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Transcript profiling in rice (Oryza sativa L.) seedlings using serial analysis of gene expression (SAGE)
Author(s) -
Matsumura Hideo,
Nirasawa Shizuko,
Terauchi Ryohei
Publication year - 1999
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1046/j.1365-313x.1999.00640.x
Subject(s) - serial analysis of gene expression , biology , oryza sativa , gene , housekeeping gene , expressed sequence tag , sage , gene expression , gene expression profiling , genetics , complementary dna , sequence analysis , microbiology and biotechnology , physics , nuclear physics
Summary Serial analysis of gene expression (SAGE) was applied for profiling expressed genes in rice seedlings. In the SAGE method, a 9–11 bp fragment (tag) represents each transcript, and frequency of a tag in the sample directly reflects the abundance of the respective mRNA. We studied 10 122 tags derived from 5921 expressed genes in rice ( Oryza sativa L.) seedlings, among which only 1367 genes (23.1%) matched the rice cDNA or EST sequences in the DNA database. SAGE showed that most of the highly expressed genes in rice seedlings belong to the category of housekeeping genes (genes encoding ribosomal proteins or proteins responsible for metabolism and cell structure). Unexpectedly, the most highly expressed gene in rice seedlings was a metallothionein (MT) gene, and together with three other messages for MT, it accounts for 2.7% of total gene expression. To our knowledge, this is the first quantitative study of global gene expression in a higher plant. We further applied the SAGE technique to identify differentially expressed genes between anaerobically treated and untreated rice seedlings. Additionally, we show that a longer cDNA fragment can be easily recovered by PCR using the SAGE tag sequence as a primer, thereby facilitating the analysis of unknown genes identified by tag sequence in SAGE. In combination with micro‐array analysis, SAGE should serve as a highly efficient tool for the identification and isolation of differentially expressed genes in plants.