1
|
Jung S, Cheng CH, Lee T, Buble K, Humann J, Zheng P, Yu J, Main D. Building resource-efficient community databases using open-source software. Database (Oxford) 2025; 2025:baaf005. [PMID: 39937662 PMCID: PMC11833237 DOI: 10.1093/database/baaf005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2024] [Revised: 12/19/2024] [Accepted: 01/17/2025] [Indexed: 02/14/2025]
Abstract
The unprecedented volume of big data being routinely generated for nonmodel crop species, coupled with advanced technology enabling the use of big data in breeding, gives further impetus for the need to have access to crop community databases, where all relevant data are curated and integrated. Funding for such databases is, however, insufficient and intermittent, resulting in the data being underutilized. While increased awareness of the importance of funding databases is important, it is practically necessary to find a more efficient way to build a community database. To meet the need for integrated database resources for various crop genomics, genetics, and breeding research communities, we have built five crop databases over the last decade using an open-source database platform and software. We describe the system and methods used for database construction, curation, and analysis protocols, and the data and tools that are available in these five crop databases. Database URL: The Genome Database for Rosaceae (GDR, www.rosaceae.org), the Genome Database for Vaccinium (GDV, www.vaccinium.org), the Citrus Genome Database (CGD, www.citrusgenomedb.org), the Pulse Crop Database (PCD, www.pulsedb.org), and CottonGen (www.cottongen.org).
Collapse
Affiliation(s)
- Sook Jung
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Chun-Huai Cheng
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Taein Lee
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Katheryn Buble
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Jodi Humann
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Ping Zheng
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Jing Yu
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| | - Dorrie Main
- Department of Horticulture, Washington State University, 303c Plant Sciences Building, Pullman, WA 99164-6414, USA
| |
Collapse
|
2
|
Mansueto L, Kretzschmar T, Mauleon R, King GJ. Building a community-driven bioinformatics platform to facilitate Cannabis sativa multi-omics research. GIGABYTE 2024; 2024:gigabyte137. [PMID: 39469541 PMCID: PMC11515022 DOI: 10.46471/gigabyte.137] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Accepted: 10/06/2024] [Indexed: 10/30/2024] Open
Abstract
Global changes in cannabis legislation after decades of stringent regulation and heightened demand for its industrial and medicinal applications have spurred recent genetic and genomics research. An international research community emerged and identified the need for a web portal to host cannabis-specific datasets that seamlessly integrates multiple data sources and serves omics-type analyses, fostering information sharing. The Tripal platform was used to host public genome assemblies, gene annotations, quantitative trait loci and genetic maps, gene and protein expression data, metabolic profiles and their sample attributes. Single nucleotide polymorphisms were called using public resequencing datasets on three genomes. Additional applications, such as SNP-Seek and MapManJS, were embedded into Tripal. A multi-omics data integration web-service Application Programming Interface (API), developed on top of existing Tripal modules, returns generic tables of samples, properties and values. Use cases demonstrate the API's utility for various omics analyses, enabling researchers to perform multi-omics analyses efficiently. Availability and implementation The web portal can be accessed at www.icgrc.info.
Collapse
Affiliation(s)
- Locedie Mansueto
- Southern Cross University, Military Road, Lismore New South Wales, 2480, Australia
| | - Tobias Kretzschmar
- Southern Cross University, Military Road, Lismore New South Wales, 2480, Australia
| | - Ramil Mauleon
- Southern Cross University, Military Road, Lismore New South Wales, 2480, Australia
- International Rice Research Institute, Pili Drive, Los Baños Laguna, 4031, Philippines
| | - Graham J. King
- Southern Cross University, Military Road, Lismore New South Wales, 2480, Australia
- Recombics, Alstonville, New South Wales, 2480, Australia
| |
Collapse
|
3
|
Li X, Bai Y, Xu C, Liu S, Yu H, Kong L, Du S, Li Q. OysterDB: A Genome Database for Ostreidae. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2024; 26:827-834. [PMID: 38822152 DOI: 10.1007/s10126-024-10327-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 05/23/2024] [Indexed: 06/02/2024]
Abstract
The molluscan family Ostreidae, commonly known as oysters, is an important molluscan group due to its economic and ecological importance. In recent years, an abundance of genomic data of Ostreidae species has been generated and available in public domain. However, there is still a lack of a high-efficiency database platform to store and distribute these data with comprehensive tools. In this study, we developed an oyster genome database (OysterDB) to consolidate oyster genomic data. This database includes eight oyster genomes and 208,923 protein-coding gene annotations. Bioinformatic tools, such as BLAST and JBrowse, are integrated into the database to provide a user-friendly platform for homologous sequence searching, visualization of genomes, and screen for candidate gene information. Moreover, OysterDB will be continuously updated with ever-growing oyster genomic resources and facilitate future studies for comparative and functional genomic analysis of oysters ( http://oysterdb.com.cn/ ).
