Details

Autor(en) / Beteiligte

• Wang, Lei
• Xie, Weibo
• Chen, Ying
• Tang, Weijiang
• Yang, Jiangyi
• Ye, Rongjian
• Liu, Li
• Lin, Yongjun
• Xu, Caiguo
• Xiao, Jinghua
• Zhang, Qifa

Titel

dynamic gene expression atlas covering the entire life cycle of rice

Ist Teil von

• The Plant journal : for cell and molecular biology, 2010-03, Vol.61 (5), p.752-766

Ort / Verlag

Oxford, UK: Oxford, UK : Blackwell Publishing Ltd

Erscheinungsjahr

2010

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• Growth and development of a plant are controlled by programmed expression of suits of genes at the appropriate time, tissue and abundance. Although genomic resources have been developed rapidly in recent years in rice, a model plant for cereal genome research, data of gene expression profiling are still insufficient to relate the developmental processes to transcriptomes, leaving a large gap between the genome sequence and phenotype. In this study, we generated genome-wide expression data by hybridizing 190 Affymetrix GeneChip Rice Genome Arrays with RNA from 39 tissues collected throughout the life cycle of the rice plant from two varieties, Zhenshan 97 and Minghui 63. Analyses of the global transcriptomes revealed many interesting features of dynamic patterns of gene expression across the tissues and stages. In total, 38 793 probe sets were detected as expressed and 69% of the expressed transcripts showed significantly variable expression levels among tissues/organs. We found that similarity of transcriptomes among organs corresponded well to their developmental relatedness. About 5.2% of the expressed transcripts showed tissue-specific expression in one or both varieties and 22.7% of the transcripts exhibited constitutive expression including 19 genes with high and stable expression in all the tissues. This dataset provided a versatile resource for plant genomic research, which can be used for associating the transcriptomes to the developmental processes, understanding the regulatory network of these processes, tracing the expression profile of individual genes and identifying reference genes for quantitative expression analyses.