Literature DB >> 22836167

Transcriptional network analysis of the tryptophan-accumulating rice mutant during grain filling.

Dong Sub Kim1, Kyung Jun Lee, Won Cheol Yim, Jin-Baek Kim, Bo-Keun Ha, Sang Hoon Kim, Si-Yong Kang.   

Abstract

In a previous study, we selected a high tryptophan (Trp)-accumulating rice (Oryza sativa L.) mutant line by in vitro mutagenesis using gamma rays. To obtain detailed information about the Trp biosynthetic pathway during the grain-filling in rice, we investigated the gene expression profiles in the wild-type (cv. Dongan) and the high-level Trp-accumulating mutant line (MRVII-33) at five different grain-filling stages using microarray analysis. The mutant line showed approximately 6.3-fold higher Trp content and 2.3-fold higher amino acids compared with the original cultivar at the final stage (stage V). The intensity of gene expression was analyzed and compared between the wild-type and mutant line at each of the five grain-filling stages using the Rice 4 × 44K oligo DNA microarray. Among the five stages, stage III showed the highest gene expression changes for both up- and down-regulated genes. Among the Trp biosynthesis-related genes, trpG showed high expression in the mutant line during stages I to IV and trpE showed higher at stage III. Gene clustering was performed based on the genes of KEGG's amino acid metabolism, and a total of 276 genes related to amino acid metabolism were placed into three clusters. The functional annotation enrichment analysis of the genes classified into the three clusters was also conducted using ClueGO. It was found that cluster 3 uniquely included biological processes related to aromatic amino acid metabolism. These results suggest that gene analysis based on microarray data is useful for elucidating the biological mechanisms of Trp accumulation in high Trp-accumulating mutants at each of the grain-filling stages.

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Year:  2012        PMID: 22836167     DOI: 10.1007/s00438-012-0712-x

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


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