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Jordão LSB, Morim MP, Baumgratz JFA, Simon MF, Eppinghaus ALC, Calfo VA. TypeTaxonScript: sugarifying and enhancing data structures in biological systematics and biodiversity research. Biol Methods Protoc 2024; 9:bpae017. [PMID: 38566774 PMCID: PMC10984730 DOI: 10.1093/biomethods/bpae017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/19/2024] [Accepted: 03/12/2024] [Indexed: 04/04/2024] Open
Abstract
Object-oriented programming (OOP) embodies a software development paradigm grounded in representing real-world entities as objects, facilitating a more efficient and structured modelling approach. In this article, we explore the synergy between OOP principles and the TypeScript (TS) programming language to create a JSON-formatted database designed for storing arrays of biological features. This fusion of technologies fosters a controlled and modular code script, streamlining the integration, manipulation, expansion, and analysis of biological data, all while enhancing syntax for improved human readability, such as through the use of dot notation. We advocate for biologists to embrace Git technology, akin to the practices of programmers and coders, for initiating versioned and collaborative projects. Leveraging the widely accessible and acclaimed IDE, Visual Studio Code, provides an additional advantage. Not only does it support running a Node.js environment, which is essential for running TS, but it also efficiently manages GitHub versioning. We provide a use case involving taxonomic data structure, focusing on angiosperm legume plants. This method is characterized by its simplicity, as the tools employed are both fully accessible and free of charge, and it is widely adopted by communities of professional programmers. Moreover, we are dedicated to facilitating practical implementation and comprehension through a comprehensive tutorial, a readily available pre-built database at GitHub, and a new package at npm.
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Affiliation(s)
- Lucas Sá Barreto Jordão
- Centro Nacional de Conservação da Flora—CNCFlora, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro, 22460-030, Brazil
| | - Marli Pires Morim
- Diretoria de Pesquisa Científica—DIPEQ, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro, 22460-030, Brazil
| | - José Fernando A Baumgratz
- Diretoria de Pesquisa Científica—DIPEQ, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro, 22460-030, Brazil
| | - Marcelo Fragomeni Simon
- Embrapa Recursos Genéticos e Biotecnologia, Parque Estação Biológica–PqEB, Brasília, 70770-901, Brazil
| | - André L C Eppinghaus
- Centro Nacional de Conservação da Flora—CNCFlora, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro, 22460-030, Brazil
| | - Vicente A Calfo
- Centro Nacional de Conservação da Flora—CNCFlora, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro, 22460-030, Brazil
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Demko V, Belova T, Messerer M, Hvidsten TR, Perroud PF, Ako AE, Johansen W, Mayer KFX, Olsen OA, Lang D. Regulation of developmental gatekeeping and cell fate transition by the calpain protease DEK1 in Physcomitrium patens. Commun Biol 2024; 7:261. [PMID: 38438476 PMCID: PMC10912778 DOI: 10.1038/s42003-024-05933-z] [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: 06/09/2023] [Accepted: 02/19/2024] [Indexed: 03/06/2024] Open
Abstract
Calpains are cysteine proteases that control cell fate transitions whose loss of function causes severe, pleiotropic phenotypes in eukaryotes. Although mainly considered as modulatory proteases, human calpain targets are directed to the N-end rule degradation pathway. Several such targets are transcription factors, hinting at a gene-regulatory role. Here, we analyze the gene-regulatory networks of the moss Physcomitrium patens and characterize the regulons that are misregulated in mutants of the calpain DEFECTIVE KERNEL1 (DEK1). Predicted cleavage patterns of the regulatory hierarchies in five DEK1-controlled subnetworks are consistent with a pleiotropic and regulatory role during cell fate transitions targeting multiple functions. Network structure suggests DEK1-gated sequential transitions between cell fates in 2D-to-3D development. Our method combines comprehensive phenotyping, transcriptomics and data science to dissect phenotypic traits, and our model explains the protease function as a switch gatekeeping cell fate transitions potentially also beyond plant development.
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Affiliation(s)
- Viktor Demko
- Department of Plant Sciences, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432, Ås, Norway
- Department of Plant Physiology, Faculty of Natural Sciences, Comenius University in Bratislava, Ilkovicova 6, 84104, Bratislava, Slovakia
- Plant Science and Biodiversity Center, Slovak Academy of Sciences, Dubravska cesta 9, 84104, Bratislava, Slovakia
| | - Tatiana Belova
- Department of Plant Sciences, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432, Ås, Norway
- Centre for Molecular Medicine Norway, University of Oslo, Oslo, Norway
| | - Maxim Messerer
- Plant Genome and Systems Biology, Helmholtz Center Munich-Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Torgeir R Hvidsten
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
| | - Pierre-François Perroud
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France
| | - Ako Eugene Ako
- Department of Biotechnology, Inland Norway University of Applied Sciences, Holsetgata 31, 2318, Hamar, Norway
- School of Animal, Rural and Environmental Sciences, Nottingham Trent University, Brackenhurst Campus, Southwell, Nottinghamshire, NG25 0QF, UK
| | - Wenche Johansen
- Department of Biotechnology, Inland Norway University of Applied Sciences, Holsetgata 31, 2318, Hamar, Norway
| | - Klaus F X Mayer
- Plant Genome and Systems Biology, Helmholtz Center Munich-Research Center for Environmental Health, 85764, Neuherberg, Germany
- School of Life Sciences, Technical University Munich, 85354, Freising, Germany
| | - Odd-Arne Olsen
- Department of Plant Sciences, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432, Ås, Norway
| | - Daniel Lang
- Plant Genome and Systems Biology, Helmholtz Center Munich-Research Center for Environmental Health, 85764, Neuherberg, Germany.
- Bundeswehr Institute of Microbiology, Microbial Genomics and Bioforensics, 80937, Munich, Germany.
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Ajike C, Enibe S, Okonkwo U, Chukwuneke J. Process modeling and simulation of Gmelina arborea (GmW) and Mansonia altissima (MaW) wood drying. Heliyon 2024; 10:e24064. [PMID: 38268592 PMCID: PMC10806297 DOI: 10.1016/j.heliyon.2024.e24064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/26/2024] Open
Abstract
This study simulate the process modeling of drying characteristics of Gmelina arborea (GmW) and Mansonia altissima (MaW) wood under the influence of various process variables such as drying time, drying temperature, and airflow velocity. GmW and MaW moisture desorption isotherms, kinetics, and thermodynamics were also studied. Five (5) thin-layer and desorption isotherm drying models were used to model the moisture ratio and water activity data from the process. According to the anatomical analysis, the GmW sample has an average lumen size of 147.44 m, indicating a high moisture content. The results showed that the Guggenheim, Anderson, and de Boer (GAB) model with the lowest sum of squared error value (0.046) demonstrated the best-fit to the experimental desorption data for GmW samples and the Henderson-P model for MaW samples, while the Demir et al. model emerged as the best kinetics model fit for describing the moisture desorption isotherm and thin-layer drying kinetics. GmW effective diffusivity (Deff) values ranged from 3.671 × 10-8 to 5.378 × 10-8 m2/s and MaW effective diffusivity (Deff) values ranged from 2.923 × 10-8 to 4.678 × 10-8 m2/s. GmW and MaW activation energies were 252.702 kJ/mol and 313.604 kJ/mol, respectively. The thermodynamic studies revealed that the heat and mass transfer coefficients varied linearly with temperature, as the change in enthalpy (ΔH) and change in entropy (ΔS) decreased while the Gibbs free energy (ΔG) increased. The results obtained from this study demonstrated that the proposed drying process modeling and simulation approach could be successfully applied to investigate the wood drying phenomena. The information can be used to reduce the drying costs and improve the wood quality.
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Affiliation(s)
- C. Ajike
- Department of Mechanical Engineering, Nnamdi Azikiwe University, Awka, Nigeria
| | - S.O. Enibe
- Department of Mechanical Engineering, Nnamdi Azikiwe University, Awka, Nigeria
| | - U.C. Okonkwo
- Department of Mechanical Engineering, Nnamdi Azikiwe University, Awka, Nigeria
| | - J.L. Chukwuneke
- Department of Mechanical Engineering, Nnamdi Azikiwe University, Awka, Nigeria
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Cooper L, Elser J, Laporte MA, Arnaud E, Jaiswal P. Planteome 2024 Update: Reference Ontologies and Knowledgebase for Plant Biology. Nucleic Acids Res 2024; 52:D1548-D1555. [PMID: 38055832 PMCID: PMC10767901 DOI: 10.1093/nar/gkad1028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/14/2023] [Accepted: 10/23/2023] [Indexed: 12/08/2023] Open
Abstract
The Planteome project (https://planteome.org/) provides a suite of reference and crop-specific ontologies and an integrated knowledgebase of plant genomics data. The plant genomics data in the Planteome has been obtained through manual and automated curation and sourced from more than 40 partner databases and resources. Here, we report on updates to the Planteome reference ontologies, namely, the Plant Ontology (PO), Trait Ontology (TO), the Plant Experimental Conditions Ontology (PECO), and integration of species/crop-specific vocabularies from our partners, the Crop Ontology (CO) into the TO ontology graph. Currently, 11 CO vocabularies are integrated into the Planteome with the addition of yam, sorghum, and potato since 2018. In addition, the size of the annotation database has increased by 34%, and the number of bioentities (genes, proteins, etc.) from 125 plant taxa has increased by 72%. We developed new tools to facilitate user requests and improvements to the CO vocabularies, and to allow fast searching and browsing of PO terms and definitions. These enhancements and future changes to automate the TO-CO mappings and knowledge discovery tools ensure that the Planteome will continue to be a valuable resource for plant biology.
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Affiliation(s)
- Laurel Cooper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | | | - Elizabeth Arnaud
- Digital Inclusion, Biodiversity International, 34397 Montpellier, France
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
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Deng CH, Naithani S, Kumari S, Cobo-Simón I, Quezada-Rodríguez EH, Skrabisova M, Gladman N, Correll MJ, Sikiru AB, Afuwape OO, Marrano A, Rebollo I, Zhang W, Jung S. Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences. Database (Oxford) 2023; 2023:baad088. [PMID: 38079567 PMCID: PMC10712715 DOI: 10.1093/database/baad088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 10/17/2023] [Accepted: 11/28/2023] [Indexed: 12/18/2023]
Abstract
Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.
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Affiliation(s)
- Cecilia H Deng
- Molecular and Digital Breeding, New Cultivar Innovation, The New Zealand Institute for Plant and Food Research Limited, 120 Mt Albert Road, Auckland 1025, New Zealand
| | - Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, New York, NY 11724, USA
| | - Irene Cobo-Simón
- Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA
- Institute of Forest Science (ICIFOR-INIA, CSIC), Madrid, Spain
| | - Elsa H Quezada-Rodríguez
- Departamento de Producción Agrícola y Animal, Universidad Autónoma Metropolitana-Xochimilco, Ciudad de México, México
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, México
| | - Maria Skrabisova
- Department of Biochemistry, Faculty of Science, Palacky University, Olomouc, Czech Republic
| | - Nick Gladman
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, New York, NY 11724, USA
- U.S. Department of Agriculture-Agricultural Research Service, NEA Robert W. Holley Center for Agriculture and Health, Cornell University, Ithaca, NY 14853, USA
| | - Melanie J Correll
- Agricultural and Biological Engineering Department, University of Florida, 1741 Museum Rd, Gainesville, FL 32611, USA
| | | | | | - Annarita Marrano
- Phoenix Bioinformatics, 39899 Balentine Drive, Suite 200, Newark, CA 94560, USA
| | | | - Wentao Zhang
- National Research Council Canada, 110 Gymnasium Pl, Saskatoon, Saskatchewan S7N 0W9, Canada
| | - Sook Jung
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
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6
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Dumschott K, Dörpholz H, Laporte MA, Brilhaus D, Schrader A, Usadel B, Neumann S, Arnaud E, Kranz A. Ontologies for increasing the FAIRness of plant research data. FRONTIERS IN PLANT SCIENCE 2023; 14:1279694. [PMID: 38098789 PMCID: PMC10720748 DOI: 10.3389/fpls.2023.1279694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/15/2023] [Indexed: 12/17/2023]
Abstract
The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data increases the likelihood of reuse, and the potential of answering novel research questions. Ontologies are a useful tool for semantically tagging datasets as adding relevant metadata increases the understanding of how data was produced and increases its interoperability. Ontologies provide concepts for a particular domain as well as the relationships between concepts. By tagging data with ontology terms, data becomes both human- and machine- interpretable, allowing for increased reuse and interoperability. However, the task of identifying ontologies relevant to a particular research domain or technology is challenging, especially within the diverse realm of fundamental plant research. In this review, we outline the ontologies most relevant to the fundamental plant sciences and how they can be used to annotate data related to plant-specific experiments within metadata frameworks, such as Investigation-Study-Assay (ISA). We also outline repositories and platforms most useful for identifying applicable ontologies or finding ontology terms.
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Affiliation(s)
- Kathryn Dumschott
- Institute of Bio- and Geosciences (IBG-4: Bioinformatics) & Bioeconomy Science Center (BioSC), CEPLAS, Forschungszentrum Jülich, Jülich, Germany
| | - Hannah Dörpholz
- Institute of Bio- and Geosciences (IBG-4: Bioinformatics) & Bioeconomy Science Center (BioSC), CEPLAS, Forschungszentrum Jülich, Jülich, Germany
| | - Marie-Angélique Laporte
- Digital Solutions Team, Digital Inclusion Lever, Bioversity International, Montpellier Office, Montpellier, France
| | - Dominik Brilhaus
- Data Science and Management & Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andrea Schrader
- Data Science and Management & Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, Cologne, Germany
| | - Björn Usadel
- Institute of Bio- and Geosciences (IBG-4: Bioinformatics) & Bioeconomy Science Center (BioSC), CEPLAS, Forschungszentrum Jülich, Jülich, Germany
- Institute for Biological Data Science & Cluster of Excellence on Plant Sciences (CEPLAS), Faculty of Mathematics and Life Sciences, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Steffen Neumann
- Program Center MetaCom, Leibniz Institute of Plant Biochemistry, Halle, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
| | - Elizabeth Arnaud
- Digital Solutions Team, Digital Inclusion Lever, Bioversity International, Montpellier Office, Montpellier, France
| | - Angela Kranz
- Institute of Bio- and Geosciences (IBG-4: Bioinformatics) & Bioeconomy Science Center (BioSC), CEPLAS, Forschungszentrum Jülich, Jülich, Germany
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Clarke JL, Cooper LD, Poelchau MF, Berardini TZ, Elser J, Farmer AD, Ficklin S, Kumari S, Laporte MA, Nelson RT, Sadohara R, Selby P, Thessen AE, Whitehead B, Sen TZ. Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the Agbiodata Consortium. Database (Oxford) 2023; 2023:baad076. [PMID: 37971715 PMCID: PMC10653126 DOI: 10.1093/database/baad076] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/17/2023] [Indexed: 11/19/2023]
Abstract
Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, respectively, conducted a Consortium-wide survey to assess the current status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data-sharing practices by AgBioData databases are in a fairly healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that, ontology use has not substantially changed since a similar survey was conducted in 2017. Based on our evaluation of the survey results, we recommend (i) providing training for database personnel in a specific data-sharing techniques, as well as in ontology use; (ii) further study on what metadata is shared, and how well it is shared among databases; (iii) promoting an understanding of data sharing and ontologies in the stakeholder community; (iv) improving data sharing and ontologies for specific phenotypic data types and formats; and (v) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means. Database URL https://www.agbiodata.org/databases.
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Affiliation(s)
- Jennifer L Clarke
- Department of Statistics and Department of Food Science and Technology, University of Nebraska–Lincoln, 340 Hardin Hall North Wing, Lincoln, NE 68583, USA
| | - Laurel D Cooper
- Department of Botany and Plant Pathology, Oregon State University, 2503 Cordley Hall, Corvallis, OR 97331, USA
| | - Monica F Poelchau
- USDA, Agricultural Research Service, National Agricultural Library, 10301 Baltimore Ave, Beltsville 20705, USA
| | - Tanya Z Berardini
- The Arabidopsis Information Resource and Phoenix Bioinformatic, 39899 Balentine Drive, Suite 200, Newark, CA, USA
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, 2503 Cordley Hall, Corvallis, OR 97331, USA
| | - Andrew D Farmer
- National Center for Genome Resources, 2935 Rodeo Park Dr. E., Santa Fe, NM 87505, USA
| | - Stephen Ficklin
- Department of Horticulture, Washington State University, 249 Clark Hall, PO Box 646414, Pullman, WA 99164, USA
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY 11724, USA
| | - Marie-Angélique Laporte
- Digital Inclusion, Bioversity International, Parc Scientifique Agropolis II, 1990 Bd de la Lironde, Montpellier 34397, France
| | - Rex T Nelson
- USDA, Agricultural Research Service, Corn Insects and Crop Genetics Research Unit, Iowa State University, 716 Farmhouse Lane, Ames, IA 50011, USA
| | - Rie Sadohara
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, 1066 Bogue St, East Lansing, MI 48824, USA
| | - Peter Selby
- School of Integrative Plant Science, College of Agriculture and Life Sciences, Cornell University, 215 Garden Avenue, Ithaca, NY 14850, USA
| | - Anne E Thessen
- Department of Biomedical Informatics, University of Colorado Anschutz, 1890 N. Revere Court, Mailstop F600, Aurora CO 80045, USA
| | - Brandon Whitehead
- Data Science and Informatics, Manaaki Whenua—Landcare Research, Ltd., Riddet Road, Massey University, Palmerston North 4472, New Zealand
| | - Taner Z Sen
- USDA, Agricultural Research Service, Crop Improvement Genetics Research Unit, Western Regional Research Center, 800 Buchanan St, Albany 94710, USA
- Department of Bioengineering, University of California, 306 Stanley Hall, Berkeley, CA 94720, USA
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8
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Ayllón-Benitez A, Bernabé-Diaz JA, Espinoza-Arias P, Esnaola-Gonzalez I, Beeckman DSA, McCaig B, Hanzlik K, Cools T, Castro Iragorri C, Palacios N. EPPO ontology: a semantic-driven approach for plant and pest codes representation. Front Artif Intell 2023; 6:1131667. [PMID: 37404339 PMCID: PMC10315572 DOI: 10.3389/frai.2023.1131667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Accepted: 05/26/2023] [Indexed: 07/06/2023] Open
Abstract
The agricultural industry and regulatory organizations define strategies and build tools and products for plant protection against pests. To identify different plants and their related pests and avoid inconsistencies between such organizations, an agreed and shared classification is necessary. In this regard, the European and Mediterranean Plant Protection Organization (EPPO) has been working on defining and maintaining a harmonized coding system (EPPO codes). EPPO codes are an easy way of referring to a specific organism by means of short 5 or 6 letter codes instead of long scientific names or ambiguous common names. EPPO codes are freely available in different formats through the EPPO Global Database platform and are implemented as a worldwide standard and used among scientists and experts in both industry and regulatory organizations. One of the large companies that adopted such codes is BASF, which uses them mainly in research and development to build their crop protection and seeds products. However, extracting the information is limited by fixed API calls or files that require additional processing steps. Facing these issues makes it difficult to use the available information flexibly, infer new data connections, or enrich it with external data sources. To overcome such limitations, BASF has developed an internal EPPO ontology to represent the list of codes provided by the EPPO Global Database as well as the regulatory categorization and relationship among them. This paper presents the development process of this ontology along with its enrichment process, which allows the reuse of relevant information available in an external knowledge source such as the NCBI Taxon. In addition, this paper describes the use and adoption of the EPPO ontology within the BASF's Agricultural Solutions division and the lessons learned during this work.
