Tracing the origin and evolution of pseudokinases across the tree of life.

Protein phosphorylation by eukaryotic protein kinases (ePKs) is a fundamental mechanism of cell signaling in all organisms. In model vertebrates, ~10% of ePKs are classified as pseudokinases, which have amino acid changes within the catalytic machinery of the kinase domain that distinguish them from their canonical kinase counterparts. However, pseudokinases still regulate various signaling pathways, usually doing so in the absence of their own catalytic output. To investigate the prevalence, evolutionary relationships, and biological diversity of these pseudoenzymes, we performed a comprehensive analysis of putative pseudokinase sequences in available eukaryotic, bacterial, and archaeal proteomes. We found that pseudokinases are present across all domains of life, and we classified nearly 30,000 eukaryotic, 1500 bacterial, and 20 archaeal pseudokinase sequences into 86 pseudokinase families, including ~30 families that were previously unknown. We uncovered a rich variety of pseudokinases with notable expansions not only in animals but also in plants, fungi, and bacteria, where pseudokinases have previously received cursory attention. These expansions are accompanied by domain shuffling, which suggests roles for pseudokinases in plant innate immunity, plant-fungal interactions, and bacterial signaling. Mechanistically, the ancestral kinase fold has diverged in many distinct ways through the enrichment of unique sequence motifs to generate new families of pseudokinases in which the kinase domain is repurposed for noncanonical nucleotide binding or to stabilize unique, inactive kinase conformations. We further provide a collection of annotated pseudokinase sequences in the Protein Kinase Ontology (ProKinO) as a new mineable resource for the signaling community.

GLYDE-II: The GLYcan data exchange format.

The GLYcan Data Exchange (GLYDE) standard has been developed for the representation of the chemical structures of monosaccharides, glycans and glycoconjugates using a connection table formalism formatted in XML. This format allows structures, including those that do not exist in any database, to be unambiguously represented and shared by diverse computational tools. GLYDE implements a partonomy model based on human language along with rules that provide consistent structural representations, including a robust namespace for specifying monosaccharides. This approach facilitates the reuse of data processing software at the level of granularity that is most appropriate for extraction of the desired information. GLYDE-II has already been used as a key element of several glycoinformatics tools. The philosophical and technical underpinnings of GLYDE-II and recent implementation of its enhanced features are described.

Qrator: a web-based curation tool for glycan structures.

Most currently available glycan structure databases use their own proprietary structure representation schema and contain numerous annotation errors. These cause problems when glycan databases are used for the annotation or mining of data generated in the laboratory. Due to the complexity of glycan structures, curating these databases is often a tedious and labor-intensive process. However, rigorously validating glycan structures can be made easier with a curation workflow that incorporates a structure-matching algorithm that compares candidate glycans to a canonical tree that embodies structural features consistent with established mechanisms for the biosynthesis of a particular class of glycans. To this end, we have implemented Qrator, a web-based application that uses a combination of external literature and database references, user annotations and canonical trees to assist and guide researchers in making informed decisions while curating glycans. Using this application, we have started the curation of large numbers of N-glycans, O-glycans and glycosphingolipids. Our curation workflow allows creating and extending canonical trees for these classes of glycans, which have subsequently been used to improve the curation workflow.

ProKinO: an ontology for integrative analysis of protein kinases in cancer.

BACKGROUND: Protein kinases are a large and diverse family of enzymes that are genomically altered in many human cancers. Targeted cancer genome sequencing efforts have unveiled the mutational profiles of protein kinase genes from many different cancer types. While mutational data on protein kinases is currently catalogued in various databases, integration of mutation data with other forms of data on protein kinases such as sequence, structure, function and pathway is necessary to identify and characterize key cancer causing mutations. Integrative analysis of protein kinase data, however, is a challenge because of the disparate nature of protein kinase data sources and data formats. RESULTS: Here, we describe ProKinO, a protein kinase-specific ontology, which provides a controlled vocabulary of terms, their hierarchy, and relationships unifying sequence, structure, function, mutation and pathway information on protein kinases. The conceptual representation of such diverse forms of information in one place not only allows rapid discovery of significant information related to a specific protein kinase, but also enables large-scale integrative analysis of protein kinase data in ways not possible through other kinase-specific resources. We have performed several integrative analyses of ProKinO data and, as an example, found that a large number of somatic mutations (∼288 distinct mutations) associated with the haematopoietic neoplasm cancer type map to only 8 kinases in the human kinome. This is in contrast to glioma, where the mutations are spread over 82 distinct kinases. We also provide examples of how ontology-based data analysis can be used to generate testable hypotheses regarding cancer mutations. CONCLUSION: We present an integrated framework for large-scale integrative analysis of protein kinase data. Navigation and analysis of ontology data can be performed using the ontology browser available at: http://vulcan.cs.uga.edu/prokino.

Mapping by sequencing the Pneumocystis genome using the ordering DNA sequences V3 tool.

A bioinformatics tool called ODS3 has been created for mapping by sequencing. The tool allows the creation of integrated genomic maps from genetic, physical mapping, and sequencing data and permits an integrated genome map to be stored, retrieved, viewed, and queried in a stand-alone capacity, in a client/server relationship with the Fungal Genome Database (FGDB), and as a web-browsing tool for the FGDB. In that ODS3 is programmed in Java, the tool promotes platform independence and supports export of integrated genome-mapping data in the extensible markup language (XML) for data interchange with other genome information systems. The tool ODS3 is used to create an initial integrated genome map of the AIDS-related fungal pathogen, Pneumocystis carinii. Contig dynamics would indicate that this physical map is approximately 50% complete with approximately 200 contigs. A total of 10 putative multigene families were found. Two of these putative families were previously characterized in P. carinii, namely the major surface glycoproteins (MSGs) and HSP70 proteins; three of these putative families (not previously characterized in P. carinii) were found to be similar to families encoding the HSP60 in Schizosaccharomyces pombe, the heat-shock psi protein in S. pombe, and the RNA synthetase family (i.e., MES1) in Saccharomyces cerevisiae. Physical mapping data are consistent with the 16S, 5.8S, and 26S rDNA genes being single copy in P. carinii. No other fungus outside this genus is known to have the rDNA genes in single copy.