ABSTRACT
The FlyRNAi database at the Drosophila RNAi Screening Center and Transgenic RNAi Project (DRSC/TRiP) provides a suite of online resources that facilitate functional genomics studies with a special emphasis on Drosophila melanogaster. Currently, the database provides: gene-centric resources that facilitate ortholog mapping and mining of information about orthologs in common genetic model species; reagent-centric resources that help researchers identify RNAi and CRISPR sgRNA reagents or designs; and data-centric resources that facilitate visualization and mining of transcriptomics data, protein modification data, protein interactions, and more. Here, we discuss updated and new features that help biological and biomedical researchers efficiently identify, visualize, analyze, and integrate information and data for Drosophila and other species. Together, these resources facilitate multiple steps in functional genomics workflows, from building gene and reagent lists to management, analysis, and integration of data.
Subject(s)
Computational Biology/methods , Databases, Genetic , Drosophila melanogaster/genetics , Genome, Insect/genetics , Genomics/methods , RNA Interference , Animals , Animals, Genetically Modified , Drosophila Proteins/genetics , Gene Expression Profiling/methods , Information Storage and Retrieval , InternetABSTRACT
Metabolic flexibility of muscle tissue describes the adaptive capacity to use different energy substrates according to their availability. The disruption of this ability associates with metabolic disease. Here, using a Drosophila model of systemic metabolic dysfunction triggered by yorkie-induced gut tumors, we show that the transcription factor REPTOR is an important regulator of energy metabolism in muscles. We present evidence that REPTOR is activated in muscles of adult flies with gut yorkie-tumors, where it modulates glucose metabolism. Further, in vivo studies indicate that sustained activity of REPTOR is sufficient in wildtype muscles to repress glycolysis and increase tricarboxylic acid (TCA) cycle metabolites. Consistent with the fly studies, higher levels of CREBRF, the mammalian ortholog of REPTOR, reduce glycolysis in mouse myotubes while promoting oxidative metabolism. Altogether, our results define a conserved function for REPTOR and CREBRF as key regulators of muscle energy metabolism.
Subject(s)
Drosophila Proteins , Drosophila , Energy Metabolism , Transcription Factors , Tumor Suppressor Proteins , Animals , Mice , Citric Acid Cycle/physiology , Glycolysis , Muscles/metabolism , Neoplasms/metabolism , Tumor Suppressor Proteins/genetics , Drosophila Proteins/genetics , Transcription Factors/geneticsABSTRACT
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.
Subject(s)
Drosophila Proteins , Protein Interaction Maps , Animals , Protein Interaction Maps/genetics , Drosophila melanogaster/genetics , Drosophila melanogaster/metabolism , Drosophila/genetics , Saccharomyces cerevisiae/metabolism , Drosophila Proteins/genetics , Drosophila Proteins/metabolism , Protein Interaction Mapping/methods , Two-Hybrid System TechniquesABSTRACT
Paralogs are genes which arose via gene duplication, and when such paralogs retain overlapping or redundant function, this poses a challenge to functional genetics research. Recent technological advancements have made it possible to systematically probe gene function for redundant genes using dual or multiplex gene perturbation, and there is a need for a simple bioinformatic tool to identify putative paralogs of a gene(s) of interest. We have developed Paralog Explorer (https://www.flyrnai.org/tools/paralogs/), an online resource that allows researchers to quickly and accurately identify candidate paralogous genes in the genomes of the model organisms D. melanogaster, C. elegans, D. rerio, M. musculus, and H. sapiens. Paralog Explorer deploys an effective between-species ortholog prediction software, DIOPT, to analyze within-species paralogs. Paralog Explorer allows users to identify candidate paralogs, and to navigate relevant databases regarding gene co-expression, protein-protein and genetic interaction, as well as gene ontology and phenotype annotations. Altogether, this tool extends the value of current ortholog prediction resources by providing sophisticated features useful for identification and study of paralogous genes.