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Affiliation(s)
| | | | | | | | | | | | - Kristin Hanzlik
- BASF SE Data Management and Data Governance, Global Research Services APR/HP, Limburgerhof, Germany
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9
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Karabulut E, Erkoç K, Acı M, Aydın M, Barriball S, Braley J, Cassetta E, Craine EB, Diaz-Garcia L, Hershberger J, Meyering B, Miller AJ, Rubin MJ, Tesdell O, Schlautman B, Şakiroğlu M. Sainfoin ( Onobrychis spp.) crop ontology: supporting germplasm characterization and international research collaborations. FRONTIERS IN PLANT SCIENCE 2023; 14:1177406. [PMID: 37255566 PMCID: PMC10225502 DOI: 10.3389/fpls.2023.1177406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 04/18/2023] [Indexed: 06/01/2023]
Abstract
Sainfoin (Onobrychis spp.) is a perennial forage legume that is also attracting attention as a perennial pulse with potential for human consumption. The dual use of sainfoin underpins diverse research and breeding programs focused on improving sainfoin lines for forage and pulses, which is driving the generation of complex datasets describing high dimensional phenotypes in the post-omics era. To ensure that multiple user groups, for example, breeders selecting for forage and those selecting for edible seed, can utilize these rich datasets, it is necessary to develop common ontologies and accessible ontology platforms. One such platform, Crop Ontology, was created in 2008 by the Consortium of International Agricultural Research Centers (CGIAR) to host crop-specific trait ontologies that support standardized plant breeding databases. In the present study, we describe the sainfoin crop ontology (CO). An in-depth literature review was performed to develop a comprehensive list of traits measured and reported in sainfoin. Because the same traits can be measured in different ways, ultimately, a set of 98 variables (variable = plant trait + method of measurement + scale of measurement) used to describe variation in sainfoin were identified. Variables were formatted and standardized based on guidelines provided here for inclusion in the sainfoin CO. The 98 variables contained a total of 82 traits from four trait classes of which 24 were agronomic, 31 were morphological, 19 were seed and forage quality related, and 8 were phenological. In addition to the developed variables, we have provided a roadmap for developing and submission of new traits to the sainfoin CO.
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Affiliation(s)
- Ebrar Karabulut
- Bioengineering Department, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye
| | - Kübra Erkoç
- Bioengineering Department, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye
| | - Murat Acı
- Bioengineering Department, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye
- The Land Institute, Salina, KS, United States
| | - Mahmut Aydın
- Department of Computer Engineering, Kafkas University, Kars, Türkiye
| | | | - Jackson Braley
- Donald Danforth Plant Science Center, St. Louis, MO, United States
| | | | | | - Luis Diaz-Garcia
- Department of Viticulture and Enology, University of California Davis, Davis, CA, United States
| | - Jenna Hershberger
- Plant and Environmental Sciences Department, Clemson University, Clemson, SC, United States
| | - Bo Meyering
- The Land Institute, Salina, KS, United States
| | - Allison J. Miller
- Donald Danforth Plant Science Center, St. Louis, MO, United States
- Department. of Biology, Saint Louis University, St. Louis, MO, United States
| | - Matthew J. Rubin
- Donald Danforth Plant Science Center, St. Louis, MO, United States
| | - Omar Tesdell
- Department of Geography, Birzeit University, Birzeit, West Bank, Palestine
| | | | - Muhammet Şakiroğlu
- Bioengineering Department, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye
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10
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Fahlgren N, Kapoor M, Yordanova G, Papatheodorou I, Waese J, Cole B, Harrison P, Ware D, Tickle T, Paten B, Burdett T, Elsik CG, Tuggle CK, Provart NJ. Toward a data infrastructure for the Plant Cell Atlas. PLANT PHYSIOLOGY 2023; 191:35-46. [PMID: 36200899 PMCID: PMC9806565 DOI: 10.1093/plphys/kiac468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/18/2022] [Indexed: 06/16/2023]
Abstract
We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment. We imagine how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades, as long as such data are made accessible to the community in an open manner.
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Affiliation(s)
- Noah Fahlgren
- Donald Danforth Plant Science Center, Saint Louis, Missouri 63132, USA
| | - Muskan Kapoor
- Bioinformatics and Computational Biology Program, Department of Animal Science, Iowa State University, Ames, Iowa 50011, USA
| | | | | | - Jamie Waese
- Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario M5S 3B2, Canada
| | - Benjamin Cole
- DOE-Joint Genome Institute, Lawrence Berkeley National Laboratory, 1, Cyclotron Road, Berkeley, California 94720, USA
| | - Peter Harrison
- EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Doreen Ware
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
- USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853, USA
| | - Timothy Tickle
- Data Sciences Platform, The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, Massachusetts 02142, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, Baskin School of Engineering, 1156 High Street, Santa Cruz, California 95064, USA
| | - Tony Burdett
- EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Christine G Elsik
- Division of Animal Sciences/Division of Plant Science & Technology/Institute for Data Science & Informatics, University of Missouri, Columbia, Missouri 65211, USA
| | - Christopher K Tuggle
- Bioinformatics and Computational Biology Program, Department of Animal Science, Iowa State University, Ames, Iowa 50011, USA
| | - Nicholas J Provart
- Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario M5S 3B2, Canada
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11
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Redsun S, Hokin S, Cameron CT, Cleary AM, Berendzen J, Dash S, Brown AV, Wilkey A, Campbell JD, Huang W, Kalberer SR, Weeks NT, Cannon SB, Farmer AD. Doing Genetic and Genomic Biology Using the Legume Information System and Associated Resources. Methods Mol Biol 2022; 2443:81-100. [PMID: 35037201 DOI: 10.1007/978-1-0716-2067-0_4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In this chapter, we introduce the main components of the Legume Information System ( https://legumeinfo.org ) and several associated resources. Additionally, we provide an example of their use by exploring a biological question: is there a common molecular basis, across legume species, that underlies the photoperiod-mediated transition from vegetative to reproductive development, that is, days to flowering? The Legume Information System (LIS) holds genetic and genomic data for a large number of crop and model legumes and provides a set of online bioinformatic tools designed to help biologists address questions and tasks related to legume biology. Such tasks include identifying the molecular basis of agronomic traits; identifying orthologs/syntelogs for known genes; determining gene expression patterns; accessing genomic datasets; identifying markers for breeding work; and identifying genetic similarities and differences among selected accessions. LIS integrates with other legume-focused informatics resources such as SoyBase ( https://soybase.org ), PeanutBase ( https://peanutbase.org ), and projects of the Legume Federation ( https://legumefederation.org ).
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Affiliation(s)
- Sven Redsun
- National Center for Genome Resources, Santa Fe, NM, USA
| | - Sam Hokin
- National Center for Genome Resources, Santa Fe, NM, USA
| | | | - Alan M Cleary
- National Center for Genome Resources, Santa Fe, NM, USA
| | | | - Sudhansu Dash
- National Center for Genome Resources, Santa Fe, NM, USA
| | - Anne V Brown
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Andrew Wilkey
- ORISE, Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Jacqueline D Campbell
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
- Department of Computer Science, Iowa State University, Ames, IA, USA
| | - Wei Huang
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Scott R Kalberer
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Nathan T Weeks
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Steven B Cannon
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA.
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12
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Larmande P, Tagny Ngompe G, Venkatesan A, Ruiz M. AgroLD: A Knowledge Graph Database for Plant Functional Genomics. Methods Mol Biol 2022; 2443:527-540. [PMID: 35037225 DOI: 10.1007/978-1-0716-2067-0_28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Recent advances in high-throughput technologies have resulted in tremendous increase in the amount of data in the agronomic domain. There is an urgent need to effectively integrate complementary information to understand the biological system in its entirety. We have developed AgroLD, a knowledge graph that exploits the Semantic Web technology and some of the relevant standard domain ontologies, to integrate information on plant species and in this way facilitating the formulation of new scientific hypotheses. This chapter outlines some integration results of the project, which initially focused on genomics, proteomics and phenomics.
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Affiliation(s)
- Pierre Larmande
- DIADE, IRD, CIRAD, Univ. Montpellier, Montpellier, France.
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, France.
| | - Gildas Tagny Ngompe
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, France
- AGAP, CIRAD, INRAE, Univ. Montpellier, av Agropolis, Montpellier, France
| | | | - Manuel Ruiz
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, France
- AGAP, CIRAD, INRAE, Univ. Montpellier, av Agropolis, Montpellier, France
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13
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Cainelli N, Forestan C, Angeli D, Villegas TR, Costa F, Botton A, Rasori A, Bonghi C, Ruperti B. Transcriptomic Insights on the Preventive Action of Apple (cv Granny Smith) Skin Wounding on Superficial Scald Development. Int J Mol Sci 2021; 22:ijms222413425. [PMID: 34948219 PMCID: PMC8705499 DOI: 10.3390/ijms222413425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/03/2022] Open
Abstract
Superficial scald is a post-harvest chilling storage injury leading to browning of the surface of the susceptible cv Granny Smith apples. Wounding of skins has been reported to play a preventive role on scald development however its underlying molecular factors are unknown. We have artificially wounded the epidermal and sub-epidermal layers of apple skins consistently obtaining the prevention of superficial scald in the surroundings of the wounds during two independent vintages. Time course RNA-Seq analyses of the transcriptional changes in wounded versus unwounded skins revealed that two transcriptional waves occurred. An early wave included genes up-regulated by wounding already after 6 h, highlighting a specific transcriptional rearrangement of genes connected to the biosynthesis and signalling of JA, ethylene and ABA. A later transcriptional wave, occurring after three months of cold storage, included genes up-regulated exclusively in unwounded skins and was prevented from its occurrence in wounded skins. A significant portion of these genes was related to decay of tissues and to the senescence hormones ABA, JA and ethylene. Such changes suggest a wound-inducible reversed hormonal balance during post-harvest storage which may explain the local inhibition of scald in wounded tissues, an aspect that will need further studies for its mechanistic explanation.
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Affiliation(s)
- Nadia Cainelli
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, Università di Padova, 35122 Legnaro, PD, Italy; (N.C.); (A.B.); (A.R.); (C.B.)
| | - Cristian Forestan
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Università di Bologna, 40127 Bologna, BO, Italy;
| | - Dario Angeli
- Fondazione Edmund Mach, Centro di Trasferimento Tecnologico, 38010 San Michele all’Adige, TN, Italy; (D.A.); (T.R.V.)
| | - Tomas Roman Villegas
- Fondazione Edmund Mach, Centro di Trasferimento Tecnologico, 38010 San Michele all’Adige, TN, Italy; (D.A.); (T.R.V.)
| | - Fabrizio Costa
- Centro Agricoltura Alimenti Ambiente, 38098 San Michele all’Adige, TN, Italy;
| | - Alessandro Botton
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, Università di Padova, 35122 Legnaro, PD, Italy; (N.C.); (A.B.); (A.R.); (C.B.)
| | - Angela Rasori
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, Università di Padova, 35122 Legnaro, PD, Italy; (N.C.); (A.B.); (A.R.); (C.B.)
| | - Claudio Bonghi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, Università di Padova, 35122 Legnaro, PD, Italy; (N.C.); (A.B.); (A.R.); (C.B.)
| | - Benedetto Ruperti
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, Università di Padova, 35122 Legnaro, PD, Italy; (N.C.); (A.B.); (A.R.); (C.B.)
- Correspondence:
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14
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Freschet GT, Pagès L, Iversen CM, Comas LH, Rewald B, Roumet C, Klimešová J, Zadworny M, Poorter H, Postma JA, Adams TS, Bagniewska‐Zadworna A, Bengough AG, Blancaflor EB, Brunner I, Cornelissen JHC, Garnier E, Gessler A, Hobbie SE, Meier IC, Mommer L, Picon‐Cochard C, Rose L, Ryser P, Scherer‐Lorenzen M, Soudzilovskaia NA, Stokes A, Sun T, Valverde‐Barrantes OJ, Weemstra M, Weigelt A, Wurzburger N, York LM, Batterman SA, Gomes de Moraes M, Janeček Š, Lambers H, Salmon V, Tharayil N, McCormack ML. A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements. THE NEW PHYTOLOGIST 2021; 232:973-1122. [PMID: 34608637 PMCID: PMC8518129 DOI: 10.1111/nph.17572] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 03/22/2021] [Indexed: 05/17/2023]
Abstract
In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.
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Affiliation(s)
- Grégoire T. Freschet
- CEFEUniv Montpellier, CNRS, EPHE, IRD1919 route de MendeMontpellier34293France
- Station d’Ecologie Théorique et ExpérimentaleCNRS2 route du CNRS09200MoulisFrance
| | - Loïc Pagès
- UR 1115 PSHCentre PACA, site AgroparcINRAE84914Avignon cedex 9France
| | - Colleen M. Iversen
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTN37831USA
| | - Louise H. Comas
- USDA‐ARS Water Management Research Unit2150 Centre Avenue, Bldg D, Suite 320Fort CollinsCO80526USA
| | - Boris Rewald
- Department of Forest and Soil SciencesUniversity of Natural Resources and Life SciencesVienna1190Austria
| | - Catherine Roumet
- CEFEUniv Montpellier, CNRS, EPHE, IRD1919 route de MendeMontpellier34293France
| | - Jitka Klimešová
- Department of Functional EcologyInstitute of Botany CASDukelska 13537901TrebonCzech Republic
| | - Marcin Zadworny
- Institute of DendrologyPolish Academy of SciencesParkowa 562‐035KórnikPoland
| | - Hendrik Poorter
- Plant Sciences (IBG‐2)Forschungszentrum Jülich GmbHD‐52425JülichGermany
- Department of Biological SciencesMacquarie UniversityNorth RydeNSW2109Australia
| | | | - Thomas S. Adams
- Department of Plant SciencesThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Agnieszka Bagniewska‐Zadworna
- Department of General BotanyInstitute of Experimental BiologyFaculty of BiologyAdam Mickiewicz UniversityUniwersytetu Poznańskiego 661-614PoznańPoland
| | - A. Glyn Bengough
- The James Hutton InstituteInvergowrie, Dundee,DD2 5DAUK
- School of Science and EngineeringUniversity of DundeeDundee,DD1 4HNUK
| | | | - Ivano Brunner
- Forest Soils and BiogeochemistrySwiss Federal Research Institute WSLZürcherstr. 1118903BirmensdorfSwitzerland
| | - Johannes H. C. Cornelissen
- Department of Ecological ScienceFaculty of ScienceVrije Universiteit AmsterdamDe Boelelaan 1085Amsterdam1081 HVthe Netherlands
| | - Eric Garnier
- CEFEUniv Montpellier, CNRS, EPHE, IRD1919 route de MendeMontpellier34293France
| | - Arthur Gessler
- Forest DynamicsSwiss Federal Research Institute WSLZürcherstr. 1118903BirmensdorfSwitzerland
- Institute of Terrestrial EcosystemsETH Zurich8092ZurichSwitzerland
| | - Sarah E. Hobbie
- Department of Ecology, Evolution and BehaviorUniversity of MinnesotaSt PaulMN55108USA
| | - Ina C. Meier
- Functional Forest EcologyUniversity of HamburgHaidkrugsweg 122885BarsbütelGermany
| | - Liesje Mommer
- Plant Ecology and Nature Conservation GroupDepartment of Environmental SciencesWageningen University and ResearchPO Box 476700 AAWageningenthe Netherlands
| | | | - Laura Rose
- Station d’Ecologie Théorique et ExpérimentaleCNRS2 route du CNRS09200MoulisFrance
- Senckenberg Biodiversity and Climate Research Centre (BiK-F)Senckenberganlage 2560325Frankfurt am MainGermany
| | - Peter Ryser
- Laurentian University935 Ramsey Lake RoadSudburyONP3E 2C6Canada
| | | | - Nadejda A. Soudzilovskaia
- Environmental Biology DepartmentInstitute of Environmental SciencesCMLLeiden UniversityLeiden2300 RAthe Netherlands
| | - Alexia Stokes
- INRAEAMAPCIRAD, IRDCNRSUniversity of MontpellierMontpellier34000France
| | - Tao Sun
- Institute of Applied EcologyChinese Academy of SciencesShenyang110016China
| | - Oscar J. Valverde‐Barrantes
- International Center for Tropical BotanyDepartment of Biological SciencesFlorida International UniversityMiamiFL33199USA
| | - Monique Weemstra
- CEFEUniv Montpellier, CNRS, EPHE, IRD1919 route de MendeMontpellier34293France
| | - Alexandra Weigelt
- Systematic Botany and Functional BiodiversityInstitute of BiologyLeipzig UniversityJohannisallee 21-23Leipzig04103Germany
| | - Nina Wurzburger
- Odum School of EcologyUniversity of Georgia140 E. Green StreetAthensGA30602USA
| | - Larry M. York
- Biosciences Division and Center for Bioenergy InnovationOak Ridge National LaboratoryOak RidgeTN37831USA
| | - Sarah A. Batterman
- School of Geography and Priestley International Centre for ClimateUniversity of LeedsLeedsLS2 9JTUK
- Cary Institute of Ecosystem StudiesMillbrookNY12545USA
| | - Moemy Gomes de Moraes
- Department of BotanyInstitute of Biological SciencesFederal University of Goiás1974690-900Goiânia, GoiásBrazil
| | - Štěpán Janeček
- School of Biological SciencesThe University of Western Australia35 Stirling HighwayCrawley (Perth)WA 6009Australia
| | - Hans Lambers
- School of Biological SciencesThe University of Western AustraliaCrawley (Perth)WAAustralia
| | - Verity Salmon
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTN37831USA
| | - Nishanth Tharayil
- Department of Plant and Environmental SciencesClemson UniversityClemsonSC29634USA
| | - M. Luke McCormack
- Center for Tree ScienceMorton Arboretum, 4100 Illinois Rt. 53LisleIL60532USA
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15
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Freschet GT, Pagès L, Iversen CM, Comas LH, Rewald B, Roumet C, Klimešová J, Zadworny M, Poorter H, Postma JA, Adams TS, Bagniewska-Zadworna A, Bengough AG, Blancaflor EB, Brunner I, Cornelissen JHC, Garnier E, Gessler A, Hobbie SE, Meier IC, Mommer L, Picon-Cochard C, Rose L, Ryser P, Scherer-Lorenzen M, Soudzilovskaia NA, Stokes A, Sun T, Valverde-Barrantes OJ, Weemstra M, Weigelt A, Wurzburger N, York LM, Batterman SA, Gomes de Moraes M, Janeček Š, Lambers H, Salmon V, Tharayil N, McCormack ML. A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements. THE NEW PHYTOLOGIST 2021. [PMID: 34608637 DOI: 10.1111/nph.17572.hal-03379708] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.