Collapse
Affiliation(s)
- Xinchun Li
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Yitian Bai
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Chengxun Xu
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Shikai Liu
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Hong Yu
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Lingfeng Kong
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Shaojun Du
- Institute of Marine and Environmental Technology, Department of Biochemistry and Molecular Biology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Qi Li
- Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China.
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China.
| |
Collapse
|
4
|
Meng T, Jiao H, Zhang Y, Zhou Y, Chen S, Wang X, Yang B, Sun J, Geng X, Ayhan DH, Guo L. FoPGDB: a pangenome database of Fusarium oxysporum, a cross-kingdom fungal pathogen. Database (Oxford) 2024; 2024:baae017. [PMID: 38537199 PMCID: PMC10972551 DOI: 10.1093/database/baae017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 01/09/2024] [Accepted: 02/22/2024] [Indexed: 03/23/2025]
Abstract
Pangenomes, capturing the genetic diversity of a species or genus, are essential to understanding the ecology, pathobiology and evolutionary mechanisms of fungi that cause infection in crops and humans. However, fungal pangenome databases remain unavailable. Here, we report the first fungal pangenome database, specifically for Fusarium oxysporum species complex (FOSC), a group of cross-kingdom pathogens causing devastating vascular wilt to over 100 plant species and life-threatening fusariosis to immunocompromised humans. The F. oxysporum Pangenome Database (FoPGDB) is a comprehensive resource integrating 35 high-quality FOSC genomes, coupled with robust analytical tools. FoPGDB allows for both gene-based and graph-based exploration of the F. oxysporum pangenome. It also curates a large repository of putative effector sequences, crucial for understanding the mechanisms of FOSC pathogenicity. With an assortment of functionalities including gene search, genomic variant exploration and tools for functional enrichment, FoPGDB provides a platform for in-depth investigations of the genetic diversity and adaptability of F. oxysporum. The modular and user-friendly interface ensures efficient data access and interpretation. FoPGDB promises to be a valuable resource for F. oxysporum research, contributing to our understanding of this pathogen's pangenomic landscape and aiding in the development of novel disease management strategies. Database URL: http://www.fopgdb.site.
Collapse
Affiliation(s)
- Tan Meng
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
- Department of Computer Science, The University of Hong Kong, Hong Kong 999077, China
| | - Hanqing Jiao
- Department of Computer Science, The University of Hong Kong, Hong Kong 999077, China
| | - Yi Zhang
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
- College of Information and Electrical Engineering, China Agricultural University, Haidian District, Beijing 100083, China
| | - Yi Zhou
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
- College of Information and Electrical Engineering, China Agricultural University, Haidian District, Beijing 100083, China
| | - Shaoying Chen
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Xinrui Wang
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Bowen Yang
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Jie Sun
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Xin Geng
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Dilay Hazal Ayhan
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Li Guo
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| |
Collapse
|
5
|
Hu J, Huang B, Yin H, Qi K, Jia Y, Xie Z, Gao Y, Li H, Li Q, Wang Z, Zou Y, Zhang S, Qiao X. PearMODB: a multiomics database for pear (Pyrus) genomics, genetics and breeding study. Database (Oxford) 2023; 2023:baad050. [PMID: 37410918 PMCID: PMC10325485 DOI: 10.1093/database/baad050] [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: 02/13/2023] [Revised: 06/06/2023] [Accepted: 06/21/2023] [Indexed: 07/08/2023]
Abstract
Pear (Pyrus ssp.) belongs to Rosaceae and is an important fruit tree widely cultivated around the world. Currently, challenges to cope with the burgeoning sets of multiomics data are rapidly increasing. Here, we constructed the Pear Multiomics Database (PearMODB) by integrating genome, transcriptome, epigenome and population variation data, and aimed to provide a portal for accessing and analyzing pear multiomics data. A variety of online tools were built including gene search, BLAST, JBrowse, expression heatmap, synteny analysis and primer design. The information of DNA methylation sites and single-nucleotide polymorphisms can be retrieved through the custom JBrowse, providing an opportunity to explore the genetic polymorphisms linked to phenotype variation. Moreover, different gene families involving transcription factors, transcription regulators and disease resistance (nucleotide-binding site leucine-rich repeat) were identified and compiled for quick search. In particular, biosynthetic gene clusters (BGCs) were identified in pear genomes, and specialized webpages were set up to show detailed information of BGCs, laying a foundation for studying metabolic diversity among different pear varieties. Overall, PearMODB provides an important platform for pear genomics, genetics and breeding studies. Database URL http://pearomics.njau.edu.cn.
