RT Journal Article SR Electronic T1 Monitoring the Expression Pattern of 1300 Arabidopsis Genes under Drought and Cold Stresses by Using a Full-Length cDNA Microarray JF The Plant Cell JO Plant Cell FD American Society of Plant Biologists SP 61 OP 72 DO 10.1105/tpc.13.1.61 VO 13 IS 1 A1 Seki, Motoaki A1 Narusaka, Mari A1 Abe, Hiroshi A1 Kasuga, Mie A1 Yamaguchi-Shinozaki, Kazuko A1 Carninci, Piero A1 Hayashizaki, Yoshihide A1 Shinozaki, Kazuo YR 2001 UL http://www.plantcell.org/content/13/1/61.abstract AB 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 ∼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.