ABSTRACT
Multicellular organisms rely on cell-cell communication to exchange information necessary for developmental processes and metabolic homeostasis. Cell-cell communication pathways can be inferred from transcriptomic datasets based on ligand-receptor expression. Recently, data generated from single-cell RNA sequencing have enabled ligand-receptor interaction predictions at an unprecedented resolution. While computational methods are available to infer cell-cell communication in vertebrates such a tool does not yet exist for Drosophila. Here, we generated a high-confidence list of ligand-receptor pairs for the major fly signaling pathways and developed FlyPhoneDB, a quantification algorithm that calculates interaction scores to predict ligand-receptor interactions between cells. At the FlyPhoneDB user interface, results are presented in a variety of tabular and graphical formats to facilitate biological interpretation. To illustrate that FlyPhoneDB can effectively identify active ligands and receptors to uncover cell-cell communication events, we applied FlyPhoneDB to Drosophila single-cell RNA sequencing data sets from adult midgut, abdomen, and blood, and demonstrate that FlyPhoneDB can readily identify previously characterized cell-cell communication pathways. Altogether, FlyPhoneDB is an easy-to-use framework that can be used to predict cell-cell communication between cell types from single-cell RNA sequencing data in Drosophila.
Subject(s)
Drosophila , Single-Cell Analysis , Animals , Cell Communication/genetics , Drosophila/genetics , Internet , Ligands , Sequence Analysis, RNA/methods , Single-Cell Analysis/methods , TranscriptomeABSTRACT
Mosquito-borne diseases present a worldwide public health burden. Current efforts to understand and counteract them have been aided by the use of cultured mosquito cells. Moreover, application in mammalian cells of forward genetic approaches such as CRISPR screens have identified essential genes and genes required for host-pathogen interactions, and in general, aided in functional annotation of genes. An equivalent approach for genetic screening of mosquito cell lines has been lacking. To develop such an approach, we design a new bioinformatic portal for sgRNA library design in several mosquito genomes, engineer mosquito cell lines to express Cas9 and accept sgRNA at scale, and identify optimal promoters for sgRNA expression in several mosquito species. We then optimize a recombination-mediated cassette exchange system to deliver CRISPR sgRNA and perform pooled CRISPR screens in an Anopheles cell line. Altogether, we provide a platform for high-throughput genome-scale screening in cell lines from disease vector species.
Subject(s)
CRISPR-Cas Systems/genetics , Mosquito Control/methods , Mosquito Vectors/genetics , Pest Control, Biological/methods , Vector Borne Diseases/prevention & control , Animals , Anopheles/genetics , Cell Line , Computational Biology/methods , Gene Knockout Techniques , Gene Library , Genes, Essential , Humans , RNA, Guide, Kinetoplastida/genetics , Vector Borne Diseases/transmissionABSTRACT
With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.
ABSTRACT
CRISPR-Cas9 is a powerful genome editing technology in which a single guide RNA (sgRNA) confers target site specificity to achieve Cas9-mediated genome editing. Numerous sgRNA design tools have been developed based on reference genomes for humans and model organisms. However, existing resources are not optimal as genetic mutations or single nucleotide polymorphisms (SNPs) within the targeting region affect the efficiency of CRISPR-based approaches by interfering with guide-target complementarity. To facilitate identification of sgRNAs (1) in non-reference genomes, (2) across varying genetic backgrounds, or (3) for specific targeting of SNP-containing alleles, for example, disease relevant mutations, we developed a web tool, SNP-CRISPR (https://www.flyrnai.org/tools/snp_crispr/). SNP-CRISPR can be used to design sgRNAs based on public variant data sets or user-identified variants. In addition, the tool computes efficiency and specificity scores for sgRNA designs targeting both the variant and the reference. Moreover, SNP-CRISPR provides the option to upload multiple SNPs and target single or multiple nearby base changes simultaneously with a single sgRNA design. Given these capabilities, SNP-CRISPR has a wide range of potential research applications in model systems and for design of sgRNAs for disease-associated variant correction.
