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Wright A, Wilkinson MD, Mungall C, Cain S, Richards S, Sternberg P, Provin E, Jacobs JL, Geib S, Raciti D, Yook K, Stein L, Molik DC. FAIR Header Reference genome: a TRUSTworthy standard. Brief Bioinform 2024; 25:bbae122. [PMID: 38555475 PMCID: PMC10981671 DOI: 10.1093/bib/bbae122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 02/16/2024] [Accepted: 02/22/2024] [Indexed: 04/02/2024] Open
Abstract
The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability and Technology. The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.
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Affiliation(s)
- Adam Wright
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Mark D Wilkinson
- Departamento de Biotecnolog’ıa-Biolog’ıa Vegetal, Escuela T’ecnica Superior de Ingenier’ıa Agron’omica, Alimentaria y de Biosistemas,Centro de Biotecnolog’ıa y Gen’omica de Plantas (CBGP, UPM-INIA/CSIC), Universidad Polit’ecnica de Madrid (UPM) - Instituto Nacional de Investigaci’on y Tecnolog’ıa Agraria y Alimentaria (INIA/CSIC), Pozuelo de Alarc’on, Madrid, ES, Spain
| | - Christopher Mungall
- Biosystems Data Science, Lawrence Berkeley National Laboratory, Building: 977, 1 Cyclotron Rd, Berkeley, CA 94720, USA
| | - Scott Cain
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Stephen Richards
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, MS: BCM226, Houston, TX 77030, USA
| | - Paul Sternberg
- Division of Biology and Biological Engineering 140-18, California Institute of Technology, Pasadena, CA 91125, USA
| | - Ellen Provin
- Department of Horticultural Studies, Texas A&M University, HFSB 204, TAMU 2133, College Station, TX 77848, USA
| | - Jonathan L Jacobs
- American Type Culture Collection, 10801 University Blvd, Manassas, VA 20110, USA
| | - Scott Geib
- Tropical Pest Genetics and Molecular Biology Research Unit, Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center, United States Department of Agriculture, Agricultural Research Service, 64 Nowelo St, Hilo HI 96720, USA
| | - Daniela Raciti
- Division of Biology and Biological Engineering 140-18, California Institute of Technology, Pasadena, CA 91125, USA
| | - Karen Yook
- Division of Biology and Biological Engineering 140-18, California Institute of Technology, Pasadena, CA 91125, USA
| | - Lincoln Stein
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - David C Molik
- Arthropod-borne Animal Diseases Research Unit, Center for Grain and Animal Health Research United States Department of Agriculture, Agricultural Research Service, 1515 College Ave, Manhattan, KS 66502 USA
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Wright A, Wilkinson MD, Mungall C, Cain S, Richards S, Sternberg P, Provin E, Jacobs JL, Geib S, Raciti D, Yook K, Stein L, Molik DC. DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.569306. [PMID: 38076838 PMCID: PMC10705436 DOI: 10.1101/2023.11.29.569306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR-bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability, and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability, and Technology (TRUST). The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility, and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.
