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      Next-generation large-scale binary protein interaction network for Drosophila melanogaster

      research-article
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      Nature Communications
      Nature Publishing Group UK
      Autophagy, Data integration, Protein-protein interaction networks

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the ‘FlyBi’ dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings ( dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

          Abstract

          Maps of protein-protein interactions (PPIs) help identify new components of pathways, complexes, and processes. In this work, state-of-the-art methods are used to identify binary Drosophila PPIs, generating broadly useful physical and data resources.

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          Most cited references84

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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                Author and article information

                Contributors
                celniker@fruitfly.org
                marc_vidal@dfci.harvard.edu
                perrimon@genetics.med.harvard.edu
                stephanie_mohr@hms.harvard.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                15 April 2023
                15 April 2023
                2023
                : 14
                : 2162
                Affiliations
                [1 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Genetics, Blavatnik Institute, , Harvard Medical School, ; 77 Avenue Louis Pasteur, Boston, MA 02115 USA
                [2 ]GRID grid.428397.3, ISNI 0000 0004 0385 0924, Program in Cancer and Stem Cell Biology, , Duke-NUS Medical School, ; 8 College Road, Singapore, 169857 Singapore
                [3 ]GRID grid.410724.4, ISNI 0000 0004 0620 9745, Division of Cellular & Molecular Research, , Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore, ; Singapore, 169610 Singapore
                [4 ]GRID grid.65499.37, ISNI 0000 0001 2106 9910, Center for Cancer Systems Biology (CCSB), , Dana-Farber Cancer Institute, ; 450 Brookline Avenue, Boston, MA 02215 USA
                [5 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Department of Physics and Astronomy, , Northwestern University, ; 633 Clark Street, Evanston, IL 60208 USA
                [6 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Northwestern Institute on Complex Systems, Chambers Hall, , Northwestern University, ; 600 Foster St, Evanston, IL 60208 USA
                [7 ]GRID grid.413575.1, ISNI 0000 0001 2167 1581, Howard Hughes Medical Institute, ; 77 Avenue Louis Pasteur, Boston, MA 02115 USA
                [8 ]GRID grid.184769.5, ISNI 0000 0001 2231 4551, Berkeley Drosophila Genome Project, , Lawrence Berkeley National Laboratory, ; 1 Cyclotron Rd, Berkeley, CA 94720 USA
                [9 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Biomedical Engineering, , Whiting School of Engineering, Johns Hopkins University, ; 3400 North Charles Street, Baltimore, MD 21218 USA
                [10 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, High-Throughput Biology Center, , Institute of Basic Biological Sciences, Johns Hopkins School of Medicine, ; 733 North Broadway, Baltimore, MD 21205 USA
                [11 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Donnelly Centre for Cellular and Biomolecular Research and Department of Molecular Genetics, , University of Toronto, ; 160 College St, Toronto, ON M5S 3E1 Canada
                [12 ]GRID grid.250674.2, ISNI 0000 0004 0626 6184, Lunenfeld-Tanenbaum Research Institute (LTRI), , Sinai Health, 600 University Ave, ; Toronto, ON M5G 1×5 Canada
                [13 ]GRID grid.11486.3a, ISNI 0000000104788040, Cytokine Receptor Lab, VIB Center for Medical Biotechnology, ; Albert Baertsoenkaai 3, 9000 Ghent, Belgium
                [14 ]GRID grid.240614.5, ISNI 0000 0001 2181 8635, Department of Cancer Genetics and Genomics, , Roswell Park Comprehensive Cancer Center, ; 665 Elm St., Buffalo, NY 14203 USA
                [15 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Computer Science, , University of Toronto, ; 40 St George St, Toronto, ON M5S 2E4 Canada
                Author information
                http://orcid.org/0000-0002-8347-9891
                http://orcid.org/0000-0002-2071-1606
                http://orcid.org/0000-0001-7908-3256
                http://orcid.org/0000-0002-6890-6277
                http://orcid.org/0000-0002-9203-1909
                http://orcid.org/0000-0002-6020-4625
                http://orcid.org/0000-0003-3347-4686
                http://orcid.org/0000-0003-2336-9225
                http://orcid.org/0000-0001-6453-0762
                http://orcid.org/0000-0002-1540-5030
                http://orcid.org/0000-0001-8415-6659
                http://orcid.org/0000-0002-6628-649X
                http://orcid.org/0000-0001-6475-1418
                http://orcid.org/0000-0001-5192-0921
                http://orcid.org/0000-0001-7542-472X
                http://orcid.org/0000-0001-9639-7708
                Article
                37876
                10.1038/s41467-023-37876-0
                10105736
                37061542
                3c28dc88-ea7b-4de5-8f6d-1819f008b0a8
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 August 2022
                : 4 April 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R01 HG007118
                Award ID: R01 AR057352
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: FundRef https://doi.org/10.13039/100000011, Howard Hughes Medical Institute (HHMI);
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                © The Author(s) 2023

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                autophagy,data integration,protein-protein interaction networks
                Uncategorized
                autophagy, data integration, protein-protein interaction networks

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