Subject(s)
Clustered Regularly Interspaced Short Palindromic Repeats , Gene Editing/methods , Polymorphism, Single Nucleotide , RNA, Guide, Kinetoplastida , Animals , Diptera , Humans , Internet , Mice , Rats , Software , ZebrafishABSTRACT
The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH term, such as a list of genes relevant to "stem cells" or "breast neoplasms." Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.
Subject(s)
Medical Subject Headings , Publications , Data Mining , Humans , Molecular Sequence Annotation , PubMedABSTRACT
The CRISPR-Cas9 system makes it possible to cause double-strand breaks in specific regions, inducing repair. In the presence of a donor construct, repair can involve insertion or 'knock-in' of an exogenous cassette. One common application of knock-in technology is to generate cell lines expressing fluorescently tagged endogenous proteins. The standard approach relies on production of a donor plasmid with â¼500 to 1000 bp of homology on either side of an insertion cassette that contains the fluorescent protein open reading frame (ORF). We present two alternative methods for knock-in of fluorescent protein ORFs into Cas9-expressing Drosophila S2R+ cultured cells, the single-stranded DNA (ssDNA) Drop-In method and the CRISPaint universal donor method. Both methods eliminate the need to clone a large plasmid donor for each target. We discuss the advantages and limitations of the standard, ssDNA Drop-In, and CRISPaint methods for fluorescent protein tagging in Drosophila cultured cells. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Knock-in into Cas9-positive S2R+ cells using the ssDNA Drop-In approach Basic Protocol 2: Knock-in into Cas9-positive S2R+ cells by homology-independent insertion of universal donor plasmids that provide mNeonGreen (CRISPaint method) Support Protocol 1: sgRNA design and cloning Support Protocol 2: ssDNA donor synthesis Support Protocol 3: Transfection using Effectene Support Protocol 4: Electroporation of S2R+-MT::Cas9 Drosophila cells Support Protocol 5: Single-cell isolation of fluorescent cells using FACS.
Subject(s)
CRISPR-Cas Systems , Drosophila/cytology , Drosophila/genetics , Gene Knock-In Techniques/methods , Genes, Insect , Green Fluorescent Proteins/genetics , Open Reading Frames , Animals , Cells, Cultured , Clustered Regularly Interspaced Short Palindromic Repeats , DNA, Single-Stranded/genetics , Gene Editing/methods , Plasmids/genetics , RNA, Guide, Kinetoplastida/genetics , TransfectionABSTRACT
High-throughput screens in Drosophila melanogaster cell lines have led to discovery of conserved gene functions related to signal transduction, host-pathogen interactions, ion transport, and more. CRISPR/Cas9 technology has opened the door to new types of large-scale cell-based screens. Whereas array-format screens require liquid handling automation and assay miniaturization, pooled-format screens, in which reagents are introduced at random and in bulk, can be done in a standard lab setting. We provide a detailed protocol for conducting and evaluating genome-wide CRISPR single guide RNA (sgRNA) pooled screens in Drosophila S2R+ cultured cells. Specifically, we provide step-by-step instructions for library design and production, optimization of cytotoxin-based selection assays, genome-scale screening, and data analysis. This type of project takes â¼3 months to complete. Results can be used in follow-up studies performed in vivo in Drosophila, mammalian cells, and/or other systems. © 2019 by John Wiley & Sons, Inc. Basic Protocol: Pooled-format screening with Cas9-expressing Drosophila S2R+ cells in the presence of cytotoxin Support Protocol 1: Optimization of cytotoxin concentration for Drosophila cell screening Support Protocol 2: CRISPR sgRNA library design and production for Drosophila cell screening Support Protocol 3: Barcode deconvolution and analysis of screening data.