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Affiliation(s)
- Grégoire T Freschet
- CEFE, Univ Montpellier, CNRS, EPHE, IRD, 1919 route de Mende, Montpellier, 34293, France
- Station d'Ecologie Théorique et Expérimentale, CNRS, 2 route du CNRS, 09200, Moulis, France
| | - Loïc Pagès
- UR 1115 PSH, Centre PACA, site Agroparc, INRAE, 84914, Avignon cedex 9, France
| | - Colleen M Iversen
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Louise H Comas
- USDA-ARS Water Management Research Unit, 2150 Centre Avenue, Bldg D, Suite 320, Fort Collins, CO, 80526, USA
| | - Boris Rewald
- Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences, Vienna, 1190, Austria
| | - Catherine Roumet
- CEFE, Univ Montpellier, CNRS, EPHE, IRD, 1919 route de Mende, Montpellier, 34293, France
| | - Jitka Klimešová
- Department of Functional Ecology, Institute of Botany CAS, Dukelska 135, 37901, Trebon, Czech Republic
| | - Marcin Zadworny
- Institute of Dendrology, Polish Academy of Sciences, Parkowa 5, 62-035, Kórnik, Poland
| | - Hendrik Poorter
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany
- Department of Biological Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
| | - Johannes A Postma
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany
| | - Thomas S Adams
- Department of Plant Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Agnieszka Bagniewska-Zadworna
- Department of General Botany, Institute of Experimental Biology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznańskiego 6, 61-614, Poznań, Poland
| | - A Glyn Bengough
- The James Hutton Institute, Invergowrie, Dundee,, DD2 5DA, UK
- School of Science and Engineering, University of Dundee, Dundee,, DD1 4HN, UK
| | - Elison B Blancaflor
- Noble Research Institute, LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Ivano Brunner
- Forest Soils and Biogeochemistry, Swiss Federal Research Institute WSL, Zürcherstr. 111, 8903, Birmensdorf, Switzerland
| | - Johannes H C Cornelissen
- Department of Ecological Science, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Eric Garnier
- CEFE, Univ Montpellier, CNRS, EPHE, IRD, 1919 route de Mende, Montpellier, 34293, France
| | - Arthur Gessler
- Forest Dynamics, Swiss Federal Research Institute WSL, Zürcherstr. 111, 8903, Birmensdorf, Switzerland
- Institute of Terrestrial Ecosystems, ETH Zurich, 8092, Zurich, Switzerland
| | - Sarah E Hobbie
- Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN, 55108, USA
| | - Ina C Meier
- Functional Forest Ecology, University of Hamburg, Haidkrugsweg 1, 22885, Barsbütel, Germany
| | - Liesje Mommer
- Plant Ecology and Nature Conservation Group, Department of Environmental Sciences, Wageningen University and Research, PO Box 47, 6700 AA, Wageningen, the Netherlands
| | | | - Laura Rose
- Station d'Ecologie Théorique et Expérimentale, CNRS, 2 route du CNRS, 09200, Moulis, France
- Senckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, 60325, Frankfurt am Main, Germany
| | - Peter Ryser
- Laurentian University, 935 Ramsey Lake Road, Sudbury, ON, P3E 2C6, Canada
| | | | - Nadejda A Soudzilovskaia
- Environmental Biology Department, Institute of Environmental Sciences, CML, Leiden University, Leiden, 2300 RA, the Netherlands
| | - Alexia Stokes
- INRAE, AMAP, CIRAD, IRD, CNRS, University of Montpellier, Montpellier, 34000, France
| | - Tao Sun
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Oscar J Valverde-Barrantes
- International Center for Tropical Botany, Department of Biological Sciences, Florida International University, Miami, FL, 33199, USA
| | - Monique Weemstra
- CEFE, Univ Montpellier, CNRS, EPHE, IRD, 1919 route de Mende, Montpellier, 34293, France
| | - Alexandra Weigelt
- Systematic Botany and Functional Biodiversity, Institute of Biology, Leipzig University, Johannisallee 21-23, Leipzig, 04103, Germany
| | - Nina Wurzburger
- Odum School of Ecology, University of Georgia, 140 E. Green Street, Athens, GA, 30602, USA
| | - Larry M York
- Biosciences Division and Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Sarah A Batterman
- School of Geography and Priestley International Centre for Climate, University of Leeds, Leeds, LS2 9JT, UK
- Cary Institute of Ecosystem Studies, Millbrook, NY, 12545, USA
| | - Moemy Gomes de Moraes
- Department of Botany, Institute of Biological Sciences, Federal University of Goiás, 19, 74690-900, Goiânia, Goiás, Brazil
| | - Štěpán Janeček
- School of Biological Sciences, The University of Western Australia, 35 Stirling Highway, Crawley (Perth), WA 6009, Australia
| | - Hans Lambers
- School of Biological Sciences, The University of Western Australia, Crawley (Perth), WA, Australia
| | - Verity Salmon
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Nishanth Tharayil
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, 29634, USA
| | - M Luke McCormack
- Center for Tree Science, Morton Arboretum, 4100 Illinois Rt. 53, Lisle, IL, 60532, USA
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16
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An Ontology-Driven Personalized Faceted Search for Exploring Knowledge Bases of Capsicum. FUTURE INTERNET 2021. [DOI: 10.3390/fi13070172] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Capsicum is a genus of flowering plants in the Solanaceae family in which the members are well known to have a high economic value. The Capsicum fruits, which are popularly known as peppers or chili, have been widely used by people worldwide. It serves as a spice and raw material for many products such as sauce, food coloring, and medicine. For many years, scientists have studied this plant to optimize its production. A tremendous amount of knowledge has been obtained and shared, as reflected in multiple knowledge-based systems, databases, or information systems. An approach to knowledge-sharing is through the adoption of a common ontology to eliminate knowledge understanding discrepancy. Unfortunately, most of the knowledge-sharing solutions are intended for scientists who are familiar with the subject. On the other hand, there are groups of potential users that could benefit from such systems but have minimal knowledge of the subject. For these non-expert users, finding relevant information from a less familiar knowledge base would be daunting. More than that, users have various degrees of understanding of the available content in the knowledge base. This understanding discrepancy raises a personalization problem. In this paper, we introduce a solution to overcome this challenge. First, we developed an ontology to facilitate knowledge-sharing about Capsicum to non-expert users. Second, we developed a personalized faceted search algorithm that provides multiple structured ways to explore the knowledge base. The algorithm addresses the personalization problem by identifying the degree of understanding about the subject from each user. In this way, non-expert users could explore a knowledge base of Capsicum efficiently. Our solution characterized users into four groups. As a result, our faceted search algorithm defines four types of matching mechanisms, including three ranking mechanisms as the core of our solution. In order to evaluate the proposed method, we measured the predictability degree of produced list of facets. Our findings indicated that the proposed matching mechanisms could tolerate various query types, and a high degree of predictability can be achieved by combining multiple ranking mechanisms. Furthermore, it demonstrates that our approach has a high potential contribution to biodiversity science in general, where many knowledge-based systems have been developed with limited access to users outside of the domain.
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Ramírez-Andreotta MD, Walls R, Youens-Clark K, Blumberg K, Isaacs KE, Kaufmann D, Maier RM. Alleviating Environmental Health Disparities Through Community Science and Data Integration. FRONTIERS IN SUSTAINABLE FOOD SYSTEMS 2021; 5. [PMID: 35664667 PMCID: PMC9165534 DOI: 10.3389/fsufs.2021.620470] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Environmental contamination is a fundamental determinant of health and well-being, and when the environment is compromised, vulnerabilities are generated. The complex challenges associated with environmental health and food security are influenced by current and emerging political, social, economic, and environmental contexts. To solve these “wicked” dilemmas, disparate public health surveillance efforts are conducted by local, state, and federal agencies. More recently, citizen/community science (CS) monitoring efforts are providing site-specific data. One of the biggest challenges in using these government datasets, let alone incorporating CS data, for a holistic assessment of environmental exposure is data management and interoperability. To facilitate a more holistic perspective and approach to solution generation, we have developed a method to provide a common data model that will allow environmental health researchers working at different scales and research domains to exchange data and ask new questions. We anticipate that this method will help to address environmental health disparities, which are unjust and avoidable, while ensuring CS datasets are ethically integrated to achieve environmental justice. Specifically, we used a transdisciplinary research framework to develop a methodology to integrate CS data with existing governmental environmental monitoring and social attribute data (vulnerability and resilience variables) that span across 10 different federal and state agencies. A key challenge in integrating such different datasets is the lack of widely adopted ontologies for vulnerability and resiliency factors. In addition to following the best practice of submitting new term requests to existing ontologies to fill gaps, we have also created an application ontology, the Superfund Research Project Data Interface Ontology (SRPDIO).
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Affiliation(s)
- Mónica D. Ramírez-Andreotta
- Department of Environmental Science, University of Arizona, Tucson, AZ, United States
- Mel and Enid Zuckerman College of Public Health’s Division of Community, Environment and Policy, University of Arizona, Tucson, AZ, United States
- Correspondence: Mónica D. Ramírez-Andreotta
| | - Ramona Walls
- BIO5 Institute, University of Arizona, Tucson, AZ, United States
| | - Ken Youens-Clark
- Department of Biosystems Engineering, University of Arizona, Tucson, AZ, United States
| | - Kai Blumberg
- Department of Biosystems Engineering, University of Arizona, Tucson, AZ, United States
| | - Katherine E. Isaacs
- Department of Computer Science, University of Arizona, Tucson, AZ, United States
| | - Dorsey Kaufmann
- Department of Environmental Science, University of Arizona, Tucson, AZ, United States
| | - Raina M. Maier
- Department of Environmental Science, University of Arizona, Tucson, AZ, United States
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Touré V, Vercruysse S, Acencio ML, Lovering RC, Orchard S, Bradley G, Casals-Casas C, Chaouiya C, Del-Toro N, Flobak Å, Gaudet P, Hermjakob H, Hoyt CT, Licata L, Lægreid A, Mungall CJ, Niknejad A, Panni S, Perfetto L, Porras P, Pratt D, Saez-Rodriguez J, Thieffry D, Thomas PD, Türei D, Kuiper M. The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). Bioinformatics 2021; 36:5712-5718. [PMID: 32637990 PMCID: PMC8023674 DOI: 10.1093/bioinformatics/btaa622] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 06/06/2020] [Accepted: 06/30/2020] [Indexed: 12/30/2022] Open
Abstract
Motivation A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called ‘causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources. Results Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources. Availability and implementation The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Vasundra Touré
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway
| | - Steven Vercruysse
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway
| | - Marcio Luis Acencio
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway
| | - Ruth C Lovering
- Functional Gene Annotation, Preclinical and Fundamental Science, Institute of Cardiovascular Science, UCL, University College London, London WC1E 6JF, UK
| | - Sandra Orchard
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Glyn Bradley
- Computational Biology, Functional Genomics, GSK, Stevenage SG1 2NY, UK
| | | | - Claudine Chaouiya
- Aix Marseille Univ, CNRS, Centrale Marseille, I2M Marseille 13331, France
| | - Noemi Del-Toro
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Åsmund Flobak
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway.,The Cancer Clinic, St. Olav's Hospital, Trondheim University Hospital, Trondheim 7030, Norway
| | - Pascale Gaudet
- SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland
| | - Henning Hermjakob
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | | | - Luana Licata
- Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy
| | - Astrid Lægreid
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway
| | - Christopher J Mungall
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Anne Niknejad
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Quartier Sorge, Amphipole Building, 1015 Lausanne, Switzerland
| | - Simona Panni
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Ecology and Earth Science, Via Pietro Bucci Cubo 6/C, Rende 87036, CS, Italy
| | - Livia Perfetto
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Pablo Porras
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Dexter Pratt
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Julio Saez-Rodriguez
- Institute of Computational Biomedicine, Heidelberg University, Faculty of Medicine, 69120 Heidelberg, Germany.,Joint Research Centre for Computational Biomedicine (JRC-COMBINE), Faculty of Medicine, RWTH Aachen University, Aachen 52062, Germany
| | - Denis Thieffry
- Institut de Biologie de l'ENS (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
| | - Paul D Thomas
- Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90007, USA
| | - Dénes Türei
- Joint Research Centre for Computational Biomedicine (JRC-COMBINE), Faculty of Medicine, RWTH Aachen University, Aachen 52062, Germany
| | - Martin Kuiper
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim 7491, Norway
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20
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Kolmykov S, Yevshin I, Kulyashov M, Sharipov R, Kondrakhin Y, Makeev VJ, Kulakovskiy IV, Kel A, Kolpakov F. GTRD: an integrated view of transcription regulation. Nucleic Acids Res 2021; 49:D104-D111. [PMID: 33231677 PMCID: PMC7778956 DOI: 10.1093/nar/gkaa1057] [Citation(s) in RCA: 101] [Impact Index Per Article: 33.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/18/2020] [Accepted: 11/03/2020] [Indexed: 12/24/2022] Open
Abstract
The Gene Transcription Regulation Database (GTRD; http://gtrd.biouml.org/) contains uniformly annotated and processed NGS data related to gene transcription regulation: ChIP-seq, ChIP-exo, DNase-seq, MNase-seq, ATAC-seq and RNA-seq. With the latest release, the database has reached a new level of data integration. All cell types (cell lines and tissues) presented in the GTRD were arranged into a dictionary and linked with different ontologies (BRENDA, Cell Ontology, Uberon, Cellosaurus and Experimental Factor Ontology) and with related experiments in specialized databases on transcription regulation (FANTOM5, ENCODE and GTEx). The updated version of the GTRD provides an integrated view of transcription regulation through a dedicated web interface with advanced browsing and search capabilities, an integrated genome browser, and table reports by cell types, transcription factors, and genes of interest.