Collapse
Affiliation(s)
- Jian Hu
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Baisha Huang
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Hao Yin
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Kaijie Qi
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuanyuan Jia
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
| | - Zhihua Xie
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuan Gao
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Hongxiang Li
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Qionghou Li
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Zewen Wang
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Ying Zou
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Shaoling Zhang
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| | - Xin Qiao
- Sanya Institute of Nanjing Agricultural University, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, No.1 Weigang, Nanjing 210095, China
- Jiangsu Engineering Research Center for Pear, Nanjing Agricultural University, Nanjing 210095, China
- College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
| |
Collapse
|
6
|
Volk GM, Gmitter FG, Krueger RR. Conserving Citrus Diversity: From Vavilov's Early Explorations to Genebanks around the World. PLANTS (BASEL, SWITZERLAND) 2023; 12:814. [PMID: 36840162 PMCID: PMC9964561 DOI: 10.3390/plants12040814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/06/2023] [Accepted: 02/09/2023] [Indexed: 06/18/2023]
Abstract
Citrus is among the most economically important fruit crops. Its vast species diversity and global production was observed by N.I. Vavilov during his international plant explorations from the early to mid-1900s. Currently, ex situ citrus collections located around the world conserve and protect citrus genetic resources, as revealed in a survey conducted in 2021. Responses were received from 43 collections in 27 countries, of which 35 provided data regarding collection composition, management practices, and security, as well as other information. The six largest citrus collections have between 1000 and 1735 accessions. The largest accession holdings are mandarins and sweet oranges, although all citrus fruit types are maintained: mandarin, sweet orange, lemon, pummelo, grapefruit, hybrids, lime, sour orange, citron, kumquat, papeda, finger lime, and crop wild relatives. Diseases pose significant threats to collections, though some collections are maintained in a clean-plant state as a result of intensive sanitation efforts. National and regional quarantine regulations often limit the export and import of citrus plants or propagative materials, thus limiting the availability of materials at an international level. Resources, both financial and human, are necessary to ensure the long-term safety and security of citrus collections on a global scale. Future efforts to develop citrus genebanking communities will provide opportunities for improved conservation, as well as collaborations and training.
