Annotating genes of known and unknown function by large-scale coexpression analysis.

About 40% of the proteins encoded in eukaryotic genomes are proteins of unknown function (PUFs). Their functional characterization remains one of the main challenges in modern biology. In this study we identified the PUF encoding genes from Arabidopsis (Arabidopsis thaliana) using a combination of sequence similarity, domain-based, and empirical approaches. Large-scale gene expression analyses of 1,310 publicly available Affymetrix chips were performed to associate the identified PUF genes with regulatory networks and biological processes of known function. To generate quality results, the study was restricted to expression sets with replicated samples. First, genome-wide clustering and gene function enrichment analysis of clusters allowed us to associate 1,541 PUF genes with tightly coexpressed genes for proteins of known function (PKFs). Over 70% of them could be assigned to more specific biological process annotations than the ones available in the current Gene Ontology release. The most highly overrepresented functional categories in the obtained clusters were ribosome assembly, photosynthesis, and cell wall pathways. Interestingly, the majority of the PUF genes appeared to be controlled by the same regulatory networks as most PKF genes, because clusters enriched in PUF genes were extremely rare. Second, large-scale analysis of differentially expressed genes was applied to identify a comprehensive set of abiotic stress-response genes. This analysis resulted in the identification of 269 PKF and 104 PUF genes that responded to a wide variety of abiotic stresses, whereas 608 PKF and 206 PUF genes responded predominantly to specific stress treatments. The provided coexpression and differentially expressed gene data represent an important resource for guiding future functional characterization experiments of PUF and PKF genes. Finally, the public Plant Gene Expression Database (http://bioweb.ucr.edu/PED) was developed as part of this project to provide efficient access and mining tools for the vast gene expression data of this study.

Charting plant interactomes: possibilities and challenges.

Protein-protein interactions are essential for nearly all cellular processes. Therefore, an important goal of post-genomic research for defining gene function and understanding the function of macromolecular complexes involves creating 'interactome' maps from empirical or inferred datasets. Systematic efforts to conduct high-throughput surveys of protein-protein interactions in plants are needed to chart the complex and dynamic interaction networks that occur throughout plant development. However, no single approach can build a complete map of the interactome. Here, we review the utility and potential of various experimental approaches for creating large-scale protein-protein interaction maps in plants. Bioinformatics approaches for curating and assessing the confidence of these datasets through inter-species comparisons will be crucial in achieving a complete understanding of protein interaction networks in plants.

A phyloproteomic characterization of in vitro autophosphorylation in calcium-dependent protein kinases.

Calcium-dependent protein kinases (CDPKs) are a novel class of signaling molecules that have been broadly implicated in relaying specific calcium-mediated responses to biotic and abiotic stress as well as developmental cues in both plants and protists. Calcium-dependent autophosphorylation has been observed in almost all CDPKs examined, but a physiological role for autophosphorylation has not been demonstrated. To date, only a handful of autophosphorylation sites have been mapped to specific residues within CDPK amino acid sequences. In an attempt to gain further insight into this phenomenon, we have mapped autophosphorylation sites and compared these phosphorylation patterns among multiple CDPK isoforms. From eight CDPKs and two CDPK-related kinases from Arabidopsis thaliana and Plasmodium falciparum, 31 new autophosphorylation sites were characterized, which in addition to the previously described sites, allowed the identification of five conserved loci. Of the 35 total sites analyzed approximately one-half were observed in the N-terminal variable domain. Homology models were generated for the protein kinase and calmodulin-like domains, each containing two of the five conserved sites, to allow intelligent speculation regarding subsequent lines of investigation.

Transcriptome changes for Arabidopsis in response to salt, osmotic, and cold stress.

To identify genes of potential importance to cold, salt, and drought tolerance, global expression profiling was performed on Arabidopsis plants subjected to stress treatments of 4 degrees C, 100 mM NaCl, or 200 mM mannitol, respectively. RNA samples were collected separately from leaves and roots after 3- and 27-h stress treatments. Profiling was conducted with a GeneChip microarray with probe sets for approximately 8,100 genes. Combined results from all three stresses identified 2,409 genes with a greater than 2-fold change over control. This suggests that about 30% of the transcriptome is sensitive to regulation by common stress conditions. The majority of changes were stimulus specific. At the 3-h time point, less than 5% (118 genes) of the changes were observed as shared by all three stress responses. By 27 h, the number of shared responses was reduced more than 10-fold (< 0.5%), consistent with a progression toward more stimulus-specific responses. Roots and leaves displayed very different changes. For example, less than 14% of the cold-specific changes were shared between root and leaves at both 3 and 27 h. The gene with the largest induction under all three stress treatments was At5g52310 (LTI/COR78), with induction levels in roots greater than 250-fold for cold, 40-fold for mannitol, and 57-fold for NaCl. A stress response was observed for 306 (68%) of the known circadian controlled genes, supporting the hypothesis that an important function of the circadian clock is to "anticipate" predictable stresses such as cold nights. Although these results identify hundreds of potentially important transcriptome changes, the biochemical functions of many stress-regulated genes remain unknown.