DNA microarray analysis in down syndrome

Abstract

Objective: Down Syndrome (DS) is complex genetic disorder with mental retardation, skelectal defects, defects of metabolism in the brain. The molecular mechanism of DS is not well understood and prenatal genetic diagnosis is important in cliniques. cDNA microarray technology is used to the analysis of gene expression levels for thousands of genes simultaneously. We tried to find the DS biomarker for prenatal genetic diagnosis by comparing the gene expression profiles from DS and normal amniotic cells using cDNA microarray technique.Design: About 1100 human genes were analyzed in this experiment. After hybridization, this chip were scanned and analyzed. Comparing the expression profile of DS with normal cell, we obtained the substractive gene expression profiles and further analysis using 5 different DS samples.Materials/Methods: We extracted total RNA from DS amniotic and normal cells using Qiagen RNA prep kit. Each total RNA was labeled with cy-3 and cy-5. The chip hybridized for 16 hours in hyb-chamber. After hybridization, non-labeled probe is removed in washing step. Finally the chip was scanned by ScanArray 4000XL. We used Imagene software for gene expression data analysis. This software showed various graphic image data. From each quantified signal, we could compared expression levels.Results: Performing clustering analysis, we found that 22 genes from 1.1K genes analysis were differentially expressed in DS. The expression level of lycyl oxidase gene in DS cells is about five times higher than that of normal cell. Twenty of genes were increased by two times in DS. Only one of genes was decreased by a half in DS. Among 22 genes, 17 genes were located in chromosome 21. These genes were related with protein expression, cell division, metabolism, cell structure, organism defense, and homeostasis. We are doing of further analysis using five different DS samples.Conclusions: Difference expression data in DS and wild-type cells will be basis of gene expression profile analysis. Most of genes did not show the large difference, but some of differentially expressed genes may be important in DS. We will discuss the role of these genes as the biomarker in Down Syndrome.Supported by: Korean Health 21 R&D Project, Ministry of Health and Welfare, Korea (01-PJ10-PG6–01GN13–0002). Objective: Down Syndrome (DS) is complex genetic disorder with mental retardation, skelectal defects, defects of metabolism in the brain. The molecular mechanism of DS is not well understood and prenatal genetic diagnosis is important in cliniques. cDNA microarray technology is used to the analysis of gene expression levels for thousands of genes simultaneously. We tried to find the DS biomarker for prenatal genetic diagnosis by comparing the gene expression profiles from DS and normal amniotic cells using cDNA microarray technique. Design: About 1100 human genes were analyzed in this experiment. After hybridization, this chip were scanned and analyzed. Comparing the expression profile of DS with normal cell, we obtained the substractive gene expression profiles and further analysis using 5 different DS samples. Materials/Methods: We extracted total RNA from DS amniotic and normal cells using Qiagen RNA prep kit. Each total RNA was labeled with cy-3 and cy-5. The chip hybridized for 16 hours in hyb-chamber. After hybridization, non-labeled probe is removed in washing step. Finally the chip was scanned by ScanArray 4000XL. We used Imagene software for gene expression data analysis. This software showed various graphic image data. From each quantified signal, we could compared expression levels. Results: Performing clustering analysis, we found that 22 genes from 1.1K genes analysis were differentially expressed in DS. The expression level of lycyl oxidase gene in DS cells is about five times higher than that of normal cell. Twenty of genes were increased by two times in DS. Only one of genes was decreased by a half in DS. Among 22 genes, 17 genes were located in chromosome 21. These genes were related with protein expression, cell division, metabolism, cell structure, organism defense, and homeostasis. We are doing of further analysis using five different DS samples. Conclusions: Difference expression data in DS and wild-type cells will be basis of gene expression profile analysis. Most of genes did not show the large difference, but some of differentially expressed genes may be important in DS. We will discuss the role of these genes as the biomarker in Down Syndrome. Supported by: Korean Health 21 R&D Project, Ministry of Health and Welfare, Korea (01-PJ10-PG6–01GN13–0002).