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The GABI Primary Database, GabiPD (http:// www.gabipd.org/), was established in the frame of the German initiative for Genome Analysis of the Plant Biological System (GABI). The goal of GabiPD is to collect, integrate, analyze and visualize primary information from GABI projects. GabiPD constitutes a repository and analysis platform for a wide array of heterogeneous data from high-throughput experiments in several plant species. Data from different ‘omics’ fronts are incorporated (i.e. genomics, transcriptomics, proteomics and metabolomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for textbased retrieval of all data types in GabiPD (e.g. clones, genes, mutant lines). All data types point to a central Gene GreenCard, where gene information is integrated from genome projects or NCBI UniGene sets. The centralized Gene GreenCard allows visualizing ESTs aligned to annotated transcripts as well as displaying identified protein domains and gene structure. Moreover, GabiPD makes available interactive genetic maps from potato and barley, and protein 2DE gels from Arabidopsis thaliana and Brassica napus. Gene expression and metabolic-profiling data can be visualized through MapManWeb. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of the data.
Background: Protein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites.
Results: From the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented.
These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected.
Conclusions: We analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future.
Background: Protein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites.
Results: From the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented.
These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected.
Conclusions: We analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future.
Cities and other human settlements are major contributors to climate change and are highly vulnerable to its impacts. They are also uniquely positioned to reduce greenhouse gas emissions and lead adaptation efforts. These compound challenges and opportunities require a comprehensive perspective on the public policy of human settlements. Drawing on core literature that has driven debate around cities and climate over recent decades, we put forward a set of boundary objects that can be applied to connect the knowledge of epistemic communities and support an integrated urbanism. We then use these boundary objects to develop the Goals-Intervention-Stakeholder-Enablers (GISE) framework for a public policy of human settlements that is both place-specific and provides insights and tools useful for climate action in cities and other human settlements worldwide. Using examples from Berlin, we apply this framework to show that climate mitigation and adaptation, public health, and well-being goals are closely linked and mutually supportive when a comprehensive approach to urban public policy is applied.