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Affiliation(s)
- Semyon Kolmykov
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russian Federation
- Federal Research Center Institute of Cytology and Genetics SB RAS, Novosibirsk 630090, Russian Federation
| | - Ivan Yevshin
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russian Federation
| | - Mikhail Kulyashov
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russian Federation
- Novosibirsk State University, Novosibirsk 630090, Russian Federation
| | - Ruslan Sharipov
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russian Federation
- Novosibirsk State University, Novosibirsk 630090, Russian Federation
| | - Yury Kondrakhin
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russian Federation
| | - Vsevolod J Makeev
- Vavilov Institute of General Genetics RAS, Moscow 119991, Russian Federation
- Moscow Institute of Physics and Technology (State University), Dolgoprudny 141700, Russian Federation
- NRC «Kurchatov Institute» - GOSNIIGENETIKA, Kurchatov Genomic Center, Moscow 123182, Russian Federation
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russian Federation
| | - Ivan V Kulakovskiy
- Vavilov Institute of General Genetics RAS, Moscow 119991, Russian Federation
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russian Federation
- Institute of Protein Research, Russian Academy of Sciences, Pushchino 142290, Russian Federation
| | - Alexander Kel
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- geneXplain GmbH, 38302 Wolfenbüttel, Germany
- Institute of Chemical Biology and Fundamental Medicine SB RAS, Novosibirsk 630090, Russian Federation
| | - Fedor Kolpakov
- BIOSOFT.RU, LLC, Novosibirsk 630090, Russian Federation
- Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russian Federation
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21
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Arnaud E, Laporte MA, Kim S, Aubert C, Leonelli S, Miro B, Cooper L, Jaiswal P, Kruseman G, Shrestha R, Buttigieg PL, Mungall CJ, Pietragalla J, Agbona A, Muliro J, Detras J, Hualla V, Rathore A, Das RR, Dieng I, Bauchet G, Menda N, Pommier C, Shaw F, Lyon D, Mwanzia L, Juarez H, Bonaiuti E, Chiputwa B, Obileye O, Auzoux S, Yeumo ED, Mueller LA, Silverstein K, Lafargue A, Antezana E, Devare M, King B. The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems. PATTERNS (NEW YORK, N.Y.) 2020; 1:100105. [PMID: 33205138 PMCID: PMC7660444 DOI: 10.1016/j.patter.2020.100105] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 05/28/2020] [Accepted: 08/24/2020] [Indexed: 12/15/2022]
Abstract
Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.
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Affiliation(s)
- Elizabeth Arnaud
- Digital Solutions Team, Digital Inclusion Lever, Bioversity International, Montpellier Office, Montpellier, France
| | - Marie-Angélique Laporte
- Digital Solutions Team, Digital Inclusion Lever, Bioversity International, Montpellier Office, Montpellier, France
| | - Soonho Kim
- Markets, Trade and Institutions Division (MTID), International Food Policy Research Institute (IFPRI), Washington, DC, USA
| | - Céline Aubert
- Environment and Production Technology Division (EPTD), International Food Policy Research Institute (IFPRI), Washington, DC, USA
| | - Sabina Leonelli
- Department of Sociology, Philosophy and Anthropology & Exeter Centre for the Study of the Life Sciences (Egenis), University of Exeter, Exeter, UK
| | - Berta Miro
- Agrifood Policy Platform, International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines
| | - Laurel Cooper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Gideon Kruseman
- Socio-Economics Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, State of México, Mexico
| | - Rosemary Shrestha
- Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, State of México, México
| | - Pier Luigi Buttigieg
- Helmholtz Metadata Collaboration, GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany
| | - Christopher J. Mungall
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | - Afolabi Agbona
- Cassava Breeding Program, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | | | - Jeffrey Detras
- Bioinformatics Cluster, Strategic Innovation Platform, International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines
| | - Vilma Hualla
- Research Informatics Unit (RIU), International Potato Center (CIP), Lima, Peru
| | - Abhishek Rathore
- Statistics, Bioinformatics & Data Management (SBDM) Theme, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India
| | - Roma Rani Das
- Statistics, Bioinformatics & Data Management (SBDM) Theme, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India
| | - Ibnou Dieng
- Biometrics Unit, International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Guillaume Bauchet
- Mueller Bioinformatics Laboratory, Boyce Thompson Institute for Plant Research, Ithaca, NY, USA
| | - Naama Menda
- Mueller Bioinformatics Laboratory, Boyce Thompson Institute for Plant Research, Ithaca, NY, USA
| | - Cyril Pommier
- BioinfOmics, Plant Bioinformatics Facility, Université Paris-Saclay, Institut National de la Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Versailles, France
| | - Felix Shaw
- Digital Biology, Earlham Institute, Norwich, Norfolk, UK
| | - David Lyon
- Mueller Bioinformatics Laboratory, Boyce Thompson Institute for Plant Research, Ithaca, NY, USA
| | - Leroy Mwanzia
- Performance, Innovation and Strategic Analysis, International Center for Tropical Agriculture (CIAT), Regional Office for Africa, Nairobi, Kenya
| | - Henry Juarez
- Research Informatics Unit (RIU), International Potato Center (CIP), Lima, Peru
| | - Enrico Bonaiuti
- Monitoring, Evaluation and Learning Team, International Center for Agricultural Research in the Dry Areas (ICARDA), Beirut, Lebanon
| | - Brian Chiputwa
- Research Methods Group (RMG), World Agroforestry (ICRAF), Nairobi, Kenya
| | - Olatunbosun Obileye
- Data Management Section, International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Sandrine Auzoux
- UPR AIDA, The French Agricultural Research Centre for International Development (CIRAD), Sainte-Clotilde, Réunion, France
- Université de Montpellier, Montpellier, France
| | - Esther Dzalé Yeumo
- Unité Délégation à l’Information Scientifique et Technique - DIST, Institut National de la Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Versailles, France
| | - Lukas A. Mueller
- Mueller Bioinformatics Laboratory, Boyce Thompson Institute for Plant Research, Ithaca, NY, USA
| | | | | | - Erick Antezana
- Bayer Crop Science SA-NV, Diegem, Belgium
- Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Medha Devare
- Environment and Production Technology Division (EPTD), International Food Policy Research Institute (IFPRI), Washington, DC, USA
| | - Brian King
- CGIAR Platform for Big Data in Agriculture, International Center for Tropical Agriculture (CIAT), Cali, Colombia
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Shaw F, Etuk A, Minotto A, Gonzalez-Beltran A, Johnson D, Rocca-Serra P, Laporte MA, Arnaud E, Devare M, Kersey P, Sansone SA, Davey RP. COPO: a metadata platform for brokering FAIR data in the life sciences. F1000Res 2020. [DOI: 10.12688/f1000research.23889.1] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Scientific innovation is increasingly reliant on data and computational resources. Much of today’s life science research involves generating, processing, and reusing heterogeneous datasets that are growing exponentially in size. Demand for technical experts (data scientists and bioinformaticians) to process these data is at an all-time high, but these are not typically trained in good data management practices. That said, we have come a long way in the last decade, with funders, publishers, and researchers themselves making the case for open, interoperable data as a key component of an open science philosophy. In response, recognition of the FAIR Principles (that data should be Findable, Accessible, Interoperable and Reusable) has become commonplace. However, both technical and cultural challenges for the implementation of these principles still exist when storing, managing, analysing and disseminating both legacy and new data. COPO is a computational system that attempts to address some of these challenges by enabling scientists to describe their research objects (raw or processed data, publications, samples, images, etc.) using community-sanctioned metadata sets and vocabularies, and then use public or institutional repositories to share them with the wider scientific community. COPO encourages data generators to adhere to appropriate metadata standards when publishing research objects, using semantic terms to add meaning to them and specify relationships between them. This allows data consumers, be they people or machines, to find, aggregate, and analyse data which would otherwise be private or invisible, building upon existing standards to push the state of the art in scientific data dissemination whilst minimising the burden of data publication and sharing.
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Braun IR, Yanarella CF, Lawrence-Dill CJ. Computing on Phenotypic Descriptions for Candidate Gene Discovery and Crop Improvement. PLANT PHENOMICS (WASHINGTON, D.C.) 2020; 2020:1963251. [PMID: 33313544 PMCID: PMC7706311 DOI: 10.34133/2020/1963251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 04/05/2020] [Indexed: 05/31/2023]
Abstract
Many newly observed phenotypes are first described, then experimentally manipulated. These language-based descriptions appear in both the literature and in community datastores. To standardize phenotypic descriptions and enable simple data aggregation and analysis, controlled vocabularies and specific data architectures have been developed. Such simplified descriptions have several advantages over natural language: they can be rigorously defined for a particular context or problem, they can be assigned and interpreted programmatically, and they can be organized in a way that allows for semantic reasoning (inference of implicit facts). Because researchers generally report phenotypes in the literature using natural language, curators have been translating phenotypic descriptions into controlled vocabularies for decades to make the information computable. Unfortunately, this methodology is highly dependent on human curation, which does not scale to the scope of all publications available across all of plant biology. Simultaneously, researchers in other domains have been working to enable computation on natural language. This has resulted in new, automated methods for computing on language that are now available, with early analyses showing great promise. Natural language processing (NLP) coupled with machine learning (ML) allows for the use of unstructured language for direct analysis of phenotypic descriptions. Indeed, we have found that these automated methods can be used to create data structures that perform as well or better than those generated by human curators on tasks such as predicting gene function and biochemical pathway membership. Here, we describe current and ongoing efforts to provide tools for the plant phenomics community to explore novel predictions that can be generated using these techniques. We also describe how these methods could be used along with mobile speech-to-text tools to collect and analyze in-field spoken phenotypic descriptions for association genetics and breeding applications.
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Affiliation(s)
- Ian R. Braun
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Colleen F. Yanarella
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Carolyn J. Lawrence-Dill
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
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Abstract
Abstract
Biodiversity research studies the variability and diversity of organisms, including variability within and between species with particular focus on the functional diversity of traits and their relationship to environment. Managing biodiversity data implies dealing with its heterogeneous nature using semantics and tailored ontologies. These are themselves differently conceived, and combining them in semantically enabled applications necessitates an effective alignment between their concepts. This paper describes the ontology matching of biodiversity- and ecology-related ontologies. We illustrate diverse challenges introduced by this kind of ontologies to ontology matching in general. Real use cases requiring pairwise alignments between environment and trait ontologies are introduced. We describe our experience creating a new track at the Ontology Alignment Evaluation Initiative designed for this specific domain and report on the results obtained by state-of-the-art participating systems. The biodiversity and ecology use case turns out to be a strong one for ontology matching, introducing new interesting challenges. Even if most of the matching systems perform relatively well in the proposed matching tasks, there is still room for improvement. We highlight possible directions in that matter and elaborate on our plan to further progress with the track.
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Braun IR, Lawrence-Dill CJ. Automated Methods Enable Direct Computation on Phenotypic Descriptions for Novel Candidate Gene Prediction. FRONTIERS IN PLANT SCIENCE 2020; 10:1629. [PMID: 31998331 PMCID: PMC6965352 DOI: 10.3389/fpls.2019.01629] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 11/19/2019] [Indexed: 06/01/2023]
Abstract
Natural language descriptions of plant phenotypes are a rich source of information for genetics and genomics research. We computationally translated descriptions of plant phenotypes into structured representations that can be analyzed to identify biologically meaningful associations. These representations include the entity-quality (EQ) formalism, which uses terms from biological ontologies to represent phenotypes in a standardized, semantically rich format, as well as numerical vector representations generated using natural language processing (NLP) methods (such as the bag-of-words approach and document embedding). We compared resulting phenotype similarity measures to those derived from manually curated data to determine the performance of each method. Computationally derived EQ and vector representations were comparably successful in recapitulating biological truth to representations created through manual EQ statement curation. Moreover, NLP methods for generating vector representations of phenotypes are scalable to large quantities of text because they require no human input. These results indicate that it is now possible to computationally and automatically produce and populate large-scale information resources that enable researchers to query phenotypic descriptions directly.
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Affiliation(s)
- Ian R. Braun
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA, United States
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA, United States
| | - Carolyn J. Lawrence-Dill
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA, United States
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA, United States
- Department of Agronomy, Iowa State University, Ames, IA, United States
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Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, O’Donovan C. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res 2020; 48:D440-D444. [PMID: 31691833 PMCID: PMC7145518 DOI: 10.1093/nar/gkz1019] [Citation(s) in RCA: 295] [Impact Index Per Article: 73.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 10/17/2019] [Accepted: 10/31/2019] [Indexed: 11/23/2022] Open
Abstract
MetaboLights is a database for metabolomics studies, their raw experimental data and associated metadata. The database is cross-species and cross-technique and it covers metabolite structures and their reference spectra as well as their biological roles and locations. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information. In this article, we describe the significant updates that we have made over the last two years to the resource to respond to the increasing amount and diversity of data being submitted by the metabolomics community. We refreshed the website and most importantly, our submission process was completely overhauled to enable us to deliver a far more user-friendly submission process and to facilitate the growing demand for reproducibility and integration with other 'omics. Metabolomics resources and data are available under the EMBL-EBI's Terms of Use via the web at https://www.ebi.ac.uk/metabolights and under Apache 2.0 at Github (https://github.com/EBI-Metabolights/).
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Affiliation(s)
- Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Keeva Cochrane
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Venkata Chandrasekhar Nainala
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Mark Williams
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jiakang Chang
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kalai Vanii Jayaseelan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Claire O’Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Wegrzyn JL, Falk T, Grau E, Buehler S, Ramnath R, Herndon N. Cyberinfrastructure and resources to enable an integrative approach to studying forest trees. Evol Appl 2020; 13:228-241. [PMID: 31892954 PMCID: PMC6935593 DOI: 10.1111/eva.12860] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 08/11/2019] [Accepted: 08/14/2019] [Indexed: 12/19/2022] Open
Abstract
Sequencing technologies and bioinformatic approaches are now available to resolve the challenges associated with complex and heterozygous genomes. Increased access to less expensive and more effective instrumentation will contribute to a wealth of high-quality plant genomes in the next few years. In the meantime, more than 370 tree species are associated with public projects in primary repositories that are interrogating expression profiles, identifying variants, or analyzing targeted capture without a high-quality reference genome. Genomic data from these projects generates sequences that represent intermediate assemblies for transcriptomes and genomes. These data contribute to forest tree biology, but the associated sequence remains trapped in supplemental files that are poorly integrated in plant community databases and comparative genomic platforms. Successful implementation of life science cyberinfrastructure is improving data standards, ontologies, analytic workflows, and integrated database platforms for both model and non-model plant species. Unique to forest trees with large populations that are long-lived, outcrossing, and genetically diverse, the phenotypic and environmental metrics associated with georeferenced populations are just as important as the genomic data sampled for each individual. To address questions related to forest health and productivity, cyberinfrastructure must keep pace with the magnitude of genomic and phenomic sampling of larger populations. This review examines the current landscape of cyberinfrastructure, with an emphasis on best practices and resources to align community data with the Findable, Accessible, Interoperable, and Reusable (FAIR) guidelines.
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Affiliation(s)
- Jill L. Wegrzyn
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut
| | - Taylor Falk
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut
| | - Emily Grau
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut
| | - Sean Buehler
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut
| | - Risharde Ramnath
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut
| | - Nic Herndon
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut
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Shamimuzzaman M, Gardiner JM, Walsh AT, Triant DA, Le Tourneau JJ, Tayal A, Unni DR, Nguyen HN, Portwood JL, Cannon EKS, Andorf CM, Elsik CG. MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database. FRONTIERS IN PLANT SCIENCE 2020; 11:592730. [PMID: 33193550 PMCID: PMC7642280 DOI: 10.3389/fpls.2020.592730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 10/01/2020] [Indexed: 05/11/2023]
Abstract
MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.
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Affiliation(s)
- Md Shamimuzzaman
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Jack M. Gardiner
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Amy T. Walsh
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Deborah A. Triant
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | | | - Aditi Tayal
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Deepak R. Unni
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Hung N. Nguyen
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - John L. Portwood
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, United States
| | - Ethalinda K. S. Cannon
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, United States
| | - Carson M. Andorf
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, United States
| | - Christine G. Elsik
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
- Division of Plant Sciences, University of Missouri, Columbia, MO, United States
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States
- *Correspondence: Christine G. Elsik,
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29
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Tello-Ruiz MK, Naithani S, Stein JC, Gupta P, Campbell M, Olson A, Wei S, Preece J, Geniza MJ, Jiao Y, Lee YK, Wang B, Mulvaney J, Chougule K, Elser J, Al-Bader N, Kumari S, Thomason J, Kumar V, Bolser DM, Naamati G, Tapanari E, Fonseca N, Huerta L, Iqbal H, Keays M, Munoz-Pomer Fuentes A, Tang A, Fabregat A, D'Eustachio P, Weiser J, Stein LD, Petryszak R, Papatheodorou I, Kersey PJ, Lockhart P, Taylor C, Jaiswal P, Ware D. Gramene 2018: unifying comparative genomics and pathway resources for plant research. Nucleic Acids Res 2019; 46:D1181-D1189. [PMID: 29165610 PMCID: PMC5753211 DOI: 10.1093/nar/gkx1111] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 10/25/2017] [Indexed: 12/24/2022] Open
Abstract
Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.
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Affiliation(s)
| | - Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Joshua C Stein
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Parul Gupta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Michael Campbell
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sharon Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Justin Preece
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Matthew J Geniza
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Yinping Jiao
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Young Koung Lee
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.,Division of Biological Sciences and Institute for Basic Science, Wonkwang University, Iksan 54538, Korea
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Joseph Mulvaney
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Noor Al-Bader
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - James Thomason
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Vivek Kumar
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Daniel M Bolser
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Guy Naamati
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Electra Tapanari
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Nuno Fonseca
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Laura Huerta
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Haider Iqbal
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Maria Keays
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | | | - Amy Tang
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Antonio Fabregat
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Peter D'Eustachio
- Department of Biochemistry & Molecular Pharmacology, NYU School of Medicine, New York, NY 10016, USA
| | - Joel Weiser
- Informatics and Bio-computing Program, Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
| | - Lincoln D Stein
- Adaptive Oncology Program, Ontario Institute for Cancer Research, Toronto M5G 0A3, Canada
| | - Robert Petryszak
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Irene Papatheodorou
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Paul J Kersey
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Patti Lockhart
- American Society of Plant Biologists, 15501 Monona Drive, Rockville, MD 20855-2768, USA
| | - Crispin Taylor
- American Society of Plant Biologists, 15501 Monona Drive, Rockville, MD 20855-2768, USA
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.,USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
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Cooper L, Meier A, Laporte MA, Elser JL, Mungall C, Sinn BT, Cavaliere D, Carbon S, Dunn NA, Smith B, Qu B, Preece J, Zhang E, Todorovic S, Gkoutos G, Doonan JH, Stevenson DW, Arnaud E, Jaiswal P. The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics. Nucleic Acids Res 2019; 46:D1168-D1180. [PMID: 29186578 PMCID: PMC5753347 DOI: 10.1093/nar/gkx1152] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 11/21/2017] [Indexed: 01/08/2023] Open
Abstract
The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository.
