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Comparison between SAGE and cDNA microarray for quantitative accuracy in transcript profiling analyses
- Comparison between SAGE and cDNA microarray for quantitative accuracy in transcript profiling analyses
- Eun M.E.; Ji Y.L.; Hye S.P.; Youn J.B.; Ha-Lee Y.M.; Dong H.L.
- Ewha Authors
- SCOPUS Author ID
- Issue Date
- Journal Title
- Journal of Plant Biology
- vol. 49, no. 6, pp. 498 - 506
- SCIE; SCOPUS; KCI
- Array-based hybridization and the serial analysis of gene expression (SAGE) are the most common approaches for high-throughput transcript analysis. Each has advantages and disadvantages. The cDNA array allows rapid screening of a large number of samples but cannot detect unknown genes. In contrast, SAGE can detect those unknown genes or transcripts but is restricted to fewer samples. Combining these two methods could provide better high-throughput analysis that allows rapid screening of both previously known and unknown genes. For this, we have generated two cDNA microarrays (from human and plant systems) based on SAGE data. The results from both of these were analyzed for their correlation and accuracy. One specialized cDNA microarray, putatively named Gastricchip, was constructed with 1744 probes, including 858 cDNA fragments based on SAGE data from gastric-cancer tissues. The other microarray, putatively named Coldstresschip, was constructed with 1482 probes, including 1209 cDNA fragments based on SAGE data from cold-stressed Arabidopsis. The hybridizations for these microarrays with relatively small sized and mostly low-level expressed gene probes were evaluated by four different labeling methods. Using primarily for these customized microarrays, the Genisphere 3DNA SubmicroEX protocol, an indirect labeling technique, produced the lowest background but the highest signal recovery, with a 1.4 S/B cut-off and high reproducibilrty (R=0.89-0.95). These cDNA microarray data were closely correlated with the SAGE data (R=0.47-0.56), especially for genes with higher expression levels (R=0.66-0.70), demonstrating that results from SAGE and a cDNA microarray are comparable and that combinatorial approach provides more efficient and accurate gene-expression patterns. In particular, identity of the genes on both sets of data is assured and hybridization for cDNA microarray is efficient.
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