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Affiliation(s)
- Adam Wright
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Mark D Wilkinson
- Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas,Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA/CSIC), Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA/CSIC), Pozuelo de Alarcón, Madrid, ES, Spain
| | - Chris Mungall
- Biosystems Data Science, Lawrence Berkeley National Laboratory, Building: 977, 1 Cyclotron Rd, Berkeley, CA 94720 USA
| | - Scott Cain
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - Stephen Richards
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, MS: BCM226, Houston, TX 77030, USA
| | - Paul Sternberg
- Division of Biology and Biological Engineering 140-18, California Institute of Technology, Pasadena, CA 91125, USA
| | - Ellen Provin
- Department of Horticultural Studies, Texas A&M University, HFSB 204, TAMU 2133, College Station, TX 77848, USA
| | - Jonathan L Jacobs
- American Type Culture Collection, 10801 University Blvd, Manassas, VA 20110, USA
| | - Scott Geib
- Tropical Pest Genetics and Molecular Biology Research Unit, Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center, United States Department of Agriculture, Agricultural Research Service, 64 Nowelo St, Hilo HI 96720 USA
| | - Daniela Raciti
- Division of Biology and Biological Engineering 140-18, California Institute of Technology, Pasadena, CA 91125, USA
| | - Karen Yook
- Division of Biology and Biological Engineering 140-18, California Institute of Technology, Pasadena, CA 91125, USA
| | - Lincoln Stein
- Adaptive Oncology Program, Ontario Institute for Cancer Research, 661 University Avenue Suite 500, Toronto, ON M5G 0A3, Canada
| | - David C Molik
- Arthropod-borne Animal Diseases Research Unit, Center for Grain and Animal Health Research United States Department of Agriculture, Agricultural Research Service, 1515 College Ave, Manhattan, KS 66502 USA
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Schoof H, Ernst R, Mayer KFX. The PlaNet Consortium: a network of European plant databases connecting plant genome data in an integrated biological knowledge resource. Comp Funct Genomics 2011; 5:184-9. [PMID: 18629059 PMCID: PMC2447343 DOI: 10.1002/cfg.374] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2003] [Accepted: 11/24/2003] [Indexed: 11/17/2022] Open
Abstract
The completion of the Arabidopsis genome and the large collections of other plant
sequences generated in recent years have sparked extensive functional genomics
efforts. However, the utilization of this data is inefficient, as data sources are
distributed and heterogeneous and efforts at data integration are lagging behind.
PlaNet aims to overcome the limitations of individual efforts as well as the
limitations of heterogeneous, independent data collections. PlaNet is a distributed
effort among European bioinformatics groups and plant molecular biologists to
establish a comprehensive integrated database in a collaborative network. Objectives
are the implementation of infrastructure and data sources to capture plant genomic
information into a comprehensive, integrated platform. This will facilitate the
systematic exploration of Arabidopsis and other plants. New methods for data
exchange, database integration and access are being developed to create a highly
integrated, federated data resource for research. The connection between the
individual resources is realized with BioMOBY. BioMOBY provides an architecture
for the discovery and distribution of biological data through web services. While
knowledge is centralized, data is maintained at its primary source without a need for
warehousing. To standardize nomenclature and data representation, ontologies and
generic data models are defined in interaction with the relevant communities.Minimal
data models should make it simple to allow broad integration, while inheritance allows
detail and depth to be added to more complex data objects without losing integration.
To allow expert annotation and keep databases curated, local and remote annotation
interfaces are provided. Easy and direct access to all data is key to the project.
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Affiliation(s)
- H Schoof
- Technische Universität München, Chair of Genome-oriented Bioinformatics, Center of Life and Food Science, Freising-Weihenstephan D-85350, Germany.
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Böttcher C, Centeno D, Freitag J, Höfgen R, Köhl K, Kopka J, Kroymann J, Matros A, Mock HP, Neumann S, Pfalz M, von Roepenack-Lahaye E, Schauer N, Trenkamp S, Zurbriggen M, Fernie AR. Teaching (and learning from) metabolomics: the 2006 PlantMetaNet ETNA Metabolomics Research School. PHYSIOLOGIA PLANTARUM 2008; 132:136-149. [PMID: 18251856 DOI: 10.1111/j.1399-3054.2007.00990.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Under the auspices of the European Training and Networking Activity programme of the European Union, a 'Metabolic Profiling and Data Analysis' Plant Genomics and Bioinformatics Summer School was hosted in Potsdam, Germany between 20 and 29 September 2006. Sixteen early career researchers were invited from the European Union partner nations and the so-called developing nations (Appendix). Lectures from invited leading European researchers provided an overview of the state of the art of these fields and seeded discussion regarding major challenges for their future advancement. Hands-on experience was provided by an example experiment - that of defining the metabolic response of Arabidopsis to treatment of a commercial herbicide of defined mode of action. This experiment was performed throughout the duration of the course in order to teach the concepts underlying extraction and machine handling as well as to provide a rich data set with which the required computation and statistical skills could be illustrated. Here we review the state of the field by describing both key lectures given at and practical aspects taught at the summer school. In addition, we disclose results that were obtained using the four distinct technical platforms at the different participating institutes. While the effects of the chosen herbicide are well documented, this study looks at a broader number of metabolites than in previous investigations. This allowed, on the one hand, not only to characterise further effects of the herbicide than previously observed but also to detect molecules other than the herbicide that were obviously present in the commercial formulation. These data and the workshop in general are all discussed in the context of the teaching of metabolomics.