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Affiliation(s)
- Laurel Cooper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Austin Meier
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | | | - Justin L Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Chris Mungall
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | | | | | - Seth Carbon
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Nathan A Dunn
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Barry Smith
- Department of Philosophy, University at Buffalo, Buffalo, NY 14260, USA
| | - Botong Qu
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA
| | - Justin Preece
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Eugene Zhang
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA
| | - Sinisa Todorovic
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA
| | - Georgios Gkoutos
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - John H Doonan
- National Plant Phenomics Centre, Institute of Biological, Environmental, and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA, UK
| | | | - Elizabeth Arnaud
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
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31
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Walls RL, Cooper L, Elser J, Gandolfo MA, Mungall CJ, Smith B, Stevenson DW, Jaiswal P. The Plant Ontology Facilitates Comparisons of Plant Development Stages Across Species. FRONTIERS IN PLANT SCIENCE 2019; 10:631. [PMID: 31214208 PMCID: PMC6558174 DOI: 10.3389/fpls.2019.00631] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/26/2019] [Indexed: 06/09/2023]
Abstract
The Plant Ontology (PO) is a community resource consisting of standardized terms, definitions, and logical relations describing plant structures and development stages, augmented by a large database of annotations from genomic and phenomic studies. This paper describes the structure of the ontology and the design principles we used in constructing PO terms for plant development stages. It also provides details of the methodology and rationale behind our revision and expansion of the PO to cover development stages for all plants, particularly the land plants (bryophytes through angiosperms). As a case study to illustrate the general approach, we examine variation in gene expression across embryo development stages in Arabidopsis and maize, demonstrating how the PO can be used to compare patterns of expression across stages and in developmentally different species. Although many genes appear to be active throughout embryo development, we identified a small set of uniquely expressed genes for each stage of embryo development and also between the two species. Evaluating the different sets of genes expressed during embryo development in Arabidopsis or maize may inform future studies of the divergent developmental pathways observed in monocotyledonous versus dicotyledonous species. The PO and its annotation database (http://www.planteome.org) make plant data for any species more discoverable and accessible through common formats, thus providing support for applications in plant pathology, image analysis, and comparative development and evolution.
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Affiliation(s)
- Ramona L. Walls
- CyVerse, Bio5 Institute, The University of Arizona, Tucson, AZ, United States
| | - Laurel Cooper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Maria Alejandra Gandolfo
- Liberty Hyde Bailey Hortorium, Plant Biology Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
| | - Christopher J. Mungall
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Barry Smith
- Department of Philosophy, University at Buffalo, Buffalo, NY, United States
| | | | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
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32
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Pan Q, Wei J, Guo F, Huang S, Gong Y, Liu H, Liu J, Li L. Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics. BMC Genomics 2019; 20:443. [PMID: 31159731 PMCID: PMC6547493 DOI: 10.1186/s12864-019-5812-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Accepted: 05/20/2019] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Trait ontology (TO) analysis is a powerful system for functional annotation and enrichment analysis of genes. However, given the complexity of the molecular mechanisms underlying phenomes, only a few hundred gene-to-TO relationships in plants have been elucidated to date, limiting the pace of research in this "big data" era. RESULTS Here, we curated all the available trait associated sites (TAS) information from 79 association mapping studies of maize (Zea mays L.) and rice (Oryza sativa L.) lines with diverse genetic backgrounds and built a large-scale TAS-derived TO system for functional annotation of genes in various crops. Our TO system contains information for up to 18,042 genes (6345 in maize at the 25 k level and 11,697 in rice at the 50 k level), including gene-to-TO relationships, which covers over one fifth of the annotated gene sets for maize and rice. A comparison of Gene Ontology (GO) vs. TO analysis demonstrated that the TAS-derived TO system is an efficient alternative tool for gene functional annotation and enrichment analysis. We therefore combined information from the TO, GO, metabolic pathway, and co-expression network databases and constructed the TAS system, which is publicly available at http://tas.hzau.edu.cn . TAS provides a user-friendly interface for functional annotation of genes, enrichment analysis, genome-wide extraction of trait-associated genes, and crosschecking of different functional annotation databases. CONCLUSIONS TAS bridges the gap between genomic and phenomic information in crops. This easy-to-use tool will be useful for geneticists, biologists, and breeders in the agricultural community, as it facilitates the dissection of molecular mechanisms conferring agronomic traits in an easy, genome-wide manner.
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Affiliation(s)
- Qingchun Pan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Junfeng Wei
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Feng Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Suiyong Huang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yong Gong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Hao Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jianxiao Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
| | - Lin Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
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33
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Brenskelle L, Stucky BJ, Deck J, Walls R, Guralnick RP. Integrating herbarium specimen observations into global phenology data systems. APPLICATIONS IN PLANT SCIENCES 2019; 7:e01231. [PMID: 30937223 PMCID: PMC6426164 DOI: 10.1002/aps3.1231] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 01/21/2019] [Indexed: 05/11/2023]
Abstract
PREMISE OF THE STUDY The Plant Phenology Ontology (PPO) was originally developed to integrate phenology observations of whole plants across different global observation networks. Here we describe a new release of the PPO and associated data pipelines that supports integration of phenology observations from herbarium specimens, which provide historical and modern phenology data. METHODS AND RESULTS Critical changes to the PPO include key terms that describe how measurements from parts of plants, which are captured in most imaged herbarium specimens, relate to whole plants. We provide proof of concept for ingesting annotations from imaged herbarium sheets of Prunus serotina, the common black cherry. We then provide an example analysis of changes in flowering timing over the past 125 years, demonstrating the value of integrating herbarium and observational phenology data sets. CONCLUSIONS These conceptual and technical advances will support the addition of phenology data from herbaria, but also could be expanded upon to facilitate the inclusion of data from photograph-based citizen science platforms. With the incorporation of herbarium phenology data, new historical baseline data will strengthen the capability to monitor, model, and forecast plant phenology changes.
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Affiliation(s)
- Laura Brenskelle
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFloridaUSA
| | - Brian J. Stucky
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFloridaUSA
| | - John Deck
- Berkeley Natural History MuseumsUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Ramona Walls
- CyVerseBio5 InstituteThe University of ArizonaTucsonArizonaUSA
| | - Rob P. Guralnick
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFloridaUSA
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The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Res 2019; 47:D330-D338. [PMID: 30395331 PMCID: PMC6323945 DOI: 10.1093/nar/gky1055] [Citation(s) in RCA: 2556] [Impact Index Per Article: 511.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Accepted: 10/17/2018] [Indexed: 02/06/2023] Open
Abstract
The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the 'GO ribbon' widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page.
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35
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Neveu P, Tireau A, Hilgert N, Nègre V, Mineau‐Cesari J, Brichet N, Chapuis R, Sanchez I, Pommier C, Charnomordic B, Tardieu F, Cabrera‐Bosquet L. Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System. THE NEW PHYTOLOGIST 2019; 221:588-601. [PMID: 30152011 PMCID: PMC6585972 DOI: 10.1111/nph.15385] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 07/07/2018] [Indexed: 05/13/2023]
Abstract
Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.
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Affiliation(s)
- Pascal Neveu
- MISTEA, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Anne Tireau
- MISTEA, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Nadine Hilgert
- MISTEA, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Vincent Nègre
- LEPSE, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Jonathan Mineau‐Cesari
- MISTEA, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
- LEPSE, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Nicolas Brichet
- LEPSE, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Romain Chapuis
- UE DIASCOPE, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Isabelle Sanchez
- MISTEA, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
| | - Cyril Pommier
- INRA, UR1164 URGI – Research Unit in Genomics‐InfoINRA de Versailles‐GrignonRoute de Saint‐CyrVersailles78026France
| | | | - François Tardieu
- LEPSE, INRA, Montpellier SupAgro, Université de MontpellierMontpellier34060France
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Venkatesan A, Tagny Ngompe G, Hassouni NE, Chentli I, Guignon V, Jonquet C, Ruiz M, Larmande P. Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy. PLoS One 2018; 13:e0198270. [PMID: 30500839 PMCID: PMC6269127 DOI: 10.1371/journal.pone.0198270] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 09/03/2018] [Indexed: 12/22/2022] Open
Abstract
Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have developed the Agronomic Linked Data (AgroLD- www.agrold.org), a knowledge-based system relying on Semantic Web technologies and exploiting standard domain ontologies, to integrate data about plant species of high interest for the plant science community e.g., rice, wheat, arabidopsis. We present some integration results of the project, which initially focused on genomics, proteomics and phenomics. AgroLD is now an RDF (Resource Description Format) knowledge base of 100M triples created by annotating and integrating more than 50 datasets coming from 10 data sources-such as Gramene.org and TropGeneDB-with 10 ontologies-such as the Gene Ontology and Plant Trait Ontology. Our evaluation results show users appreciate the multiple query modes which support different use cases. AgroLD's objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes/proteins in, for instances, plant disease resistance or high yield traits. We expect the resolution of these questions to facilitate the formulation of new scientific hypotheses to be validated with a knowledge-oriented approach.
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Affiliation(s)
- Aravind Venkatesan
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- LIRMM, Univ. of Montpellier & CNRS, Montpellier, France
| | - Gildas Tagny Ngompe
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- LIRMM, Univ. of Montpellier & CNRS, Montpellier, France
| | - Nordine El Hassouni
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- UMR AGAP, CIRAD, Montpellier, France
- South Green Bioinformatics Platform, Montpellier, France
| | - Imene Chentli
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- LIRMM, Univ. of Montpellier & CNRS, Montpellier, France
| | - Valentin Guignon
- South Green Bioinformatics Platform, Montpellier, France
- Bioversity International, Montpellier, France
| | - Clement Jonquet
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- LIRMM, Univ. of Montpellier & CNRS, Montpellier, France
| | - Manuel Ruiz
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- UMR AGAP, CIRAD, Montpellier, France
- South Green Bioinformatics Platform, Montpellier, France
- AGAP, Univ. of Montpellier, CIRAD, INRA, INRIA, SupAgro, Montpellier, France
| | - Pierre Larmande
- Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France
- LIRMM, Univ. of Montpellier & CNRS, Montpellier, France
- South Green Bioinformatics Platform, Montpellier, France
- DIADE, IRD, Univ. of Montpellier, Montpellier, France
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Endara L, Thessen AE, Cole HA, Walls R, Gkoutos G, Cao Y, Chong SS, Cui H. Modifier Ontologies for frequency, certainty, degree, and coverage phenotype modifier. Biodivers Data J 2018; 6:e29232. [PMID: 30532623 PMCID: PMC6281706 DOI: 10.3897/bdj.6.e29232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 11/20/2018] [Indexed: 11/21/2022] Open
Abstract
Background: When phenotypic characters are described in the literature, they may be constrained or clarified with additional information such as the location or degree of expression, these terms are called "modifiers". With effort underway to convert narrative character descriptions to computable data, ontologies for such modifiers are needed. Such ontologies can also be used to guide term usage in future publications. Spatial and method modifiers are the subjects of ontologies that already have been developed or are under development. In this work, frequency (e.g., rarely, usually), certainty (e.g., probably, definitely), degree (e.g., slightly, extremely), and coverage modifiers (e.g., sparsely, entirely) are collected, reviewed, and used to create two modifier ontologies with different design considerations. The basic goal is to express the sequential relationships within a type of modifiers, for example, usually is more frequent than rarely, in order to allow data annotated with ontology terms to be classified accordingly. Method: Two designs are proposed for the ontology, both using the list pattern: a closed ordered list (i.e., five-bin design) and an open ordered list design. The five-bin design puts the modifier terms into a set of 5 fixed bins with interval object properties, for example, one_level_more/less_frequently_than, where new terms can only be added as synonyms to existing classes. The open list approach starts with 5 bins, but supports the extensibility of the list via ordinal properties, for example, more/less_frequently_than, allowing new terms to be inserted as a new class anywhere in the list. The consequences of the different design decisions are discussed in the paper. CharaParser was used to extract modifiers from plant, ant, and other taxonomic descriptions. After a manual screening, 130 modifier words were selected as the candidate terms for the modifier ontologies. Four curators/experts (three biologists and one information scientist specialized in biosemantics) reviewed and categorized the terms into 20 bins using the Ontology Term Organizer (OTO) (http://biosemantics.arizona.edu/OTO). Inter-curator variations were reviewed and expressed in the final ontologies. Results: Frequency, certainty, degree, and coverage terms with complete agreement among all curators were used as class labels or exact synonyms. Terms with different interpretations were either excluded or included using "broader synonym" or "not recommended" annotation properties. These annotations explicitly allow for the user to be aware of the semantic ambiguity associated with the terms and whether they should be used with caution or avoided. Expert categorization results showed that 16 out of 20 bins contained terms with full agreements, suggesting differentiating the modifiers into 5 levels/bins balances the need to differentiate modifiers and the need for the ontology to reflect user consensus. Two ontologies, developed using the Protege ontology editor, are made available as OWL files and can be downloaded from https://github.com/biosemantics/ontologies. Contribution: We built the first two modifier ontologies following a consensus-based approach with terms commonly used in taxonomic literature. The five-bin ontology has been used in the Explorer of Taxon Concepts web toolkit to compute the similarity between characters extracted from literature to facilitate taxon concepts alignments. The two ontologies will also be used in an ontology-informed authoring tool for taxonomists to facilitate consistency in modifier term usage.
