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Background: Following gene duplication, retained paralogs undergo functional divergence, which is reflected in changes in DNA sequence and expression patterns. The extent of divergence is influenced by several factors, including protein function. We examine whether an epigenetic modification, trimethylation of histone H3 at lysine 27 (H3K27me3), could be a factor in the evolution of expression patterns after gene duplication. Whereas in animals this repressive mark for transcription is deposited on long regions of DNA, in plants its localization is gene-specific. Because of this and a well-annotated recent whole-genome duplication, Arabidopsis thaliana is uniquely suited for studying the potential association of H3K27me3 with the evolutionary fate of genes., Results: Paralogous pairs with H3K27me3 show the highest coding sequence divergence, which can be explained by their low expression levels. Interestingly, they also show the highest similarity in expression patterns and upstream regulatory regions, while paralogous pairs where only one gene is an H3K27me3 target show the highest divergence in expression patterns and upstream regulatory sequence. These trends in divergence of expression and upstream regions are especially pronounced for transcription factors., Conclusions: After duplication, a histone modification can be associated with a particular fate of paralogs: H3K27me3 is linked to lower expression divergence yet higher coding sequence divergence. Our results show that H3K27me3 constrains expression divergence after duplication. Moreover, its association with higher conservation of upstream regions provides a potential mechanism for the conserved H3K27me3 targeting of the paralogs.

The four vertebrate R-spondin proteins are secreted agonists of the canonical Wnt/β-catenin signaling pathway. These proteins are approximately 35 kDa, and are characterized by two amino-terminal furin-like repeats, which are necessary and sufficient for Wnt signal potentiation, and a thrombospondin domain situated more towards the carboxyl terminus that can bind matrix glycosaminoglycans and/or proteoglycans. Although R-spondins are unable to initiate Wnt signaling, they can potently enhance responses to low-dose Wnt proteins. In humans, rare disruptions of the gene encoding R-spondin1 cause a syndrome of XX sex reversal (phenotypic male), palmoplantar keratosis (a thickening of the palms and soles caused by excess keratin formation) and predisposition to squamous cell carcinoma of the skin. Mutations in the gene encoding R-spondin4 cause anonychia (absence or hypoplasia of nails on fingers and toes). Recently, leucine-rich repeat-containing G-protein-coupled receptor (Lgr)4, Lgr5 and Lgr6, three closely related orphans of the leucine-rich repeat family of G-protein-coupled receptors, have been identified as receptors for R-spondins. Lgr5 and Lgr6 are markers for adult stem cells. Because R-spondins are potent stimulators of adult stem cell proliferation in vivo and in vitro, these findings might guide the therapeutic use of R-spondins in regenerative medicine.

Background: Reversible phosphorylation of proteins is involved in a wide range of processes, ranging from signaling cascades to regulation of protein complex assembly. Little is known about the structure and evolution of phosphorylation networks. Recent high-throughput phosphoproteomics studies have resulted in the rapid accumulation of phosphopeptide datasets for many model organisms. Here, we exploit these novel data for the comparative analysis of phosphorylation events between different species of eukaryotes., Results: Comparison of phosphoproteomics datasets of six eukaryotes yields an overlap ranging from approximately 700 sites for human and mouse (two large datasets of closely related species) to a single site for fish and yeast (distantly related as well as two of the smallest datasets). Some conserved events appear surprisingly old; those shared by plant and animals suggest conservation over the time scale of a billion years. In spite of the hypothesized incomprehensive nature of phosphoproteomics datasets and differences in experimental procedures, we show that the overlap between phosphoproteomes is greater than expected by chance and indicates increased functional relevance. Despite the dynamic nature of the evolution of phosphorylation, the relative overlap between the different datasets is identical to the phylogeny of the species studied., Conclusion: This analysis provides a framework for the generation of biological insights by comparative analysis of high-throughput phosphoproteomics datasets. We expect the rapidly growing body of data from high-throughput mass spectrometry analysis to make comparative phosphoproteomics a powerful tool for elucidating the evolutionary and functional dynamics of reversible phosphorylation.

Background: In the post-genomic era various functional genomics, proteomics and computational techniques have been developed to elucidate the protein interaction network. While some of these techniques are specific for a certain type of interaction, most predict a mixture of interactions. Qualitative labels are essential for the molecular biologist to experimentally verify predicted interactions., Results: Of the individual protein-protein interaction prediction methods, some can predict physical interactions without producing other types of interactions. None of the methods can specifically predict metabolic interactions. We have constructed an 'omics evidence landscape' that combines all sources of evidence for protein interactions from various types of omics data for Saccharomyces cerevisiae. We explore this evidence landscape to identify areas with either only metabolic or only physical interactions, allowing us to specifically predict the nature of new interactions in these areas. We combine the datasets in ways that examine the whole evidence landscape and not only the highest scoring protein pairs in both datasets and find specific predictions., Conclusion: The combination of evidence types in the form of the evidence landscape allows for qualitative labels to be inferred and placed on the predicted protein interaction network of S. cerevisiae. These qualitative labels will help in the biological interpretation of gene networks and will direct experimental verification of the predicted interactions.