Seki M, Narusaka M, Abe H, Kasuga M, Yamaguchi-Shinozaki K, Carninci P, Hayashizaki Y, Shinozaki K. Monitoring the expression pattern of 1300 Arabidopsis genes under drought and cold stresses by using a full-length cDNA microarray.
THE PLANT CELL 2001;
13:61-72. [PMID:
11158529 PMCID:
PMC102214 DOI:
10.1105/tpc.13.1.61]
[Citation(s) in RCA: 597] [Impact Index Per Article: 24.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Full-length cDNAs are essential for functional analysis of plant genes. Using the biotinylated CAP trapper method, we constructed full-length Arabidopsis cDNA libraries from plants in different conditions, such as drought-treated, cold-treated, or unstressed plants, and at various developmental stages from germination to mature seed. We prepared a cDNA microarray using approximately 1300 full-length Arabidopsis cDNAs to identify drought- and cold-inducible genes and target genes of DREB1A/CBF3, a transcription factor that controls stress-inducible gene expression. In total, 44 and 19 cDNAs for drought- and cold-inducible genes, respectively, were isolated, 30 and 10 of which were novel stress-inducible genes that have not been reported as drought- or cold-inducible genes previously. Twelve stress-inducible genes were identified as target stress-inducible genes of DREB1A, and six of them were novel. On the basis of RNA gel blot and microarray analyses, the six genes were identified as novel drought- and cold-inducible genes that are controlled by DREB1A. Eleven DREB1A target genes whose genomic sequences have been registered in the GenBank database contained the dehydration-responsive element (DRE) or DRE-related CCGAC core motif in their promoter regions. These results show that our full-length cDNA microarray is a useful material with which to analyze the expression pattern of Arabidopsis genes under drought and cold stresses, to identify target genes of stress-related transcription factors, and to identify potential cis-acting DNA elements by combining the expression data with the genomic sequence data.
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