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Affiliation(s)
- Lorena Endara
- University of Florida, Gainesville, United States of AmericaUniversity of FloridaGainesvilleUnited States of America
| | - Anne E Thessen
- The Ronin Institute for Independent Scholarship, Monclair, NJ, United States of AmericaThe Ronin Institute for Independent ScholarshipMonclair, NJUnited States of America
| | - Heather A Cole
- Science and Technology Branch, Agriculture and Agri-Food Canada, Government of Canada, Ottawa, CanadaScience and Technology Branch, Agriculture and Agri-Food Canada, Government of CanadaOttawaCanada
| | - Ramona Walls
- CyVerse, Tucson, United States of AmericaCyVerseTucsonUnited States of America
| | - Georgios Gkoutos
- College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United KingdomCollege of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of BirminghamBirminghamUnited Kingdom
- Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, B15 2TT, Birmingham, United KingdomInstitute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, B15 2TTBirminghamUnited Kingdom
| | - Yujie Cao
- Center for Studies of Information Resources, Wuhan Universtity, Wuhan, ChinaCenter for Studies of Information Resources, Wuhan UniverstityWuhanChina
| | - Steven S. Chong
- National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, United States of AmericaNational Center for Ecological Analysis and Synthesis, University of California, Santa BarbaraSanta BarbaraUnited States of America
- University of Arizona, Tucson, United States of AmericaUniversity of ArizonaTucsonUnited States of America
| | - Hong Cui
- University of Arizona, Tucson, United States of AmericaUniversity of ArizonaTucsonUnited States of America
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38
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Appels R, Eversole K, Feuillet C, Keller B, Rogers J, Stein N, Pozniak CJ, Stein N, Choulet F, Distelfeld A, Eversole K, Poland J, Rogers J, Ronen G, Sharpe AG, Pozniak C, Ronen G, Stein N, Barad O, Baruch K, Choulet F, Keeble-Gagnère G, Mascher M, Sharpe AG, Ben-Zvi G, Josselin AA, Stein N, Mascher M, Himmelbach A, Choulet F, Keeble-Gagnère G, Mascher M, Rogers J, Balfourier F, Gutierrez-Gonzalez J, Hayden M, Josselin AA, Koh C, Muehlbauer G, Pasam RK, Paux E, Pozniak CJ, Rigault P, Sharpe AG, Tibbits J, Tiwari V, Choulet F, Keeble-Gagnère G, Mascher M, Josselin AA, Rogers J, Spannagl M, Choulet F, Lang D, Gundlach H, Haberer G, Keeble-Gagnère G, Mayer KFX, Ormanbekova D, Paux E, Prade V, Šimková H, Wicker T, Choulet F, Spannagl M, Swarbreck D, Rimbert H, Felder M, Guilhot N, Gundlach H, Haberer G, Kaithakottil G, Keilwagen J, Lang D, Leroy P, Lux T, Mayer KFX, Twardziok S, Venturini L, Appels R, Rimbert H, Choulet F, Juhász A, Keeble-Gagnère G, Choulet F, Spannagl M, Lang D, Abrouk M, Haberer G, Keeble-Gagnère G, Mayer KFX, Wicker T, Choulet F, Wicker T, Gundlach H, Lang D, Spannagl M, Lang D, Spannagl M, Appels R, Fischer I, Uauy C, Borrill P, Ramirez-Gonzalez RH, Appels R, Arnaud D, Chalabi S, Chalhoub B, Choulet F, Cory A, Datla R, Davey MW, Hayden M, Jacobs J, Lang D, Robinson SJ, Spannagl M, Steuernagel B, Tibbits J, Tiwari V, van Ex F, Wulff BBH, Pozniak CJ, Robinson SJ, Sharpe AG, Cory A, Benhamed M, Paux E, Bendahmane A, Concia L, Latrasse D, Rogers J, Jacobs J, Alaux M, Appels R, Bartoš J, Bellec A, Berges H, Doležel J, Feuillet C, Frenkel Z, Gill B, Korol A, Letellier T, Olsen OA, Šimková H, Singh K, Valárik M, van der Vossen E, Vautrin S, Weining S, Korol A, Frenkel Z, Fahima T, Glikson V, Raats D, Rogers J, Tiwari V, Gill B, Paux E, Poland J, Doležel J, Číhalíková J, Šimková H, Toegelová H, Vrána J, Sourdille P, Darrier B, Appels R, Spannagl M, Lang D, Fischer I, Ormanbekova D, Prade V, Barabaschi D, Cattivelli L, Hernandez P, Galvez S, Budak H, Steuernagel B, Jones JDG, Witek K, Wulff BBH, Yu G, Small I, Melonek J, Zhou R, Juhász A, Belova T, Appels R, Olsen OA, Kanyuka K, King R, Nilsen K, Walkowiak S, Pozniak CJ, Cuthbert R, Datla R, Knox R, Wiebe K, Xiang D, Rohde A, Golds T, Doležel J, Čížková J, Tibbits J, Budak H, Akpinar BA, Biyiklioglu S, Muehlbauer G, Poland J, Gao L, Gutierrez-Gonzalez J, N'Daiye A, Doležel J, Šimková H, Číhalíková J, Kubaláková M, Šafář J, Vrána J, Berges H, Bellec A, Vautrin S, Alaux M, Alfama F, Adam-Blondon AF, Flores R, Guerche C, Letellier T, Loaec M, Quesneville H, Pozniak CJ, Sharpe AG, Walkowiak S, Budak H, Condie J, Ens J, Koh C, Maclachlan R, Tan Y, Wicker T, Choulet F, Paux E, Alberti A, Aury JM, Balfourier F, Barbe V, Couloux A, Cruaud C, Labadie K, Mangenot S, Wincker P, Gill B, Kaur G, Luo M, Sehgal S, Singh K, Chhuneja P, Gupta OP, Jindal S, Kaur P, Malik P, Sharma P, Yadav B, Singh NK, Khurana J, Chaudhary C, Khurana P, Kumar V, Mahato A, Mathur S, Sevanthi A, Sharma N, Tomar RS, Rogers J, Jacobs J, Alaux M, Bellec A, Berges H, Doležel J, Feuillet C, Frenkel Z, Gill B, Korol A, van der Vossen E, Vautrin S, Gill B, Kaur G, Luo M, Sehgal S, Bartoš J, Holušová K, Plíhal O, Clark MD, Heavens D, Kettleborough G, Wright J, Valárik M, Abrouk M, Balcárková B, Holušová K, Hu Y, Luo M, Salina E, Ravin N, Skryabin K, Beletsky A, Kadnikov V, Mardanov A, Nesterov M, Rakitin A, Sergeeva E, Handa H, Kanamori H, Katagiri S, Kobayashi F, Nasuda S, Tanaka T, Wu J, Appels R, Hayden M, Keeble-Gagnère G, Rigault P, Tibbits J, Olsen OA, Belova T, Cattonaro F, Jiumeng M, Kugler K, Mayer KFX, Pfeifer M, Sandve S, Xun X, Zhan B, Šimková H, Abrouk M, Batley J, Bayer PE, Edwards D, Hayashi S, Toegelová H, Tulpová Z, Visendi P, Weining S, Cui L, Du X, Feng K, Nie X, Tong W, Wang L, Borrill P, Gundlach H, Galvez S, Kaithakottil G, Lang D, Lux T, Mascher M, Ormanbekova D, Prade V, Ramirez-Gonzalez RH, Spannagl M, Stein N, Uauy C, Venturini L, Stein N, Appels R, Eversole K, Rogers J, Borrill P, Cattivelli L, Choulet F, Hernandez P, Kanyuka K, Lang D, Mascher M, Nilsen K, Paux E, Pozniak CJ, Ramirez-Gonzalez RH, Šimková H, Small I, Spannagl M, Swarbreck D, Uauy C. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 2018; 361:361/6403/eaar7191. [PMID: 30115783 DOI: 10.1126/science.aar7191] [Citation(s) in RCA: 1481] [Impact Index Per Article: 246.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 07/11/2018] [Indexed: 12/14/2022]
Abstract
An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.
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Affiliation(s)
| | | | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Kellye Eversole
- International Wheat Genome Sequencing Consortium (IWGSC), 5207 Wyoming Road, Bethesda, MD 20816, USA. .,Eversole Associates, 5207 Wyoming Road, Bethesda, MD 20816, USA
| | - Catherine Feuillet
- Bayer CropScience, Crop Science Division, Research and Development, Innovation Centre, 3500 Paramount Parkway, Morrisville, NC 27560, USA
| | - Beat Keller
- Department of Plant and Microbial Biology, University of Zurich, Zollikerstrasse 107, 8008 Zurich, Switzerland
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany. .,The University of Western Australia (UWA), School of Agriculture and Environment, 35 Stirling Highway, Crawley, WA 6009, Australia
| | | | - Curtis J Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany. .,The University of Western Australia (UWA), School of Agriculture and Environment, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Assaf Distelfeld
- School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv 69978, Israel
| | - Kellye Eversole
- International Wheat Genome Sequencing Consortium (IWGSC), 5207 Wyoming Road, Bethesda, MD 20816, USA. .,Eversole Associates, 5207 Wyoming Road, Bethesda, MD 20816, USA
| | - Jesse Poland
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | - Gil Ronen
- NRGene Ltd., 5 Golda Meir Street, Ness Ziona 7403648, Israel
| | - Andrew G Sharpe
- University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | | | - Curtis Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Gil Ronen
- NRGene Ltd., 5 Golda Meir Street, Ness Ziona 7403648, Israel
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany. .,The University of Western Australia (UWA), School of Agriculture and Environment, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Omer Barad
- NRGene Ltd., 5 Golda Meir Street, Ness Ziona 7403648, Israel
| | - Kobi Baruch
- NRGene Ltd., 5 Golda Meir Street, Ness Ziona 7403648, Israel
| | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Andrew G Sharpe
- University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | - Gil Ben-Zvi
- NRGene Ltd., 5 Golda Meir Street, Ness Ziona 7403648, Israel
| | - Ambre-Aurore Josselin
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | | | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany. .,The University of Western Australia (UWA), School of Agriculture and Environment, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany
| | | | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | - François Balfourier
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Juan Gutierrez-Gonzalez
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, St. Paul, MN 55108, USA
| | - Matthew Hayden
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Ambre-Aurore Josselin
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - ChuShin Koh
- University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | - Gary Muehlbauer
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, St. Paul, MN 55108, USA
| | - Raj K Pasam
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Etienne Paux
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Curtis J Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Philippe Rigault
- GYDLE, Suite 220, 1135 Grande Allée, Ouest, Québec, QC G1S 1E7, Canada
| | - Andrew G Sharpe
- University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | - Josquin Tibbits
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Vijay Tiwari
- Plant Science and Landscape Architecture, University of Maryland, 4291 Fieldhouse Road, 2102 Plant Sciences Building, College Park, MD 20742, USA
| | | | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Ambre-Aurore Josselin
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | | | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Heidrun Gundlach
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Georg Haberer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Klaus F X Mayer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany
| | - Danara Ormanbekova
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,Department of Agricultural Sciences, University of Bologna, Viale Fanin, 44 40127 Bologna, Italy
| | - Etienne Paux
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Verena Prade
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Thomas Wicker
- Department of Plant and Microbial Biology, University of Zurich, Zollikerstrasse 107, 8008 Zurich, Switzerland
| | | | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Hélène Rimbert
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Marius Felder
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Nicolas Guilhot
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Heidrun Gundlach
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Georg Haberer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Jens Keilwagen
- Julius Kühn-Institut, Institute for Biosafety in Plant Biotechnology, Erwin-Baur-Str. 27, 06484 Quedlinburg, Germany
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Philippe Leroy
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Thomas Lux
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Klaus F X Mayer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany
| | - Sven Twardziok
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Luca Venturini
- Earlham Institute, Core Bioinformatics, Norwich NR4 7UZ, UK
| | | | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Hélène Rimbert
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Angéla Juhász
- Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia.,Agricultural Institute, MTA Centre for Agricultural Research, Applied Genomics Department, 2 Brunszvik Street, Martonvásár H 2462, Hungary
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | | | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Michael Abrouk
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic.,Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Georg Haberer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Klaus F X Mayer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany
| | - Thomas Wicker
- Department of Plant and Microbial Biology, University of Zurich, Zollikerstrasse 107, 8008 Zurich, Switzerland
| | | | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Thomas Wicker
- Department of Plant and Microbial Biology, University of Zurich, Zollikerstrasse 107, 8008 Zurich, Switzerland
| | - Heidrun Gundlach
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Iris Fischer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Cristobal Uauy
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | - Philippa Borrill
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | | | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Dominique Arnaud
- Institut National de la Recherche Agronomique (INRA), 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Smahane Chalabi
- Institut National de la Recherche Agronomique (INRA), 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Boulos Chalhoub
- Monsanto SAS, 28000 Boissay, France.,Institut National de la Recherche Agronomique (INRA), 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Aron Cory
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Raju Datla
- National Research Council Canada, Aquatic and Crop Resource Development, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada
| | - Mark W Davey
- Bayer CropScience, Trait Research, Innovation Center, Technologiepark 38, 9052 Gent, Belgium
| | - Matthew Hayden
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - John Jacobs
- Bayer CropScience, Trait Research, Innovation Center, Technologiepark 38, 9052 Gent, Belgium
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Stephen J Robinson
- Agriculture and Agri-Food Canada, Saskatoon Research and Development Centre, 107 Science Place, Saskatoon, SK S7N 0X2, Canada
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Josquin Tibbits
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Vijay Tiwari
- Plant Science and Landscape Architecture, University of Maryland, 4291 Fieldhouse Road, 2102 Plant Sciences Building, College Park, MD 20742, USA
| | - Fred van Ex
- Bayer CropScience, Trait Research, Innovation Center, Technologiepark 38, 9052 Gent, Belgium
| | - Brande B H Wulff
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | | | - Curtis J Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Stephen J Robinson
- Agriculture and Agri-Food Canada, Saskatoon Research and Development Centre, 107 Science Place, Saskatoon, SK S7N 0X2, Canada
| | - Andrew G Sharpe
- University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | - Aron Cory
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | | | - Moussa Benhamed
- Biology Department, Institute of Plant Sciences-Paris-Saclay, Bâtiment 630, rue de Noetzlin, Plateau du Moulon, CS80004, 91192 Gif-sur-Yvette Cedex, France
| | - Etienne Paux
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Abdelhafid Bendahmane
- Biology Department, Institute of Plant Sciences-Paris-Saclay, Bâtiment 630, rue de Noetzlin, Plateau du Moulon, CS80004, 91192 Gif-sur-Yvette Cedex, France
| | - Lorenzo Concia
- Biology Department, Institute of Plant Sciences-Paris-Saclay, Bâtiment 630, rue de Noetzlin, Plateau du Moulon, CS80004, 91192 Gif-sur-Yvette Cedex, France
| | - David Latrasse
- Biology Department, Institute of Plant Sciences-Paris-Saclay, Bâtiment 630, rue de Noetzlin, Plateau du Moulon, CS80004, 91192 Gif-sur-Yvette Cedex, France
| | | | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | - John Jacobs
- Bayer CropScience, Trait Research, Innovation Center, Technologiepark 38, 9052 Gent, Belgium
| | - Michael Alaux
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Jan Bartoš
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Arnaud Bellec
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Hélène Berges
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Catherine Feuillet
- Bayer CropScience, Crop Science Division, Research and Development, Innovation Centre, 3500 Paramount Parkway, Morrisville, NC 27560, USA
| | - Zeev Frenkel
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | - Bikram Gill
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Abraham Korol
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | | | - Odd-Arne Olsen
- Faculty of Bioscience, Department of Plant Science, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Kuldeep Singh
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Miroslav Valárik
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | | | - Sonia Vautrin
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Song Weining
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | | | - Abraham Korol
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | - Zeev Frenkel
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | - Tzion Fahima
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | | | - Dina Raats
- Earlham Institute, Core Bioinformatics, Norwich NR4 7UZ, UK
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | | | - Vijay Tiwari
- Plant Science and Landscape Architecture, University of Maryland, 4291 Fieldhouse Road, 2102 Plant Sciences Building, College Park, MD 20742, USA
| | - Bikram Gill
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Etienne Paux
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Jesse Poland
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | | | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jarmila Číhalíková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Helena Toegelová
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jan Vrána
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | | | | | - Benoit Darrier
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | | | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Iris Fischer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Danara Ormanbekova
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,Department of Agricultural Sciences, University of Bologna, Viale Fanin, 44 40127 Bologna, Italy
| | - Verena Prade
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Delfina Barabaschi
- Council for Agricultural Research and Economics (CREA), Research Centre for Genomics and Bioinformatics, via S. Protaso, 302, I -29017 Fiorenzuola d'Arda, Italy
| | - Luigi Cattivelli
- Council for Agricultural Research and Economics (CREA), Research Centre for Genomics and Bioinformatics, via S. Protaso, 302, I -29017 Fiorenzuola d'Arda, Italy
| | | | - Pilar Hernandez
- Instituto de Agricultura Sostenible (IAS-CSIC), Consejo Superior de Investigaciones Científicas, Alameda del Obispo s/n, 14004 Córdoba, Spain
| | - Sergio Galvez
- Universidad de Málaga, Lenguajes y Ciencias de la Computación, Campus de Teatinos, 29071 Málaga, Spain
| | - Hikmet Budak
- Plant Sciences and Plant Pathology, Cereal Genomics Lab, Montana State University, 412 Leon Johnson Hall, Bozeman, MT 59717, USA
| | | | | | | | - Kamil Witek
- The Sainsbury Laboratory, Norwich Research Park, Norwich NR4 7UH, UK
| | - Brande B H Wulff
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | - Guotai Yu
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | | | - Ian Small
- School of Molecular Sciences, ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Joanna Melonek
- School of Molecular Sciences, ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Ruonan Zhou
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany
| | | | - Angéla Juhász
- Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia.,Agricultural Institute, MTA Centre for Agricultural Research, Applied Genomics Department, 2 Brunszvik Street, Martonvásár H 2462, Hungary
| | - Tatiana Belova
- Faculty of Bioscience, Department of Plant Science, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Odd-Arne Olsen
- Faculty of Bioscience, Department of Plant Science, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | | | - Kostya Kanyuka
- Rothamsted Research, Biointeractions and Crop Protection, West Common, Harpenden AL5 2JQ, UK
| | - Robert King
- Rothamsted Research, Computational and Analytical Sciences, West Common, Harpenden AL5 2JQ, UK
| | | | - Kirby Nilsen
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Sean Walkowiak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Curtis J Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Richard Cuthbert
- Agriculture and Agri-Food Canada, Swift Current Research and Development Centre, Box 1030, Swift Current, SK S9H 3X2, Canada
| | - Raju Datla
- National Research Council Canada, Aquatic and Crop Resource Development, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada
| | - Ron Knox
- Agriculture and Agri-Food Canada, Swift Current Research and Development Centre, Box 1030, Swift Current, SK S9H 3X2, Canada
| | - Krysta Wiebe
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Daoquan Xiang
- National Research Council Canada, Aquatic and Crop Resource Development, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada
| | | | - Antje Rohde
- Bayer CropScience, Breeding and Trait Development, Technologiepark 38, 9052 Gent, Belgium
| | - Timothy Golds
- Bayer CropScience, Trait Research, Innovation Center, Technologiepark 38, 9052 Gent, Belgium
| | | | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jana Čížková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Josquin Tibbits
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | | | - Hikmet Budak
- Plant Sciences and Plant Pathology, Cereal Genomics Lab, Montana State University, 412 Leon Johnson Hall, Bozeman, MT 59717, USA
| | - Bala Ani Akpinar
- Plant Sciences and Plant Pathology, Cereal Genomics Lab, Montana State University, 412 Leon Johnson Hall, Bozeman, MT 59717, USA
| | - Sezgi Biyiklioglu
- Plant Sciences and Plant Pathology, Cereal Genomics Lab, Montana State University, 412 Leon Johnson Hall, Bozeman, MT 59717, USA
| | | | - Gary Muehlbauer
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, St. Paul, MN 55108, USA
| | - Jesse Poland
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Liangliang Gao
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Juan Gutierrez-Gonzalez
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, St. Paul, MN 55108, USA
| | - Amidou N'Daiye
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | | | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jarmila Číhalíková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Marie Kubaláková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jan Šafář
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jan Vrána
