

{"project":"2_test","denotations":[{"id":"11882253-8650213-10250610","span":{"begin":604,"end":605},"obj":"8650213"},{"id":"11882253-1458489-10250611","span":{"begin":637,"end":638},"obj":"1458489"},{"id":"11882253-11463791-10250612","span":{"begin":1021,"end":1023},"obj":"11463791"}],"text":"Within the limited number of examples, there is a good correlation between the clear results from DADA and other gene expression analysis methods such as quantitative real time RT-PCR, RNase Protection Assays, and various hybridization procedures (data not shown). A number of additional genes with differential regulation discovered by DADA and confirmed by independent methods are now under investigations for the use as therapeutical targets (unpublished observations). Some of the genes identified by DADA including MCP-2 and Cystatin C were neither discovered by means of subtractive hybridization [3], nor by differential display [9], although these methods were successfully used in comparable settings in our laboratory and lead to a high number of differentially expressed genes. Vice versa, DADA could not detect certain differentially expressed genes, that were discovered by standard methods. As an example, the injury-induced differential expression of S100A9 could be detected by subtractive hybridization [33]. The DADA fingerprint of S100A9 was detected in both analyzed cDNA libraries. However, as it occurs only once in each library, no statistical significant differential expression could be identified by the DADA method. Only a subset of genes was identified by all methods. In general, the different approaches can be seen as complementary rather than competitive. The specific findings will certainly vary with changes in the completeness and individual execution of the respective screens. Additionally, DADA offers advantages with regard to absolute and quantitative data at the level of screening."}