The PlantsP and PlantsT Functional Genomics Databases.

PlantsP and PlantsT allow users to quickly gain a global understanding of plant phosphoproteins and plant membrane transporters, respectively, from evolutionary relationships to biochemical function as well as a deep understanding of the molecular biology of individual genes and their products. As one database with two functionally different web interfaces, PlantsP and PlantsT are curated plant-specific databases that combine sequence-derived information with experimental functional-genomics data. PlantsP focuses on proteins involved in the phosphorylation process (i.e., kinases and phosphatases), whereas PlantsT focuses on membrane transport proteins. Experimentally, PlantsP provides a resource for information on a collection of T-DNA insertion mutants (knockouts) in each kinase and phosphatase, primarily in Arabidopsis thaliana, and PlantsT uniquely combines experimental data regarding mineral composition (derived from inductively coupled plasma atomic emission spectroscopy) of mutant and wild-type strains. Both databases provide extensive information on motifs and domains, detailed information contributed by individual experts in their respective fields, and descriptive information drawn directly from the literature. The databases incorporate a unique user annotation and review feature aimed at acquiring expert annotation directly from the plant biology community. PlantsP is available at http://plantsp.sdsc.edu and PlantsT is available at http://plantst.sdsc.edu.

An Atlas of the Human Kinome Reveals the Mutational Landscape Underlying Dysregulated Phosphorylation Cascades in Cancer.

Kinase inhibitors are used widely to treat various cancers, but adaptive reprogramming of kinase cascades and activation of feedback loop mechanisms often contribute to therapeutic resistance. Determining comprehensive, accurate maps of kinase circuits may therefore help elucidate mechanisms of response and resistance to kinase inhibitor therapies. In this study, we identified and validated phosphorylatable target sites across human cell and tissue types to generate PhosphoAtlas, a map of 1,733 functionally interconnected proteins comprising the human phospho-reactome. A systematic curation approach was used to distill protein phosphorylation data cross-referenced from 38 public resources. We demonstrated how a catalog of 2,617 stringently verified heptameric peptide regions at the catalytic interface of kinases and substrates could expose mutations that recurrently perturb specific phospho-hubs. In silico mapping of 2,896 nonsynonymous tumor variants identified from thousands of tumor tissues also revealed that normal and aberrant catalytic interactions co-occur frequently, showing how tumors systematically hijack, as well as spare, particular subnetworks. Overall, our work provides an important new resource for interrogating the human tumor kinome to strategically identify therapeutically actionable kinase networks that drive tumorigenesis. Cancer Res; 76(7); 1733-45. ©2016 AACR.

Development of a microarray assay that measures hybridization stoichiometry in moles.

Microarray data is most useful when it can be compared with other genetic detection technologies. In this report, we designed a microarray assay format that transforms raw data into a defined scientific unit (i.e., moles) by measuring the amount of array feature present and the cDNA sequence hybridized. This study profiles a mouse reference universal RNA sample on a microarray consisting of PCR products. In measuring array features, a labeled DNA sequence was designed that hybridizes to a conserved sequence that is present in every array feature. To measure the amount of cDNA sample hybridized, the RNA sample was processed to ensure consistent dye to DNA ratio for every labeled target cDNA molecule, using labeled branched dendrimers rather than by incorporation. A dye printing assay was then performed in order to correlate molecules of cyanine dye to signal intensity. We demonstrate that by using this microarray assay design, raw data can be transformed into defined scientific units, which will facilitate interpretation of other experiments, such as data deposited at the Gene Expression Omnibus and ArrayExpress.