Collapse
Affiliation(s)
- Gayle M. Volk
- USDA-ARS National Laboratory for Genetic Resources Preservation, 1111 S. Mason St., Fort Collins, CO 80521, USA
| | - Frederick G. Gmitter
- Citrus Research and Education Center (CREC), Institute of Food and Agricultural Sciences (IFAS), University of Florida, Lake Alfred, FL 33850, USA
| | - Robert R. Krueger
- USDA-ARS National Germplasm Repository for Citrus and Dates, 1060 Martin Luther King Blvd., Riverside, CA 92507, USA
| |
Collapse
|
7
|
Xu Y, Zhang X, Li H, Zheng H, Zhang J, Olsen MS, Varshney RK, Prasanna BM, Qian Q. Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction. MOLECULAR PLANT 2022; 15:1664-1695. [PMID: 36081348 DOI: 10.1016/j.molp.2022.09.001] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 08/20/2022] [Accepted: 09/02/2022] [Indexed: 05/12/2023]
Abstract
The first paradigm of plant breeding involves direct selection-based phenotypic observation, followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and, more recently, by incorporation of molecular marker genotypes. However, plant performance or phenotype (P) is determined by the combined effects of genotype (G), envirotype (E), and genotype by environment interaction (GEI). Phenotypes can be predicted more precisely by training a model using data collected from multiple sources, including spatiotemporal omics (genomics, phenomics, and enviromics across time and space). Integration of 3D information profiles (G-P-E), each with multidimensionality, provides predictive breeding with both tremendous opportunities and great challenges. Here, we first review innovative technologies for predictive breeding. We then evaluate multidimensional information profiles that can be integrated with a predictive breeding strategy, particularly envirotypic data, which have largely been neglected in data collection and are nearly untouched in model construction. We propose a smart breeding scheme, integrated genomic-enviromic prediction (iGEP), as an extension of genomic prediction, using integrated multiomics information, big data technology, and artificial intelligence (mainly focused on machine and deep learning). We discuss how to implement iGEP, including spatiotemporal models, environmental indices, factorial and spatiotemporal structure of plant breeding data, and cross-species prediction. A strategy is then proposed for prediction-based crop redesign at both the macro (individual, population, and species) and micro (gene, metabolism, and network) scales. Finally, we provide perspectives on translating smart breeding into genetic gain through integrative breeding platforms and open-source breeding initiatives. We call for coordinated efforts in smart breeding through iGEP, institutional partnerships, and innovative technological support.
Collapse
Affiliation(s)
- Yunbi Xu
- Institute of Crop Sciences, CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China; CIMMYT-China Tropical Maize Research Center, School of Food Science and Engineering, Foshan University, Foshan, Guangdong 528231, China; Peking University Institute of Advanced Agricultural Sciences, Weifang, Shandong 261325, China.
| | - Xingping Zhang
- Peking University Institute of Advanced Agricultural Sciences, Weifang, Shandong 261325, China
| | - Huihui Li
- Institute of Crop Sciences, CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan 572024, China
| | - Hongjian Zheng
- CIMMYT-China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai 201400, China
| | - Jianan Zhang
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang, Hebei 050035, China
| | - Michael S Olsen
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF Campus, United Nations Avenue, Nairobi, Kenya
| | - Rajeev K Varshney
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Australia
| | - Boddupalli M Prasanna
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF Campus, United Nations Avenue, Nairobi, Kenya
| | - Qian Qian
- Institute of Crop Sciences, CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| |
Collapse
|
8
|
Droc G, Martin G, Guignon V, Summo M, Sempéré G, Durant E, Soriano A, Baurens FC, Cenci A, Breton C, Shah T, Aury JM, Ge XJ, Harrison PH, Yahiaoui N, D’Hont A, Rouard M. The banana genome hub: a community database for genomics in the Musaceae. HORTICULTURE RESEARCH 2022; 9:uhac221. [PMID: 36479579 PMCID: PMC9720444 DOI: 10.1093/hr/uhac221] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/22/2022] [Indexed: 06/17/2023]
Abstract
The Banana Genome Hub provides centralized access for genome assemblies, annotations, and the extensive related omics resources available for bananas and banana relatives. A series of tools and unique interfaces are implemented to harness the potential of genomics in bananas, leveraging the power of comparative analysis, while recognizing the differences between datasets. Besides effective genomic tools like BLAST and the JBrowse genome browser, additional interfaces enable advanced gene search and gene family analyses including multiple alignments and phylogenies. A synteny viewer enables the comparison of genome structures between chromosome-scale assemblies. Interfaces for differential expression analyses, metabolic pathways and GO enrichment were also added. A catalogue of variants spanning the banana diversity is made available for exploration, filtering, and export to a wide variety of software. Furthermore, we implemented new ways to graphically explore gene presence-absence in pangenomes as well as genome ancestry mosaics for cultivated bananas. Besides, to guide the community in future sequencing efforts, we provide recommendations for nomenclature of locus tags and a curated list of public genomic resources (assemblies, resequencing, high density genotyping) and upcoming resources-planned, ongoing or not yet public. The Banana Genome Hub aims at supporting the banana scientific community for basic, translational, and applied research and can be accessed at https://banana-genome-hub.southgreen.fr.
