No abstract

To gain a global view of mRNA decay in Arabidopsis thaliana, suspension cell cultures were treated with a transcriptional inhibitor, and microarrays were used to measure transcript abundance over time. The deduced mRNA half-lives varied widely, from minutes to >24 h. Three features of the transcript displayed a correlation with decay rates: (1) genes possessing at least one intron produce mRNA transcripts significantly more stable than those of intronless genes, and this was not related to overall length, sequence composition, or number of introns; (2) various sequence elements in the 39 untranslated region are enriched among short-and long-lived transcripts, and their multiple occurrence suggests combinatorial control of transcript decay; and (3) transcripts that are microRNA targets generally have short half-lives. The decay rate of transcripts correlated with subcellular localization and function of the encoded proteins. Analysis of transcript decay rates for genes encoding orthologous proteins between Arabidopsis, yeast, and humans indicated that yeast and humans had a higher percentage of transcripts with shorter half-lives and that the relative stability of transcripts from genes encoding proteins involved in cell cycle, transcription, translation, and energy metabolism is conserved. Comparison of decay rates with changes in transcript abundance under a variety of abiotic stresses reveal that a set of transcription factors are downregulated with similar kinetics to decay rates, suggesting that inhibition of their transcription is an important early response to abiotic stress.

The complex cellular functions of an organism frequently rely on physical interactions between proteins. A map of all proteinprotein interactions, an interactome, is thus an invaluable tool. We present an interactome for Arabidopsis (Arabidopsis thaliana) predicted from interacting orthologs in yeast (Saccharomyces cerevisiae), nematode worm (Caenorhabditis elegans), fruitfly (Drosophila melanogaster), and human (Homo sapiens). As an internal quality control, a confidence value was generated based on the amount of supporting evidence for each interaction. A total of 1,159 high confidence, 5,913 medium confidence, and 12,907 low confidence interactions were identified for 3,617 conserved Arabidopsis proteins. There was significant coexpression of genes whose proteins were predicted to interact, even among low confidence interactions. Interacting proteins were also significantly more likely to be found within the same subcellular location, and significantly less likely to be found in conflicting localizations than randomly paired proteins. A notable exception was that proteins located in the Golgi were more likely to interact with Golgi, vacuolar, or endoplasmic reticulum sorted proteins, indicating possible docking or trafficking interactions. These predictions can aid researchers by extending known complexes and pathways with candidate proteins. In addition we have predicted interactions for many previously unknown proteins in known pathways and complexes. We present this interactome, and an online Web interface the Arabidopsis Interactions Viewer, as a first step toward understanding global signaling in Arabidopsis, and to whet the appetite for those who are awaiting results from high-throughput experimental approaches.