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | | | - Hélène Berges
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Arnaud Bellec
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Sonia Vautrin
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | | | - Michael Alaux
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | | | | | - Raphael Flores
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | - Claire Guerche
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | | | - Mikaël Loaec
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | | | | | | | - Curtis J Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Andrew G Sharpe
- National Research Council Canada, Aquatic and Crop Resource Development, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada.,University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | | | - Hikmet Budak
- Plant Sciences and Plant Pathology, Cereal Genomics Lab, Montana State University, 412 Leon Johnson Hall, Bozeman, MT 59717, USA
| | - Janet Condie
- National Research Council Canada, Aquatic and Crop Resource Development, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada
| | - Jennifer Ens
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - ChuShin Koh
- University of Saskatchewan, Global Institute for Food Security, 110 Gymnasium Place, Saskatoon, SK S7N 4J8, Canada
| | - Ron Maclachlan
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Yifang Tan
- National Research Council Canada, Aquatic and Crop Resource Development, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada
| | - Thomas Wicker
- Department of Plant and Microbial Biology, University of Zurich, Zollikerstrasse 107, 8008 Zurich, Switzerland
| | | | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Etienne Paux
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Adriana Alberti
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Jean-Marc Aury
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - François Balfourier
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Valérie Barbe
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Arnaud Couloux
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Corinne Cruaud
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Karine Labadie
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Sophie Mangenot
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France
| | - Patrick Wincker
- CEA-Institut de Biologie François-Jacob, Genoscope, 2 rue Gaston Crémieux, 91057 Evry Cedex, France.,CNRS, UMR 8030, CP5706, 91057 Evry, France.,Université d'Evry, UMR 8030, CP5706, 91057 Evry, France
| | | | - Bikram Gill
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Gaganpreet Kaur
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Mingcheng Luo
- Department of Plant Sciences, University of California, Davis, One Shield Avenue, Davis, CA 95617, USA
| | - Sunish Sehgal
- Agronomy Horticulture and Plant Science, South Dakota State University, 2108 Jackrabbit Drive, Brookings, SD 57006, USA
| | | | - Kuldeep Singh
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Parveen Chhuneja
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Om Prakash Gupta
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Suruchi Jindal
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Parampreet Kaur
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Palvi Malik
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Priti Sharma
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | - Bharat Yadav
- Punjab Agricultural University, Ludhiana, School of Agricultural Biotechnology, ICAR-National Bureau of Plant Genetic Resources, Dev Prakash Shastri Marg, New Delhi 110012, India
| | | | - Nagendra K Singh
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - JitendraP Khurana
- University of Delhi South Campus, Interdisciplinary Center for Plant Genomics and Department of Plant Molecular Biology, Benito Juarez Road, New Delhi 110021, India
| | - Chanderkant Chaudhary
- University of Delhi South Campus, Interdisciplinary Center for Plant Genomics and Department of Plant Molecular Biology, Benito Juarez Road, New Delhi 110021, India
| | - Paramjit Khurana
- University of Delhi South Campus, Interdisciplinary Center for Plant Genomics and Department of Plant Molecular Biology, Benito Juarez Road, New Delhi 110021, India
| | - Vinod Kumar
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - Ajay Mahato
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - Saloni Mathur
- University of Delhi South Campus, Interdisciplinary Center for Plant Genomics and Department of Plant Molecular Biology, Benito Juarez Road, New Delhi 110021, India
| | - Amitha Sevanthi
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - Naveen Sharma
- University of Delhi South Campus, Interdisciplinary Center for Plant Genomics and Department of Plant Molecular Biology, Benito Juarez Road, New Delhi 110021, India
| | - Ram Sewak Tomar
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | | | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | - John Jacobs
- Bayer CropScience, Trait Research, Innovation Center, Technologiepark 38, 9052 Gent, Belgium
| | - Michael Alaux
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | - Arnaud Bellec
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Hélène Berges
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Catherine Feuillet
- Bayer CropScience, Crop Science Division, Research and Development, Innovation Centre, 3500 Paramount Parkway, Morrisville, NC 27560, USA
| | - Zeev Frenkel
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | - Bikram Gill
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Abraham Korol
- University of Haifa, Institute of Evolution and the Department of Evolutionary and Environmental Biology, 199 Abba-Hushi Avenue, Mount Carmel, Haifa 3498838, Israel
| | | | - Sonia Vautrin
- INRA, CNRGV, chemin de Borde Rouge, CS 52627, 31326 Castanet-Tolosan Cedex, France
| | | | - Bikram Gill
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Gaganpreet Kaur
- Plant Pathology, Throckmorton Hall, Kansas State University, Manhattan, KS 66506, USA
| | - Mingcheng Luo
- Department of Plant Sciences, University of California, Davis, One Shield Avenue, Davis, CA 95617, USA
| | - Sunish Sehgal
- Agronomy Horticulture and Plant Science, South Dakota State University, 2108 Jackrabbit Drive, Brookings, SD 57006, USA
| | | | - Jan Bartoš
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Kateřina Holušová
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Ondřej Plíhal
- Department of Molecular Biology, Centre of the Region Haná for Biotechnological and Agricultural Research, Palacký University, Šlechtitelů 27, CZ-78371 Olomouc, Czech Republic
| | | | - Matthew D Clark
- Earlham Institute, Core Bioinformatics, Norwich NR4 7UZ, UK.,Department of Lifesciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK
| | - Darren Heavens
- Earlham Institute, Core Bioinformatics, Norwich NR4 7UZ, UK
| | | | - Jon Wright
- Earlham Institute, Core Bioinformatics, Norwich NR4 7UZ, UK
| | | | - Miroslav Valárik
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Michael Abrouk
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic.,Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Barbora Balcárková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Kateřina Holušová
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Yuqin Hu
- Department of Plant Sciences, University of California, Davis, One Shield Avenue, Davis, CA 95617, USA
| | - Mingcheng Luo
- Department of Plant Sciences, University of California, Davis, One Shield Avenue, Davis, CA 95617, USA
| | | | - Elena Salina
- The Federal Research Center Institute of Cytology and Genetics, SB RAS, pr. Lavrentyeva 10, Novosibirsk 630090, Russia
| | - Nikolai Ravin
- Research Center of Biotechnology of the Russian Academy of Sciences, Institute of Bioengineering, Leninsky Avenue 33, Building 2, Moscow 119071, Russia.,Faculty of Biology, Moscow State University, Leninskie Gory, 1, Moscow 119991, Russia
| | - Konstantin Skryabin
- Research Center of Biotechnology of the Russian Academy of Sciences, Institute of Bioengineering, Leninsky Avenue 33, Building 2, Moscow 119071, Russia.,Faculty of Biology, Moscow State University, Leninskie Gory, 1, Moscow 119991, Russia
| | - Alexey Beletsky
- Research Center of Biotechnology of the Russian Academy of Sciences, Institute of Bioengineering, Leninsky Avenue 33, Building 2, Moscow 119071, Russia
| | - Vitaly Kadnikov
- Research Center of Biotechnology of the Russian Academy of Sciences, Institute of Bioengineering, Leninsky Avenue 33, Building 2, Moscow 119071, Russia
| | - Andrey Mardanov
- Research Center of Biotechnology of the Russian Academy of Sciences, Institute of Bioengineering, Leninsky Avenue 33, Building 2, Moscow 119071, Russia
| | - Michail Nesterov
- The Federal Research Center Institute of Cytology and Genetics, SB RAS, pr. Lavrentyeva 10, Novosibirsk 630090, Russia
| | - Andrey Rakitin
- Research Center of Biotechnology of the Russian Academy of Sciences, Institute of Bioengineering, Leninsky Avenue 33, Building 2, Moscow 119071, Russia
| | - Ekaterina Sergeeva
- The Federal Research Center Institute of Cytology and Genetics, SB RAS, pr. Lavrentyeva 10, Novosibirsk 630090, Russia
| | | | - Hirokazu Handa
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Hiroyuki Kanamori
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Satoshi Katagiri
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Fuminori Kobayashi
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Shuhei Nasuda
- Graduate School of Agriculture, Kyoto University, Kitashirakawaoiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan
| | - Tsuyoshi Tanaka
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Jianzhong Wu
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | | | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Matthew Hayden
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Gabriel Keeble-Gagnère
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Philippe Rigault
- GYDLE, Suite 220, 1135 Grande Allée, Ouest, Québec, QC G1S 1E7, Canada
| | - Josquin Tibbits
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | | | - Odd-Arne Olsen
- Faculty of Bioscience, Department of Plant Science, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | - Tatiana Belova
- Faculty of Bioscience, Department of Plant Science, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | | | - Min Jiumeng
- BGI-Shenzhen, BGI Genomics, Building No. 7, BGI Park, No. 21 Hongan 3rd Street, Yantian District, Shenzhen 518083, China
| | - Karl Kugler
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Klaus F X Mayer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany
| | - Matthias Pfeifer
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Simen Sandve
- Faculty of Bioscience, Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | - Xu Xun
- BGI-Shenzhen, BGI Genomics, Yantian District, Shenzhen 518083, Guangdong, China
| | - Bujie Zhan
- Faculty of Bioscience, Department of Plant Science, Norwegian University of Life Sciences, Arboretveien 6, 1433 Ås, Norway
| | | | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Michael Abrouk
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic.,Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Jacqueline Batley
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA 6009, Australia
| | - Philipp E Bayer
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA 6009, Australia
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA 6009, Australia
| | - Satomi Hayashi
- Queensland University of Technology, Earth, Environmental and Biological Sciences, Brisbane, QLD 4001, Australia
| | - Helena Toegelová
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Zuzana Tulpová
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Paul Visendi
- University of Greenwich, Natural Resources Institute, Central Avenue, Chatham, Kent ME4 4TB, UK
| | | | - Song Weining
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | - Licao Cui
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | - Xianghong Du
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | - Kewei Feng
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | - Xiaojun Nie
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | - Wei Tong
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | - Le Wang
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712101, China
| | | | - Philippa Borrill
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | - Heidrun Gundlach
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Sergio Galvez
- Universidad de Málaga, Lenguajes y Ciencias de la Computación, Campus de Teatinos, 29071 Málaga, Spain
| | | | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Thomas Lux
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Danara Ormanbekova
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.,Department of Agricultural Sciences, University of Bologna, Viale Fanin, 44 40127 Bologna, Italy
| | - Verena Prade
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany. .,The University of Western Australia (UWA), School of Agriculture and Environment, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Cristobal Uauy
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | - Luca Venturini
- Earlham Institute, Core Bioinformatics, Norwich NR4 7UZ, UK
| | | | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany. .,The University of Western Australia (UWA), School of Agriculture and Environment, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia. .,Murdoch University, Australia-China Centre for Wheat Improvement, School of Veterinary and Life Sciences, 90 South Street, Murdoch, WA 6150, Australia
| | - Kellye Eversole
- International Wheat Genome Sequencing Consortium (IWGSC), 5207 Wyoming Road, Bethesda, MD 20816, USA. .,Eversole Associates, 5207 Wyoming Road, Bethesda, MD 20816, USA
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge CB23 1HE, UK
| | - Philippa Borrill
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
| | - Luigi Cattivelli
- Council for Agricultural Research and Economics (CREA), Research Centre for Genomics and Bioinformatics, via S. Protaso, 302, I -29017 Fiorenzuola d'Arda, Italy
| | - Frédéric Choulet
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Pilar Hernandez
- Instituto de Agricultura Sostenible (IAS-CSIC), Consejo Superior de Investigaciones Científicas, Alameda del Obispo s/n, 14004 Córdoba, Spain
| | - Kostya Kanyuka
- Rothamsted Research, Biointeractions and Crop Protection, West Common, Harpenden AL5 2JQ, UK
| | - Daniel Lang
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genebank, Corrensstr. 3, 06466 Stadt Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Kirby Nilsen
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | - Etienne Paux
- GDEC (Genetics, Diversity and Ecophysiology of Cereals), INRA, Université Clermont Auvergne (UCA), 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Curtis J Pozniak
- University of Saskatchewan, Crop Development Centre, Agriculture Building, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
| | | | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Ian Small
- School of Molecular Sciences, ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
| | - Manuel Spannagl
- Helmholtz Center Munich, Plant Genome and Systems Biology (PGSB), Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | | | - Cristobal Uauy
- John Innes Centre, Crop Genetics, Norwich Research Park, Norwich NR4 7UH, UK
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Singh G, Kuzniar A, van Mulligen EM, Gavai A, Bachem CW, Visser RGF, Finkers R. QTLTableMiner ++: semantic mining of QTL tables in scientific articles. BMC Bioinformatics 2018; 19:183. [PMID: 29801439 PMCID: PMC5970438 DOI: 10.1186/s12859-018-2165-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 04/25/2018] [Indexed: 11/11/2022] Open
Abstract
Background A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. Results The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. Conclusion QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats. Electronic supplementary material The online version of this article (10.1186/s12859-018-2165-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gurnoor Singh
- Plant Breeding, Wageningen University and Research, Wageningen, The Netherlands
| | - Arnold Kuzniar
- Netherlands eScience Center (NLeSC), Amsterdam, The Netherlands
| | - Erik M van Mulligen
- Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anand Gavai
- Netherlands eScience Center (NLeSC), Amsterdam, The Netherlands
| | - Christian W Bachem
- Plant Breeding, Wageningen University and Research, Wageningen, The Netherlands
| | - Richard G F Visser
- Plant Breeding, Wageningen University and Research, Wageningen, The Netherlands
| | - Richard Finkers
- Plant Breeding, Wageningen University and Research, Wageningen, The Netherlands.
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Stucky BJ, Guralnick R, Deck J, Denny EG, Bolmgren K, Walls R. The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data. FRONTIERS IN PLANT SCIENCE 2018; 9:517. [PMID: 29765382 PMCID: PMC5938398 DOI: 10.3389/fpls.2018.00517] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2018] [Accepted: 04/04/2018] [Indexed: 05/25/2023]
Abstract
Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.
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Affiliation(s)
- Brian J. Stucky
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States
| | - Rob Guralnick
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States
| | - John Deck
- Berkeley Natural History Museums, University of California, Berkeley, Berkeley, CA, United States
| | - Ellen G. Denny
- USA National Phenology Network, The University of Arizona, Tucson, AZ, United States
| | - Kjell Bolmgren
- Unit for Field-based Forest Research, Swedish University of Agricultural Sciences, Lammhult, Sweden
| | - Ramona Walls
- CyVerse, The University of Arizona, Tucson, AZ, United States
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Woldesemayat AA, Modise DM, Gemeildien J, Ndimba BK, Christoffels A. Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species. PLoS One 2018; 13:e0192678. [PMID: 29590108 PMCID: PMC5873934 DOI: 10.1371/journal.pone.0192678] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 01/29/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. METHODS In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. RESULTS Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs associated with different traits that are responsive to multiple stresses. Ontology mapping was used to validate the identified genes, while reconstruction of the phylogenetic tree was instrumental to infer the evolutionary relationship of the sorghum orthologs. The results also show specific genes responsible for various interrelated components of drought response mechanism such as drought tolerance, drought avoidance and drought escape. CONCLUSIONS We submit that this approach is novel and to our knowledge, has not been used previously in any other research; it enables us to perform cross-species queries for genes that are likely to be associated with multiple stress tolerance, as a means to identify novel targets for engineering stress resistance in sorghum and possibly, in other crop species.
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Affiliation(s)
- Adugna Abdi Woldesemayat
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Belleville, South Africa
- Department of Life and Consumer Sciences, College of Agriculture and Environmental Sciences, University of South Africa, Science Campus, Florida, Johannesburg, South Africa
- * E-mail: ,
| | - David M. Modise
- Department of Agriculture and Animal Health, College of Agriculture and Environmental Sciences, University of South Africa, Science Campus, Florida, Johannesburg, South Africa
| | - Junaid Gemeildien
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Belleville, South Africa
| | - Bongani K. Ndimba
- Department of Biotechnology, University of the Western Cape, Cape Town, Western Cape, South Africa
- Agricultural Research Council, Infruitech-Nietvoorbij, Stellenbosch, South Africa
| | - Alan Christoffels
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Belleville, South Africa
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Chiu B, Pyysalo S, Vulić I, Korhonen A. Bio-SimVerb and Bio-SimLex: wide-coverage evaluation sets of word similarity in biomedicine. BMC Bioinformatics 2018; 19:33. [PMID: 29402212 PMCID: PMC5800055 DOI: 10.1186/s12859-018-2039-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 01/24/2018] [Indexed: 01/10/2023] Open
Abstract
Background Word representations support a variety of Natural Language Processing (NLP) tasks. The quality of these representations is typically assessed by comparing the distances in the induced vector spaces against human similarity judgements. Whereas comprehensive evaluation resources have recently been developed for the general domain, similar resources for biomedicine currently suffer from the lack of coverage, both in terms of word types included and with respect to the semantic distinctions. Notably, verbs have been excluded, although they are essential for the interpretation of biomedical language. Further, current resources do not discern between semantic similarity and semantic relatedness, although this has been proven as an important predictor of the usefulness of word representations and their performance in downstream applications. Results We present two novel comprehensive resources targeting the evaluation of word representations in biomedicine. These resources, Bio-SimVerb and Bio-SimLex, address the previously mentioned problems, and can be used for evaluations of verb and noun representations respectively. In our experiments, we have computed the Pearson’s correlation between performances on intrinsic and extrinsic tasks using twelve popular state-of-the-art representation models (e.g. word2vec models). The intrinsic–extrinsic correlations using our datasets are notably higher than with previous intrinsic evaluation benchmarks such as UMNSRS and MayoSRS. In addition, when evaluating representation models for their abilities to capture verb and noun semantics individually, we show a considerable variation between performances across all models. Conclusion Bio-SimVerb and Bio-SimLex enable intrinsic evaluation of word representations. This evaluation can serve as a predictor of performance on various downstream tasks in the biomedical domain. The results on Bio-SimVerb and Bio-SimLex using standard word representation models highlight the importance of developing dedicated evaluation resources for NLP in biomedicine for particular word classes (e.g. verbs). These are needed to identify the most accurate methods for learning class-specific representations. Bio-SimVerb and Bio-SimLex are publicly available.
