Expression Profiles of Mutant PKD2 Gene Overexpression in HEK 293 Cells

Lee, Jae Eun; Yang, Moon Hee; Park, Min Ha; Park, Jong Hoon

Abstract

BACKGROUND
PKD2 gene, encoding polycystin-2 protein is a cause of autosomal dominant polycystic kidney disease (ADPKD) forms cyst in the kidney, liver, and pancreas and result cardiac defects. Polycystin-2 protein interacts with polycystin-1 to produce calcium-permeable non-selective cation current but this signaling pathway was unknown well. To identify expression profiles of mutant PKD2 gene overexpressed HEK 293 cells and EF-hand motif function, we execute microarray experiment using mutant (m1, m1/m2) PKD2 overexpressed cells. METHODS: cDNA probes were prepared by labeling mRNA from mutant (m1, m1/m2) PKD2 overexpressed cells with Cy5-dUTP and Cy3-dUTP through reverse transcription. The mixed probes of each sample were then hybridized with 14, 080 cDNA microarray, and the fluorescent signals were scanned by Arraywox scanner (Applied Precision LLC. Northeastern, USA). The values of Cy5-dUTP and Cy3- dUTP on each spot were analyzed and calculated by ImaGene 5.1 software (BioDiscovery Inc., El Segundo, CA, USA). Normalization was performed by using subtract mean and all genes. RESULTS: It PKD2 over-expressed cells, up-regulated genes were 11 containing PTK2 and down-regulated genes were 27 including MAP2, ABS. In mutant (m1) PKD2 genes, up-regulated genes were 20 and down-regulated genes were 121. In mutant (m1/m2) PKD2 genes, up-regulated genes were 363 and down-regulated genes were 360, respectively. Based on the clustering data, up-regulated genes were 5 containing IL4R and SIL1, and down-regulated genes were 6 including SAE1 and CPSF4. CONCLUSION: Microarray analysis may provide invaluable information on the role of mutant PKD2 gene product. In this study, we have used a high-density cDNA microarray technique to assess the gene expression profile of mutant (m1, m1/m2) PKD2 overexpression cells. Value of up- and down-regulated genes normalized by Genesight 3.2 version software compared with M/A plot data to identify confidence of data. Selected genes numbers were different, but the level of fold value was similar. Finally, we identified that several genes maybe involve in PKD2 function.