Collapse
Affiliation(s)
| | - Guillaume Martin
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
| | - Valentin Guignon
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
| | - Marilyne Summo
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
| | - Guilhem Sempéré
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- CIRAD, UMR INTERTRYP, F-34398 Montpellier, France
- INTERTRYP, Université de Montpellier, CIRAD, IRD, 34398 Montpellier, France
| | - Eloi Durant
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Syngenta Seeds SAS, Saint-Sauveur, 31790, France
- DIADE, Univ Montpellier, CIRAD, IRD, Montpellier, 34830, France
| | - Alexandre Soriano
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
| | - Franc-Christophe Baurens
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Alberto Cenci
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
| | - Catherine Breton
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
| | | | - Jean-Marc Aury
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Xue-Jun Ge
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510520, China
- Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou 510520, China
| | - Pat Heslop Harrison
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510520, China
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK
| | - Nabila Yahiaoui
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Angélique D’Hont
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | | |
Collapse
|
9
|
Yu J, Jung S, Cheng CH, Lee T, Zheng P, Buble K, Crabb J, Humann J, Hough H, Jones D, Campbell JT, Udall J, Main D. CottonGen: The Community Database for Cotton Genomics, Genetics, and Breeding Research. PLANTS (BASEL, SWITZERLAND) 2021; 10:plants10122805. [PMID: 34961276 PMCID: PMC8705096 DOI: 10.3390/plants10122805] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/11/2021] [Accepted: 12/12/2021] [Indexed: 05/12/2023]
Abstract
Over the last eight years, the volume of whole genome, gene expression, SNP genotyping, and phenotype data generated by the cotton research community has exponentially increased. The efficient utilization/re-utilization of these complex and large datasets for knowledge discovery, translation, and application in crop improvement requires them to be curated, integrated with other types of data, and made available for access and analysis through efficient online search tools. Initiated in 2012, CottonGen is an online community database providing access to integrated peer-reviewed cotton genomic, genetic, and breeding data, and analysis tools. Used by cotton researchers worldwide, and managed by experts with crop-specific knowledge, it continuous to be the logical choice to integrate new data and provide necessary interfaces for information retrieval. The repository in CottonGen contains colleague, gene, genome, genotype, germplasm, map, marker, metabolite, phenotype, publication, QTL, species, transcriptome, and trait data curated by the CottonGen team. The number of data entries housed in CottonGen has increased dramatically, for example, since 2014 there has been an 18-fold increase in genes/mRNAs, a 23-fold increase in whole genomes, and a 372-fold increase in genotype data. New tools include a genetic map viewer, a genome browser, a synteny viewer, a metabolite pathways browser, sequence retrieval, BLAST, and a breeding information management system (BIMS), as well as various search pages for new data types. CottonGen serves as the home to the International Cotton Genome Initiative, managing its elections and serving as a communication and coordination hub for the community. With its extensive curation and integration of data and online tools, CottonGen will continue to facilitate utilization of its critical resources to empower research for cotton crop improvement.
Collapse
Affiliation(s)
- Jing Yu
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Sook Jung
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Chun-Huai Cheng
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Taein Lee
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Ping Zheng
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Katheryn Buble
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - James Crabb
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Jodi Humann
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Heidi Hough
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
| | - Don Jones
- Cotton Incorporated, Cary, NC 27513, USA;
| | - J. Todd Campbell
- The Agricultural Research Service of U.S. Department of Agriculture, Florence, SC 29501, USA;
| | - Josh Udall
- The Agricultural Research Service of U.S. Department of Agriculture, College Station, TX 77845, USA;
| | - Dorrie Main
- Department of Horticulture, Washington State University, Pullman, WA 99164, USA; (J.Y.); (S.J.); (C.-H.C.); (T.L.); (P.Z.); (K.B.); (J.C.); (J.H.); (H.H.)
- Correspondence: ; Tel.: +1-509-335-2774
| |
Collapse
|