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Keränen SVE, Villahoz-Baleta A, Bruno AE, Halfon MS. REDfly: An Integrated Knowledgebase for Insect Regulatory Genomics. INSECTS 2022; 13:618. [PMID: 35886794 PMCID: PMC9323752 DOI: 10.3390/insects13070618] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 07/01/2022] [Accepted: 07/06/2022] [Indexed: 11/29/2022]
Abstract
We provide here an updated description of the REDfly (Regulatory Element Database for Fly) database of transcriptional regulatory elements, a unique resource that provides regulatory annotation for the genome of Drosophila and other insects. The genomic sequences regulating insect gene expression-transcriptional cis-regulatory modules (CRMs, e.g., "enhancers") and transcription factor binding sites (TFBSs)-are not currently curated by any other major database resources. However, knowledge of such sequences is important, as CRMs play critical roles with respect to disease as well as normal development, phenotypic variation, and evolution. Characterized CRMs also provide useful tools for both basic and applied research, including developing methods for insect control. REDfly, which is the most detailed existing platform for metazoan regulatory-element annotation, includes over 40,000 experimentally verified CRMs and TFBSs along with their DNA sequences, their associated genes, and the expression patterns they direct. Here, we briefly describe REDfly's contents and data model, with an emphasis on the new features implemented since 2020. We then provide an illustrated walk-through of several common REDfly search use cases.
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Affiliation(s)
| | - Angel Villahoz-Baleta
- Center for Computational Research, State University of New York at Buffalo, Buffalo, NY 14203, USA; (A.V.-B.); (A.E.B.)
- New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | - Andrew E. Bruno
- Center for Computational Research, State University of New York at Buffalo, Buffalo, NY 14203, USA; (A.V.-B.); (A.E.B.)
- New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | - Marc S. Halfon
- New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
- Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14203, USA
- Department of Biomedical Informatics, State University of New York at Buffalo, Buffalo, NY 14203, USA
- Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
- Department of Molecular and Cellular Biology and Program in Cancer Genetics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
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Asma H, Halfon MS. Annotating the Insect Regulatory Genome. INSECTS 2021; 12:591. [PMID: 34209769 PMCID: PMC8305585 DOI: 10.3390/insects12070591] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/23/2021] [Accepted: 06/25/2021] [Indexed: 11/17/2022]
Abstract
An ever-growing number of insect genomes is being sequenced across the evolutionary spectrum. Comprehensive annotation of not only genes but also regulatory regions is critical for reaping the full benefits of this sequencing. Driven by developments in sequencing technologies and in both empirical and computational discovery strategies, the past few decades have witnessed dramatic progress in our ability to identify cis-regulatory modules (CRMs), sequences such as enhancers that play a major role in regulating transcription. Nevertheless, providing a timely and comprehensive regulatory annotation of newly sequenced insect genomes is an ongoing challenge. We review here the methods being used to identify CRMs in both model and non-model insect species, and focus on two tools that we have developed, REDfly and SCRMshaw. These resources can be paired together in a powerful combination to facilitate insect regulatory annotation over a broad range of species, with an accuracy equal to or better than that of other state-of-the-art methods.
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Affiliation(s)
- Hasiba Asma
- Program in Genetics, Genomics, and Bioinformatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA;
| | - Marc S. Halfon
- Program in Genetics, Genomics, and Bioinformatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA;
- Department of Biochemistry, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- Department of Biomedical Informatics, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- Department of Biological Sciences, University at Buffalo-State University of New York, Buffalo, NY 14203, USA
- NY State Center of Excellence in Bioinformatics & Life Sciences, Buffalo, NY 14203, USA
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Rivera J, Keränen SVE, Gallo SM, Halfon MS. REDfly: the transcriptional regulatory element database for Drosophila. Nucleic Acids Res 2020; 47:D828-D834. [PMID: 30329093 PMCID: PMC6323911 DOI: 10.1093/nar/gky957] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 10/04/2018] [Indexed: 12/21/2022] Open
Abstract
The REDfly database provides a comprehensive curation of experimentally-validated Drosophila transcriptional cis-regulatory elements and includes information on DNA sequence, experimental evidence, patterns of regulated gene expression, and more. Now in its thirteenth year, REDfly has grown to over 23 000 records of tested reporter gene constructs and 2200 tested transcription factor binding sites. Recent developments include the start of curation of predicted cis-regulatory modules in addition to experimentally-verified ones, improved search and filtering, and increased interaction with the authors of curated papers. An expanded data model that will capture information on temporal aspects of gene regulation, regulation in response to environmental and other non-developmental cues, sexually dimorphic gene regulation, and non-endogenous (ectopic) aspects of reporter gene expression is under development and expected to be in place within the coming year. REDfly is freely accessible at http://redfly.ccr.buffalo.edu, and news about database updates and new features can be followed on Twitter at @REDfly_database.
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Affiliation(s)
- John Rivera
- Center for Computational Research, State University of New York at Buffalo, Buffalo, NY 14203, USA.,New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | | | - Steven M Gallo
- Center for Computational Research, State University of New York at Buffalo, Buffalo, NY 14203, USA.,New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | - Marc S Halfon
- New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA.,Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14203, USA.,Department of Biomedical Informatics, State University of New York at Buffalo, Buffalo, NY 14203, USA.,Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA.,Department of Molecular and Cellular Biology and Program in Cancer Genetics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
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