Dataset Information

An online global database of Hemiptera-Phytoplasma-Plant biological interactions.

ABSTRACT: Background:Phytoplasmas are phloem-limited plant pathogenic bacteria in the class Mollicutes transmitted by sap-feeding insect vectors of the Order Hemiptera. Vectors still have not yet been identified for about half of the 33 known phytoplasma groups and this has greatly hindered efforts to control the spread of diseases affecting important crops. Extensive gaps of knowledge on actual phytoplasma vectors and on the plant disease epidemiology prevent our understanding of the basic underlying biological mechanisms that facilitate interactions between insects, phytoplasmas and their host plants. New information:This paper presents a complete online database of Hemiptera-Phytoplasma-Plant (HPP) biological interactions worldwide, searchable via an online interface. The raw data are available through Zenodo at https://doi.org/10.5281/zenodo.2532738. The online database search interface was created using the 3I software (Dmitriev 2006) which enhances data usability by providing a customised web interface (http://trivellone.speciesfile.org/) that provides an overview of the recorded biological interactions and ability to discover particular interactions by searching for one or more phytoplasma, insect or plant taxa. The database will facilitate synthesis of all available and relevant data on the observed associations between phytoplasmas and their insect and plant hosts and will provide useful data to generate and test ecological and evolutionary hypotheses.

SUBMITTER: Trivellone V

PROVIDER: S-EPMC6400871 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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An online global database of Hemiptera-Phytoplasma-Plant biological interactions.

Trivellone Valeria V

Biodiversity data journal 20190226 7

<h4>Background</h4>Phytoplasmas are phloem-limited plant pathogenic bacteria in the class Mollicutes transmitted by sap-feeding insect vectors of the Order Hemiptera. Vectors still have not yet been identified for about half of the 33 known phytoplasma groups and this has greatly hindered efforts to control the spread of diseases affecting important crops. Extensive gaps of knowledge on actual phytoplasma vectors and on the plant disease epidemiology prevent our understanding of the basic underl ...[more]

PMID: 30846902

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Project description:Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Project description:BACKGROUND: Human protein-protein interaction (PPIs) data are the foundation for understanding molecular signalling networks and the functional roles of biomolecules. Several human PPI databases have become available; however, comparisons of these datasets have suggested limited data coverage and poor data quality. Ongoing collection and integration of human PPIs from different sources, both experimentally and computationally, can enable disease-specific network biology modelling in translational bioinformatics studies. RESULTS: We developed a new web-based resource, the Human Annotated and Predicted Protein Interaction (HAPPI) database, located at http://bio.informatics.iupui.edu/HAPPI/. The HAPPI database was created by extracting and integrating publicly available protein interaction databases, including HPRD, BIND, MINT, STRING, and OPHID, using database integration techniques. We designed a unified entity-relationship data model to resolve semantic level differences of diverse concepts involved in PPI data integration. We applied a unified scoring model to give each PPI a measure of its reliability that can place each PPI at one of the five star rank levels from 1 to 5. We assessed the quality of PPIs contained in the new HAPPI database, using evolutionary conserved co-expression pairs called "MetaGene" pairs to measure the extent of MetaGene pair and PPI pair overlaps. While the overall quality of the HAPPI database across all star ranks is comparable to the overall qualities of HPRD or IntNetDB, the subset of the HAPPI database with star ranks between 3 and 5 has a much higher average quality than all other human PPI databases. As of summer 2008, the database contains 142,956 non-redundant, medium to high-confidence level human protein interaction pairs among 10,592 human proteins. The HAPPI database web application also provides ..." should be "The HAPPI database web application also provides hyperlinked information of genes, pathways, protein domains, protein structure displays, and sequence feature maps for interactive exploration of PPI data in the database. CONCLUSION: HAPPI is by far the most comprehensive public compilation of human protein interaction information. It enables its users to fully explore PPI data with quality measures and annotated information necessary for emerging network biology studies.

Dataset Information

An online global database of Hemiptera-Phytoplasma-Plant biological interactions.

Publications

An online global database of Hemiptera-Phytoplasma-Plant biological interactions.

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