Predicted Drosophila Interactome Resource and web tool for functional interpretation of differentially expressed genes

Drosophila melanogaster is a well-established model organism that is widely used in genetic studies. This species enjoys the availability of a wide range of research tools, well-annotated reference databases and highly similar gene circuitry to other insects. To facilitate molecular mechanism studies in Drosophila, we present the Predicted Drosophila Interactome Resource (PDIR), a database of high-quality predicted functional gene interactions. These interactions were inferred from evidence in 10 public databases providing information for functional gene interactions from diverse perspectives. The current version of PDIR includes 102 835 putative functional associations with balanced sensitivity and specificity, which are expected to cover 22.56% of all Drosophila protein interactions. This set of functional interactions is a good reference for hypothesis formulation in molecular mechanism studies. At the same time, these interactions also serve as a high-quality reference interactome for gene set linkage analysis (GSLA), which is a web tool for the interpretation of the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that the PDIR/GSLA system was able to produce a more comprehensive and concise interpretation of the collective functional impact of multiple simultaneously changed genes compared with the widely used gene set annotation tools, including PANTHER and David. PDIR and its associated GSLA service can be accessed at http://drosophila.biomedtzc.cn.

[1]  Xin Chen,et al.  Human interactome resource and gene set linkage analysis for the functional interpretation of biologically meaningful gene sets , 2013, Bioinform..

[2]  Kengo Kinoshita,et al.  COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference , 2018, Nucleic Acids Res..

[3]  Huan Yan,et al.  Wnt/β-catenin signaling pathway in trophoblasts and abnormal activation in preeclampsia (Review). , 2017, Molecular medicine reports.

[4]  Lixia Yao,et al.  Predicted Arabidopsis Interactome Resource and Gene Set Linkage Analysis: A Transcriptomic Analysis Resource1[OPEN] , 2018, Plant Physiology.

[5]  A. Barabasi,et al.  High-Quality Binary Protein Interaction Map of the Yeast Interactome Network , 2008, Science.

[6]  Bernardo A Mangiola,et al.  A Drosophila protein-interaction map centered on cell-cycle regulators , 2004, Genome Biology.

[7]  Hans Clevers,et al.  Wnt/β-Catenin Signaling in Development and Disease , 2006, Cell.

[8]  N. Tolwinski Introduction: Drosophila—A Model System for Developmental Biology , 2017, Journal of developmental biology.

[9]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[10]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[11]  G. Morata,et al.  Cell competition and tumorigenesis in the imaginal discs of Drosophila. , 2020, Seminars in cancer biology.

[12]  Stephen Guest,et al.  DroID 2011: a comprehensive, integrated resource for protein, transcription factor, RNA and gene interactions for Drosophila , 2010, Nucleic Acids Res..

[13]  Bonnie Berger,et al.  An integrative approach to ortholog prediction for disease-focused and other functional studies , 2011, BMC Bioinformatics.

[14]  Kara Dolinski,et al.  The BioGRID interaction database: 2019 update , 2018, Nucleic Acids Res..

[15]  Tamás Korcsmáros,et al.  ComPPI: a cellular compartment-specific database for protein–protein interaction network analysis , 2014, Nucleic Acids Res..

[16]  Silvio C. E. Tosatto,et al.  The Pfam protein families database in 2019 , 2018, Nucleic Acids Res..

[17]  Erik L. L. Sonnhammer,et al.  Inparanoid: a comprehensive database of eukaryotic orthologs , 2004, Nucleic Acids Res..

[18]  James C. Hu,et al.  The Gene Ontology Resource: 20 years and still GOing strong , 2019 .

[19]  L. Castagnoli,et al.  mentha: a resource for browsing integrated protein-interaction networks , 2013, Nature Methods.

[20]  Juancarlos Chan,et al.  Gene Ontology Consortium: going forward , 2014, Nucleic Acids Res..

[21]  Anushya Muruganujan,et al.  PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements , 2016, Nucleic Acids Res..

[22]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[23]  Minoru Kanehisa,et al.  New approach for understanding genome variations in KEGG , 2018, Nucleic Acids Res..

[24]  Ye Guang Chen,et al.  Dishevelled: The hub of Wnt signaling. , 2010, Cellular signalling.

[25]  M. Peifer,et al.  Novel roles for APC family members and Wingless/Wnt signaling during Drosophila brain development. , 2007, Developmental biology.

[26]  Bumki Min,et al.  IDDI: integrated domain-domain interaction and protein interaction analysis system , 2012, Proteome Science.

[27]  H. Clevers,et al.  Wnt signaling, stem cells, and cancer of the gastrointestinal tract. , 2012, Cold Spring Harbor Perspectives in Biology.

[28]  J. Schulz,et al.  Drosophila melanogaster as a model organism for Alzheimer’s disease , 2013, Molecular Neurodegeneration.

[29]  Damian Smedley,et al.  BioMart – biological queries made easy , 2009, BMC Genomics.

[30]  Pietro Perona,et al.  High-throughput Ethomics in Large Groups of Drosophila , 2009, Nature Methods.

[31]  Rafael C. Jimenez,et al.  The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases , 2013, Nucleic Acids Res..

[32]  Davide Heller,et al.  STRING v10: protein–protein interaction networks, integrated over the tree of life , 2014, Nucleic Acids Res..

[33]  Yanhui Hu,et al.  Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data , 2017, Nucleic Acids Res..

[34]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[35]  Giulia Antonazzo,et al.  FlyBase 2.0: the next generation , 2018, Nucleic Acids Res..

[36]  Christian Stolte,et al.  COMPARTMENTS: unification and visualization of protein subcellular localization evidence , 2014, Database J. Biol. Databases Curation.

[37]  Lanjuan Li,et al.  Quantitative evaluation of human bone mesenchymal stem cells rescuing fulminant hepatic failure in pigs , 2016, Gut.

[38]  Julia B. Cordero,et al.  Intestinal stem cell overproliferation resulting from inactivation of the APC tumor suppressor requires the transcription cofactors Earthbound and Erect wing , 2017, PLoS genetics.

[39]  Norbert Perrimon,et al.  High-throughput RNA interference screens in Drosophila tissue culture cells. , 2005, Methods in enzymology.

[40]  J Douglas Armstrong,et al.  Drosophila melanogaster--the model organism of choice for the complex biology of multi-cellular organisms. , 2005, Gravitational and space biology bulletin : publication of the American Society for Gravitational and Space Biology.

[41]  Matthew Landry,et al.  Support Vector Machine Implementations for Classification & Clustering , 2006, BMC Bioinformatics.

[42]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of human colon and rectal cancer , 2012, Nature.

[43]  J. Couso,et al.  Functions of long non-coding RNAs in human disease and their conservation in Drosophila development. , 2017, Biochemical Society transactions.

[44]  Xi He,et al.  Developmental Cell Review Wnt / b-Catenin Signaling : Components , Mechanisms , and Diseases , 2022 .