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Affiliation(s)
- Billy Chiu
- Language Technology Laboratory, DTAL, University of Cambridge, 9 West Road, Cambridge, CB39DB, UK.
| | - Sampo Pyysalo
- Language Technology Laboratory, DTAL, University of Cambridge, 9 West Road, Cambridge, CB39DB, UK
| | - Ivan Vulić
- Language Technology Laboratory, DTAL, University of Cambridge, 9 West Road, Cambridge, CB39DB, UK
| | - Anna Korhonen
- Language Technology Laboratory, DTAL, University of Cambridge, 9 West Road, Cambridge, CB39DB, UK
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Oliveira D, Pesquita C. Improving the interoperability of biomedical ontologies with compound alignments. J Biomed Semantics 2018; 9:1. [PMID: 29316968 PMCID: PMC5761129 DOI: 10.1186/s13326-017-0171-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Accepted: 12/21/2017] [Indexed: 12/29/2022] Open
Abstract
Background Ontologies are commonly used to annotate and help process life sciences data. Although their original goal is to facilitate integration and interoperability among heterogeneous data sources, when these sources are annotated with distinct ontologies, bridging this gap can be challenging. In the last decade, ontology matching systems have been evolving and are now capable of producing high-quality mappings for life sciences ontologies, usually limited to the equivalence between two ontologies. However, life sciences research is becoming increasingly transdisciplinary and integrative, fostering the need to develop matching strategies that are able to handle multiple ontologies and more complex relations between their concepts. Results We have developed ontology matching algorithms that are able to find compound mappings between multiple biomedical ontologies, in the form of ternary mappings, finding for instance that “aortic valve stenosis”(HP:0001650) is equivalent to the intersection between “aortic valve”(FMA:7236) and “constricted” (PATO:0001847). The algorithms take advantage of search space filtering based on partial mappings between ontology pairs, to be able to handle the increased computational demands. The evaluation of the algorithms has shown that they are able to produce meaningful results, with precision in the range of 60-92% for new mappings. The algorithms were also applied to the potential extension of logical definitions of the OBO and the matching of several plant-related ontologies. Conclusions This work is a first step towards finding more complex relations between multiple ontologies. The evaluation shows that the results produced are significant and that the algorithms could satisfy specific integration needs.
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Affiliation(s)
- Daniela Oliveira
- Insight Centre for Data Analytics, NUI Galway, Galway Business Park, Dangan, Galway, H91 AEX4, Ireland. .,LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal.
| | - Catia Pesquita
- LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal
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Harper L, Campbell J, Cannon EKS, Jung S, Poelchau M, Walls R, Andorf C, Arnaud E, Berardini TZ, Birkett C, Cannon S, Carson J, Condon B, Cooper L, Dunn N, Elsik CG, Farmer A, Ficklin SP, Grant D, Grau E, Herndon N, Hu ZL, Humann J, Jaiswal P, Jonquet C, Laporte MA, Larmande P, Lazo G, McCarthy F, Menda N, Mungall CJ, Munoz-Torres MC, Naithani S, Nelson R, Nesdill D, Park C, Reecy J, Reiser L, Sanderson LA, Sen TZ, Staton M, Subramaniam S, Tello-Ruiz MK, Unda V, Unni D, Wang L, Ware D, Wegrzyn J, Williams J, Woodhouse M, Yu J, Main D. AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture. Database (Oxford) 2018; 2018:5096675. [PMID: 30239679 PMCID: PMC6146126 DOI: 10.1093/database/bay088] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 07/19/2018] [Accepted: 07/30/2018] [Indexed: 01/07/2023]
Abstract
The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.
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Affiliation(s)
- Lisa Harper
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | | | - Ethalinda K S Cannon
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
- Computer Science, Iowa State University, Ames, IA, USA
| | - Sook Jung
- Horticulture, Washington State University, Pullman, WA, USA
| | - Monica Poelchau
- National Agricultural Library, USDA Agricultural Research Service, Beltsville, MD, USA
| | | | - Carson Andorf
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
- Computer Science, Iowa State University, Ames, IA, USA
| | - Elizabeth Arnaud
- Bioversity International, Informatics Unit, Conservation and Availability Programme, Parc Scientifique Agropolis II, Montpellier, France
| | - Tanya Z Berardini
- The Arabidopsis Information Resource, Phoenix Bioinformatics, Fremont, CA, USA
| | | | - Steve Cannon
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - James Carson
- Texas Advanced Computing Center, The University of Texas at Austin, Austin, TX, USA
| | - Bradford Condon
- Entomology and Plant Pathology, University of Tennessee Knoxville, Knoxville, TN, USA
| | - Laurel Cooper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Nathan Dunn
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Christine G Elsik
- Division of Animal Sciences and Division of Plant Sciences, University of Missouri, Columbia, MO, USA
| | - Andrew Farmer
- National Center for Genome Resources, Santa Fe, NM, USA
| | | | - David Grant
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Emily Grau
- National Center for Genome Resources, Santa Fe, NM, USA
| | - Nic Herndon
- Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA
| | - Zhi-Liang Hu
- Animal Science, Iowa State University, Ames, USA
| | - Jodi Humann
- Horticulture, Washington State University, Pullman, WA, USA
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Clement Jonquet
- Laboratory of Informatics, Robotics, Microelectronics of Montpellier, University of Montpellier & CNRS, Montpellier, France
| | - Marie-Angélique Laporte
- Bioversity International, Informatics Unit, Conservation and Availability Programme, Parc Scientifique Agropolis II, Montpellier, France
| | | | - Gerard Lazo
- Crop Improvement and Genetics Research Unit, USDA-ARS, Albany, CA, USA
| | - Fiona McCarthy
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, USA
| | | | | | | | - Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Rex Nelson
- Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
| | - Daureen Nesdill
- Marriott Library, University of Utah, Salt Lake City, UT, USA
| | - Carissa Park
- Animal Science, Iowa State University, Ames, USA
| | - James Reecy
- Animal Science, Iowa State University, Ames, USA
| | - Leonore Reiser
- The Arabidopsis Information Resource, Phoenix Bioinformatics, Fremont, CA, USA
| | | | - Taner Z Sen
- Crop Improvement and Genetics Research Unit, USDA-ARS, Albany, CA, USA
| | - Margaret Staton
- Entomology and Plant Pathology, University of Tennessee Knoxville, Knoxville, TN, USA
| | | | | | - Victor Unda
- Horticulture, Washington State University, Pullman, WA, USA
| | - Deepak Unni
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Liya Wang
- Plant Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Doreen Ware
- USDA, Plant, Soil and Nutrition Research, Ithaca, NY, USA
- Plant Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Jill Wegrzyn
- Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA
| | - Jason Williams
- Cold Spring Harbor Laboratory, DNA Learning Center, Cold Spring Harbor, NY, USA
| | - Margaret Woodhouse
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
| | - Jing Yu
- Horticulture, Washington State University, Pullman, WA, USA
| | - Doreen Main
- Horticulture, Washington State University, Pullman, WA, USA
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Abstract
The Gene Ontology Consortium (GOC) produces a wealth of resources widely used throughout the scientific community. In this chapter, we discuss the different ways in which researchers can access the resources of the GOC. We here share details about the mechanics of obtaining GO annotations, both by manually browsing, querying, and downloading data from the GO website, as well as computationally accessing the resources from the command line, including the ability to restrict the data being retrieved to subsets with only certain attributes.
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Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism. BMC SYSTEMS BIOLOGY 2017; 11:130. [PMID: 29322929 PMCID: PMC5763303 DOI: 10.1186/s12918-017-0510-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. An ontology for anti-rheumatism traditional Chinese drugs would strongly support the representation, analysis, and understanding of these drugs. Results In this study, we first systematically collected reported information about 26 traditional Chinese decoction pieces drugs, including their chemical ingredients and adverse events (AEs). By mostly reusing terms from existing ontologies (e.g., TCMDPO for traditional Chinese medicines, NCBITaxon for taxonomy, ChEBI for chemical elements, and OAE for adverse events) and making semantic axioms linking different entities, we developed the Ontology of Chinese Medicine for Rheumatism (OCMR) that includes over 3000 class terms. Our OCMR analysis found that these 26 traditional Chinese decoction pieces are made from anatomic entities (e.g., root and stem) from 3 Bilateria animals and 23 Mesangiospermae plants. Anti-inflammatory and antineoplastic roles are important for anti-rheumatism drugs. Using the total of 555 unique ChEBI chemical entities identified from these drugs, our ChEBI-based classification analysis identified 18 anti-inflammatory, 33 antineoplastic chemicals, and 9 chemicals (including 3 diterpenoids and 3 triterpenoids) having both anti-inflammatory and antineoplastic roles. Furthermore, our study detected 22 diterpenoids and 23 triterpenoids, including 16 pentacyclic triterpenoids that are likely bioactive against rheumatism. Six drugs were found to be associated with 184 unique AEs, including three AEs (i.e., dizziness, nausea and vomiting, and anorexia) each associated with 5 drugs. Several chemical entities are classified as neurotoxins (e.g., diethyl phthalate) and allergens (e.g., eugenol), which may explain the formation of some TCD AEs. The OCMR could be efficiently queried for useful information using SPARQL scripts. Conclusions The OCMR ontology was developed to systematically represent 26 traditional anti-rheumatism Chinese drugs and their related information. The OCMR analysis identified possible anti-rheumatism and AE mechanisms of these drugs. Our novel ontology-based approach can also be applied to systematic representation and analysis of other traditional Chinese drugs. Electronic supplementary material The online version of this article (10.1186/s12918-017-0510-5) contains supplementary material, which is available to authorized users.
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Sharma B, Kramer EM. Aquilegia B gene homologs promote petaloidy of the sepals and maintenance of the C domain boundary. EvoDevo 2017; 8:22. [PMID: 29209492 PMCID: PMC5704387 DOI: 10.1186/s13227-017-0085-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Accepted: 11/09/2017] [Indexed: 11/12/2022] Open
Abstract
The model Aquilegia coerulea x “Origami” possesses several interesting floral features, including petaloid sepals that are morphologically distinct from the true petals and a broad domain containing many whorls of stamens. We undertook the current study in an effort to understand the former trait, but additionally uncovered data that inform on the latter. The Aquilegia B gene homolog AqPI is shown to contribute to the production of anthocyanin in the first whorl sepals, although it has no major role in their morphology. Surprisingly, knockdown of AqPI in Aquilegia coerulea x “Origami” also reveals a role for the B class genes in maintaining the expression of the C gene homolog AqAG1 in the outer whorls of stamens. These findings suggest that the transference of pollinator function to the first whorl sepals included a non-homeotic recruitment of the B class genes to promote aspects of petaloidy. They also confirm results in several other Ranunculales that have revealed an unexpected regulatory connection between the B and C class genes.
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Affiliation(s)
- Bharti Sharma
- Department of Biological Sciences, California Polytechnic State University Pomona, 3801 West Temple Avenue, Pomona, CA 91768 USA
| | - Elena M Kramer
- Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Ave., Cambridge, MA 02138 USA
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Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, Prill RJ, Tripathi A, Gibbons SM, Ackermann G, Navas-Molina JA, Janssen S, Kopylova E, Vázquez-Baeza Y, González A, Morton JT, Mirarab S, Zech Xu Z, Jiang L, Haroon MF, Kanbar J, Zhu Q, Jin Song S, Kosciolek T, Bokulich NA, Lefler J, Brislawn CJ, Humphrey G, Owens SM, Hampton-Marcell J, Berg-Lyons D, McKenzie V, Fierer N, Fuhrman JA, Clauset A, Stevens RL, Shade A, Pollard KS, Goodwin KD, Jansson JK, Gilbert JA, Knight R. A communal catalogue reveals Earth's multiscale microbial diversity. Nature 2017; 551:457-463. [PMID: 29088705 PMCID: PMC6192678 DOI: 10.1038/nature24621] [Citation(s) in RCA: 1231] [Impact Index Per Article: 175.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 10/10/2017] [Indexed: 02/07/2023]
Abstract
Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.
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Affiliation(s)
- Luke R Thompson
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Biological Sciences and Northern Gulf Institute, University of Southern Mississippi, Hattiesburg, Mississippi, USA.,Ocean Chemistry and Ecosystems Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, stationed at Southwest Fisheries Science Center, La Jolla, California, USA
| | - Jon G Sanders
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Amnon Amir
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Joshua Ladau
- The Gladstone Institutes and University of California San Francisco, San Francisco, California, USA
| | - Kenneth J Locey
- Department of Biology, Indiana University, Bloomington, Indiana, USA
| | - Robert J Prill
- Industrial and Applied Genomics, IBM Almaden Research Center, San Jose, California, USA
| | - Anupriya Tripathi
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Division of Biological Sciences, University of California San Diego, La Jolla, California, USA.,Skaggs School of Pharmacy, University of California San Diego, La Jolla, California, USA
| | - Sean M Gibbons
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Gail Ackermann
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Jose A Navas-Molina
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
| | - Stefan Janssen
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Evguenia Kopylova
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Yoshiki Vázquez-Baeza
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
| | - Antonio González
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - James T Morton
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
| | - Siavash Mirarab
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California, USA
| | - Zhenjiang Zech Xu
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Lingjing Jiang
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California, USA
| | - Mohamed F Haroon
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Jad Kanbar
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Qiyun Zhu
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Se Jin Song
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Tomasz Kosciolek
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Nicholas A Bokulich
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, USA
| | - Joshua Lefler
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Colin J Brislawn
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Gregory Humphrey
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Sarah M Owens
- Biosciences Division, Argonne National Laboratory, Argonne, Illinois, USA
| | - Jarrad Hampton-Marcell
- Biosciences Division, Argonne National Laboratory, Argonne, Illinois, USA.,Department of Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Donna Berg-Lyons
- BioFrontiers Institute, University of Colorado, Boulder, Colorado, USA
| | - Valerie McKenzie
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, USA
| | - Noah Fierer
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, USA.,Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA
| | - Jed A Fuhrman
- Department of Biological Sciences, University of Southern California, Los Angeles, California, USA
| | - Aaron Clauset
- BioFrontiers Institute, University of Colorado, Boulder, Colorado, USA.,Department of Computer Science, University of Colorado, Boulder, Colorado, USA
| | - Rick L Stevens
- Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, Illinois, USA.,Department of Computer Science, University of Chicago, Chicago, Illinois, USA
| | - Ashley Shade
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, USA.,Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan, USA.,Program in Ecology, Evolutionary Biology and Behavior, Michigan State University, East Lansing, Michigan, USA
| | - Katherine S Pollard
- The Gladstone Institutes and University of California San Francisco, San Francisco, California, USA
| | - Kelly D Goodwin
- Ocean Chemistry and Ecosystems Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, stationed at Southwest Fisheries Science Center, La Jolla, California, USA
| | - Janet K Jansson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Jack A Gilbert
- Biosciences Division, Argonne National Laboratory, Argonne, Illinois, USA.,Department of Surgery, University of Chicago, Chicago, Illinois, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA.,Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
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49
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Salhi A, Negrão S, Essack M, Morton MJL, Bougouffa S, Razali R, Radovanovic A, Marchand B, Kulmanov M, Hoehndorf R, Tester M, Bajic VB. DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species. Sci Rep 2017; 7:5968. [PMID: 28729549 PMCID: PMC5519719 DOI: 10.1038/s41598-017-05448-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 05/25/2017] [Indexed: 12/29/2022] Open
Abstract
Tomato is the most economically important horticultural crop used as a model to study plant biology and particularly fruit development. Knowledge obtained from tomato research initiated improvements in tomato and, being transferrable to other such economically important crops, has led to a surge of tomato-related research and published literature. We developed DES-TOMATO knowledgebase (KB) for exploration of information related to tomato. Information exploration is enabled through terms from 26 dictionaries and combination of these terms. To illustrate the utility of DES-TOMATO, we provide several examples how one can efficiently use this KB to retrieve known or potentially novel information. DES-TOMATO is free for academic and nonprofit users and can be accessed at http://cbrc.kaust.edu.sa/des_tomato/, using any of the mainstream web browsers, including Firefox, Safari and Chrome.
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Affiliation(s)
- Adil Salhi
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
| | - Sónia Negrão
- King Abdullah University of Science and Technology (KAUST), Division of Biological and Environmental Sciences and Engineering, Thuwal, 23955-6900, Saudi Arabia
| | - Magbubah Essack
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
| | - Mitchell J L Morton
- King Abdullah University of Science and Technology (KAUST), Division of Biological and Environmental Sciences and Engineering, Thuwal, 23955-6900, Saudi Arabia
| | - Salim Bougouffa
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
| | - Rozaimi Razali
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
| | - Aleksandar Radovanovic
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
| | | | - Maxat Kulmanov
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
| | - Robert Hoehndorf
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia
- King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, 23955-6900, Saudi Arabia
| | - Mark Tester
- King Abdullah University of Science and Technology (KAUST), Division of Biological and Environmental Sciences and Engineering, Thuwal, 23955-6900, Saudi Arabia
| | - Vladimir B Bajic
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, 23955-6900, Saudi Arabia.
- King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, 23955-6900, Saudi Arabia.
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50
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Bolser DM, Staines DM, Perry E, Kersey PJ. Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomic Data. Methods Mol Biol 2017; 1533:1-31. [PMID: 27987162 DOI: 10.1007/978-1-4939-6658-5_1] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Ensembl Plants ( http://plants.ensembl.org ) is an integrative resource presenting genome-scale information for 39 sequenced plant species. Available data includes genome sequence, gene models, functional annotation, and polymorphic loci; for the latter, additional information including population structure, individual genotypes, linkage, and phenotype data is available for some species. Comparative data is also available, including genomic alignments and "gene trees," which show the inferred evolutionary history of each gene family represented in the resource. Access to the data is provided through a genome browser, which incorporates many specialist interfaces for different data types, through a variety of programmatic interfaces, and via a specialist data mining tool supporting rapid filtering and retrieval of bulk data. Genomic data from many non-plant species, including those of plant pathogens, pests, and pollinators, is also available via the same interfaces through other divisions of Ensembl.Ensembl Plants is updated 4-6 times a year and is developed in collaboration with our international partners in the Gramene ( http://www.gramene.org ) and transPLANT projects ( http://www.transplantdb.eu ).
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Affiliation(s)
- Dan M Bolser
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Daniel M Staines
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Emily Perry
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Paul J Kersey
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
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