From bits to bites: Advancement of the Germinate platform to support prebreeding informatics for crop wild relatives (original) (raw)
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2020
The efficient management and distribution of experimental data from pre-breeding projects is important to ensure uptake of valuable germplasm into breeding and research programmes. Being able to access and share this data in standard formats is essential in this process. The adoption of a common informatics platform for crops which may have limited resources brings economies of scale allowing common informatics components to be rolled out across multiple species. The close integration of such a platform with commonly used breeding software, visualization and analysis tools reduces the barrier for entry to researchers working on these data and provides a common framework to facilitate collaborations and data sharing. This work presents significant updates to the Germinate platform and highlights its value in distributing pre-breeding data for 14 crops as part of the project “Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives” (hereafter C...
PLANT PHYSIOLOGY, 2005
The extensive germplasm resource collections that are now available for major crop plants and their wild relatives will increasingly provide valuable biological and bioinformatics resources for plant physiologists and geneticists to dissect the molecular basis of key traits and to develop highly adapted plant material to sustain future breeding programs. A key to the efficient deployment of these resources is the development of information systems that will enable the collection and storage of biological information for these plant lines to be integrated with the molecular information that is now becoming available through the use of high-throughput genomics and post-genomics technologies. The GERMINATE database has been designed to hold a diverse variety of data types, ranging from molecular to phenotypic, and to allow querying between such data for any plant species. Data are stored in GERMINATE in a technology-independent manner, such that new technologies can be accommodated in the database as they emerge, without modification of the underlying schema. Users can access data in GERMINATE databases either via a lightweight Perl-CGI Web interface or by the more complex Genomic Diversity and Phenotype Connection software. GERMINATE is released under the GNU General Public License and is available at http:// germinate.scri.sari.ac.uk/germinate/.
2018
Background: With the advent of next-generation marker platforms and phenomics in crop breeding programs, the volume of both the genotypic and phenotypic data produced has increased exponentially. Often the data remain underutilized if not properly collated, managed and accessed. Effective management of the data is paramount to making sound and timely decision on cross planning in order to accelerate genetic gain (ΔG) in crops for disease resistance, agronomic and end-use quality traits. Results: To address the challenges in managing and efficient utilization of the sheer volume of data generated in a crop breeding program, we developed an electronic information system called the Crop Information Engine and Research Assistant (CIERA). The CIERA, written in Visual Basic, runs on the Microsoft Windows operating system and requires the .Net Framework 4.7 as well as the MySQL Community Server 5.7. The highly intuitive graphical user interface of CIERA includes user-friendly query tools to facilitate the collation of data across relevant phenotypic environments from its phenotypic data management database and can combine that information with the genealogy and genetic data from its genealogy management and genetic data management databases, respectively. Conclusions: Using CIERA, breeders can build a comprehensive profile of germplasm, within a few minutes, to assist them in planning crosses for enhancing genetic gain by selecting superior lines for crosses.
The Breeding Information Management System (BIMS): an online resource for crop breeding
Database
In this era of big data, breeding programs are producing ever larger amounts of data. This necessitates access to efficient management systems to keep track of cross, performance, pedigree, geographical and image-based data, as well as genotyping data. In this article, we report the progress on the Breeding Information Management System (BIMS), a free, secure and online breeding management system that allows breeders to store, manage, archive and analyze their private breeding data. BIMS is the first publicly available database system that enables individual breeders to integrate their private phenotypic and genotypic data with public data and, at the same time, have complete control of their own breeding data along with access to tools such as data import/export, data analysis and data archiving. The integration of breeding data with publicly available genomic and genetic data enhances genetic understanding of important traits and maximizes the marker-assisted breeding utility for ...
Breedbase: a digital ecosystem for modern plant breeding
G3 Genes|Genomes|Genetics
Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavaba...
The Hordeum Toolbox: The Barley Coordinated Agricultural Project Genotype and Phenotype Resource
The Plant Genome Journal, 2012
The use of DNA markers in public sector plant breeding is now the norm. Such markers are common across breeding programs and this commonality enables and enhances collaboration. Therefore, large collaborative research projects that measure several phenotypes across multiple environments coupled with the expanding amount of genotype data attainable with current marker technologies are on the rise and these projects demand effi cient data delivery. However, development of computational tools for advanced data integration, visualization, and analysis is still a bottleneck, even though these resources have the greatest potential impact for users who are extracting and developing hypothesis-based solutions. The Hordeum Toolbox (THT) was developed as a data resource for the Barley Coordinated Agricultural Project (CAP) with the novel capability of constructing user-defi ned downloadable sets of phenotype and/or genotype data for downstream analysis. Internal tools in THT enable users to create clusters of a selected group of lines based on genotype data, parse pedigrees, and select germplasm based on haplotype, phenotype, and agronomic properties. The Hordeum Toolbox can be adapted to breeding programs or collaborations to assist researchers in germplasm selection, genotype data visualization, and the integration of complex data sets for statistical analysis. T RADITIONALLY, plant breeders have collected phenotype data from breeding populations and used it to select for superior genotypes. Data access was limited to individual programs via spreadsheets or in-house databases. Th is approach has been successful in developing novel germplasm and varieties. However, with the exception of the few lines being grown in regional nurseries, the only scientists that had access to these extensive datasets were those that were intimately associated with the programs that generated the data. Th erefore, there was little understanding of the relationship of germplasm between programs, and the ability to share germplasm between programs in an intelligent manner was restricted. Webaccessible databases that contain data on all germplasm within a breeding program provide the opportunity
Open Source for seeds and genetic sequence data: Practical experience and future strategies
Perspective - Cirad
non-proprietary assets: it reverses the intellectual property rights rationale by introducing negotiated terms of access and use with the aim of keeping seeds in a protected commons. From a social standpoint, these commons are populated by community members who are willing to share freely, while excluding those who are not. Biologically, it creates a putative pool of crop varieties and associated germplasm with limitless potential for breeding, sharing and re-sharing as long as the commons protocols are upheld. With current technological innovations, new challenges are arising as seed information is increasingly exchanged without the biological material itself. This dematerialization is a mounting concern for local communities who have long experienced appropriation of genetic resources without recompense while relying on access and benefit-sharing regimes to contest unilateral appropriation. Open source experience drawn from the software industry might also benefit seed bioinformatics in this respect. This Perspective builds on the findings of the Open Source for Seeds (OSS) and Digital Sequence Information: Practical Experiences with OSS Implementation workshop (2017, CIRAD, Montpellier, France). It presents the open source seed principles based on practical experience from three opensource cases in the United States, Germany and East Africa. It discusses practical challenges in expanding open source to other types of subject matter and settings.
Frontiers in Physiology, 2012
The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http:// cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (https://www. integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP.