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A gene expression map of Arabidopsis development


Davison,  T
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;


Schoelkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Schmid, M., Davison, T., Henz, S., Pape, U., Demar, M., Vingron, M., et al. (2005). A gene expression map of Arabidopsis development. Poster presented at 16th International Conference on Arabidopsis Research (ICAR 2005), Madison, WI, USA.

Cite as: https://hdl.handle.net/21.11116/0000-000C-27BC-5
In contrast to most animals, plants develop continuously, with new organs being initiated and elaborated throughout the life cycle of the organism. As a consequence, individuals consist of repeated units, such as leaves or flowers, which are present in many developmental stages at any given time of the life cycle. It follows that many transcriptional programs underlying the development of different organ systems are continuously active. Plants therefore provide an excellent opportunity to study how transcriptional programs control multicellular development. We have analyzed global gene expression during development of the reference plant Arabidopsis thaliana in 79 samples covering many stages, from embryogenesis to senescence, and diverse organs. Among several findings is the observation that the expression levels of transcription factor genes and signal transduction components are similar to those of metabolic genes. In contrast, genes encoding proteins involved in photosynthesis or protein biosynthesis are expressed at substantially higher levels, whereas genes in the replication category are underexpressed. Another focus of our study is the analysis of co-expression of genes throughout development. Examining the expression patterns of large gene families, we find that they are often more similar than expected by chance, indicating that many gene families have been co-opted for specific developmental processes. Also, physical location along the chromosomes affects gene activity. Using sliding window analysis, we find that genes in close proximity are much more likely to be co-expressed than expected by chance. There are a few small regions of very high correlation, which in most cases correspond to tandem duplications. Tandem duplications do not, however, explain all of the co-expression, since we find significant correlation even when tandem-duplications are excluded from the analysis. The dataset is a part of the AtGenExpress expression atlas, which aims at giving the community access to a large micro array dataset. All data is being made publicly available through several websites.