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Affiliation(s)
- Christoph Böttcher
- Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120 Halle/Saale, Germany
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Schoof H, Spannagl M, Yang L, Ernst R, Gundlach H, Haase D, Haberer G, Mayer KFX. Munich information center for protein sequences plant genome resources: a framework for integrative and comparative analyses 1(W). PLANT PHYSIOLOGY 2005; 138:1301-9. [PMID: 16010004 PMCID: PMC1176403 DOI: 10.1104/pp.104.059188] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
With several plant genomes sequenced, the power of comparative genome analysis can now be applied. However, genome-scale cross-species analyses are limited by the effort for data integration. To develop an integrated cross-species plant genome resource, we maintain comprehensive databases for model plant genomes, including Arabidopsis (Arabidopsis thaliana), maize (Zea mays), Medicago truncatula, and rice (Oryza sativa). Integration of data and resources is emphasized, both in house as well as with external partners and databases. Manual curation and state-of-the-art bioinformatic analysis are combined to achieve quality data. Easy access to the data is provided through Web interfaces and visualization tools, bulk downloads, and Web services for application-level access. This allows a consistent view of the model plant genomes for comparative and evolutionary studies, the transfer of knowledge between species, and the integration with functional genomics data.
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Affiliation(s)
- Heiko Schoof
- Technische Universität München, Chair of Genome Oriented Bioinformatics, Center of Life and Food Science, D-85354 Freising-Weihenstephan, Germany.
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Binz PA, Hermjakob H, van der Vet P. The ESF Programme on Functional Genomics Workshop on 'Data Integration in Functional Genomics: Application to Biological Pathways'. Comp Funct Genomics 2004; 5:148-55. [PMID: 18629067 PMCID: PMC2447351 DOI: 10.1002/cfg.389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
We report from the second ESF Programme on Functional Genomics workshop on Data Integration, which covered topics including the status of biological pathways databases in existing consortia; pathways as part of bioinformatics infrastructures; design, creation and formalization of biological pathways databases; generating and supporting pathway data and interoperability of databases with other external databases and standards. Key issues emerging from the discussions were the need for continued funding to cover maintenance and curation of databases, the importance of quality control of the data in these resources, and efforts to facilitate the exchange of data and to ensure the interoperability of databases.
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Affiliation(s)
- Pierre-Alain Binz
- Proteome Informatics GroupSwiss Institute of Bioinformatics 1 Michel ServetGeneva1211Switzerland,Department of Biological Sciences and BioinformaticsUniversity of GenevaGenevaSwitzerland
| | | | - Paul van der Vet
- Department of Computer ScienceUniversity of TwenteEnschedeThe Netherlands
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Schoof H, Ernst R, Nazarov V, Pfeifer L, Mewes HW, Mayer KFX. MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource for plant genomics. Nucleic Acids Res 2004; 32:D373-6. [PMID: 14681437 PMCID: PMC308802 DOI: 10.1093/nar/gkh068] [Citation(s) in RCA: 72] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2003] [Revised: 09/29/2003] [Accepted: 09/29/2003] [Indexed: 11/12/2022] Open
Abstract
Arabidopsis thaliana is the most widely studied model plant. Functional genomics is intensively underway in many laboratories worldwide. Beyond the basic annotation of the primary sequence data, the annotated genetic elements of Arabidopsis must be linked to diverse biological data and higher order information such as metabolic or regulatory pathways. The MIPS Arabidopsis thaliana database MAtDB aims to provide a comprehensive resource for Arabidopsis as a genome model that serves as a primary reference for research in plants and is suitable for transfer of knowledge to other plants, especially crops. The genome sequence as a common backbone serves as a scaffold for the integration of data, while, in a complementary effort, these data are enhanced through the application of state-of-the-art bioinformatics tools. This information is visualized on a genome-wide and a gene-by-gene basis with access both for web users and applications. This report updates the information given in a previous report and provides an outlook on further developments. The MAtDB web interface can be accessed at http://mips.gsf.de/proj/thal/db.
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Affiliation(s)
- Heiko Schoof
- Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany.
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