FlyBase 102—advanced approaches to interrogating FlyBase

FlyBase (http://flybase.org) is the leading website and database of Drosophila genes and genomes. Whether you are using the fruit fly Drosophila melanogaster as an experimental system or wish to understand Drosophila biological knowledge in relation to human disease or to other model systems, FlyBase can help you successfully find the information you are looking for. Here, we demonstrate some of our more advanced searching systems and highlight some of our new tools for searching the wealth of data on FlyBase. The first section explores gene function in FlyBase, using our TermLink tool to search with Controlled Vocabulary terms and our new RNA-Seq Search tool to search gene expression. The second section of this article describes a few ways to search genomic data in FlyBase, using our BLAST server and the new implementation of GBrowse 2, as well as our new FeatureMapper tool. Finally, we move on to discuss our most powerful search tool, QueryBuilder, before describing pre-computed cuts of the data and how to query the database programmatically

FlyExpress 7: An Integrated Discovery Platform To Study Coexpressed Genes Using in Situ Hybridization Images in Drosophila

abstract: Gene expression patterns assayed across development can offer key clues about a gene’s function and regulatory role. Drosophila melanogaster is ideal for such investigations as multiple individual and high-throughput efforts have captured the spatiotemporal patterns of thousands of embryonic expressed genes in the form of in situ images. FlyExpress (www.flyexpress.net), a knowledgebase based on a massive and unique digital library of standardized images and a simple search engine to find coexpressed genes, was created to facilitate the analytical and visual mining of these patterns. Here, we introduce the next generation of FlyExpress resources to facilitate the integrative analysis of sequence data and spatiotemporal patterns of expression from images. FlyExpress 7 now includes over 100,000 standardized in situ images and implements a more efficient, user-defined search algorithm to identify coexpressed genes via Genomewide Expression Maps (GEMs). Shared motifs found in the upstream 5′ regions of any pair of coexpressed genes can be visualized in an interactive dotplot. Additional webtools and link-outs to assist in the downstream validation of candidate motifs are also provided. Together, FlyExpress 7 represents our largest effort yet to accelerate discovery via the development and dispersal of new webtools that allow researchers to perform data-driven analyses of coexpression (image) and genomic (sequence) data.The final version of this article, as published in G3: Genes|Genomes|Genetics, can be viewed online at: http://www.g3journal.org/content/7/8/279

Exploring FlyBase Data Using QuickSearch.

FlyBase (flybase.org) is the primary online database of genetic, genomic, and functional information about Drosophila species, with a major focus on the model organism Drosophila melanogaster. The long and rich history of Drosophila research, combined with recent surges in genomic-scale and high-throughput technologies, mean that FlyBase now houses a huge quantity of data. Researchers need to be able to rapidly and intuitively query these data, and the QuickSearch tool has been designed to meet these needs. This tool is conveniently located on the FlyBase homepage and is organized into a series of simple tabbed interfaces that cover the major data and annotation classes within the database. This unit describes the functionality of all aspects of the QuickSearch tool. With this knowledge, FlyBase users will be equipped to take full advantage of all QuickSearch features and thereby gain improved access to data relevant to their research. © 2016 by John Wiley & Sons, Inc

A Genetic Screen for Mcm10: Interactions Between Mcm10 and Deficiency Regions on the Third Chromosome of Drosophila Melanogaster

Mis-regulation of the Mcm10 gene has been linked with multiple forms of cancer, including many forms of breast cancer (Thu, Y. 2014). Despite this, the role of Mcm10 in cancer is not yet fully known. One way to study a gene is to see the effects when it is no longer functioning. When eukaryotic organisms are homozygous deficient for Mcm10 they are still able to function despite the complete loss of the Mcm10 protein (Christensen, T. 2003). This suggests that there are other genes that interact with Mcm10 which are able to make up for its’ loss, allowing the organism to continue to function. The hypothesis is that by studying the interactions between Mcm10 and other genes, Mcm10’s role, and its carcinogenic effects, can be more fully understood. Genetic screening will aid in this study of Mcm10 and its interacting genes, as well as their role in cancer. We propose an enhancer/suppressor screen of the third chromosome of Drosophila melanogaster, spanning roughly 7,619 genes, to determine Mcm10’s mechanisms of interaction.B.S

Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis

Background: RNA interference (RNAi) is an effective and important tool used to study gene function. For large-scale screens, RNAi is used to systematically down-regulate genes of interest and analyze their roles in a biological process. However, RNAi is associated with off-target effects (OTEs), including microRNA (miRNA)-like OTEs. The contribution of reagent-specific OTEs to RNAi screen data sets can be significant. In addition, the post-screen validation process is time and labor intensive. Thus, the availability of robust approaches to identify candidate off-targeted transcripts would be beneficial. Results: Significant efforts have been made to eliminate false positive results attributable to sequence-specific OTEs associated with RNAi. These approaches have included improved algorithms for RNAi reagent design, incorporation of chemical modifications into siRNAs, and the use of various bioinformatics strategies to identify possible OTEs in screen results. Genome-wide Enrichment of Seed Sequence matches (GESS) was developed to identify potential off-targeted transcripts in large-scale screen data by seed-region analysis. Here, we introduce a user-friendly web application that provides researchers a relatively quick and easy way to perform GESS analysis on data from human or mouse cell-based screens using short interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), as well as for Drosophila screens using shRNAs. Online GESS relies on up-to-date transcript sequence annotations for human and mouse genes extracted from NCBI Reference Sequence (RefSeq) and Drosophila genes from FlyBase. The tool also accommodates analysis with user-provided reference sequence files. Conclusion: Online GESS provides a straightforward user interface for genome-wide seed region analysis for human, mouse and Drosophila RNAi screen data. With the tool, users can either use a built-in database or provide a database of transcripts for analysis. This makes it possible to analyze RNAi data from any organism for which the user can provide transcript sequences

Behavioral Genetics: Investigating the genes of a complex phenotype in fruit flies

Synopsis: This laboratory exercise uses both inquiry-based and active-learning approaches to uncover the genetic architecture of behavior in the model organism, Drosophila melanogaster. The exercise can be performed in either a single two-hour or two 60-minute lab periods and requires access to computers with an internet connection to help introduce students to modern genetic and genomic analysis. Students first will quantify behavioral interactions associated with mating in wildtype fruit flies. They will then connect these phenotypic ontologies to individual candidate genes using curated data from Drosophila's model organism database, FlyBase. Students will explore known characteristics of chosen candidate genes including models of genic structure, genomic context, and known functional attributes including patterns of spatial and temporal gene expression. Introduction

RNA-seq reveals post-transcriptional regulation of Drosophila insulin-like peptide dilp8 and the neuropeptide-like precursor Nplp2 by the exoribonuclease Pacman/XRN1

Ribonucleases are critically important in many cellular and developmental processes and defects in their expression are associated with human disease. Pacman/XRN1 is a highly conserved cytoplasmic exoribonuclease which degrades RNAs in a 5' - 3' direction. In Drosophila, null mutations in pacman result in small imaginal discs, a delay in onset of pupariation and lethality during the early pupal stage. In this paper, we have used RNA-seq in a genome-wide search for mRNAs misregulated in pacman null wing imaginal discs. Only 4.2% of genes are misregulated ±>2-fold in pacman null mutants compared to controls, in line with previous work showing that Pacman has specificity for particular mRNAs. Further analysis of the most upregulated mRNAs showed that Pacman post-transcriptionally regulates the expression of the secreted insulin-like peptide Dilp8. Dilp8 is related to human IGF-1, and has been shown to co-ordinate tissue growth with developmental timing in Drosophila. The increased expression of Dilp8 is consistent with the developmental delay seen in pacman null mutants. Our analysis, together with our previous results, show that the normal role of this exoribonuclease in imaginal discs is to suppress the expression of transcripts that are crucial in apoptosis and growth control during normal development