Connecting data for consumer preferences, food quality, and breeding in support of market-oriented breeding of root, tuber, and banana crops.

The 5-year project 'Breeding roots, tubers and banana products for end user preferences' (RTBfoods) focused on collecting consumers' preferences on 12 food products to guide breeding programmes. It involved multidisciplinary teams from Africa, Latin America, and Europe. Diverse data types were generated on preferred qualities of users (farmers, family and entrepreneurial processors, traders or retailers, and consumers). Country-based target product profiles were produced with a comprehensive market analysis, disaggregating gender's role and preferences, providing prioritised lists of traits for the development of new plant varieties. We describe the approach taken to create, in the roots, tubers, and banana breeding databases, a centralised and meaningful open access to sensory information on food products and genotypes. Biochemical, instrumental textural, and sensory analysis data are then directly connected to the specific plant record while user survey data, bearing personal information, were analysed, anonymised, and uploaded in a repository. Names and descriptions of food quality traits were added into the Crop Ontology for labelling data in the databases, along with the various methods of measurement used by the project. The development and application of standard operating procedures, data templates, and adapted trait ontologies improved the data quality and its format, enabling the linking of these to the plant material studied when uploaded in the breeding databases or in repositories. Some modifications to the database model were necessary to accommodate the food sensory traits and sensory panel trials. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Breedbase: a digital ecosystem for modern plant breeding.

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://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.

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.

Exploiting the diversity of tomato: the development of a phenotypically and genetically detailed germplasm collection.

A collection of 163 accessions, including Solanum pimpinellifolium, Solanum lycopersicum var. cerasiforme and Solanum lycopersicum var. lycopersicum, was selected to represent the genetic and morphological variability of tomato at its centers of origin and domestication: Andean regions of Peru and Ecuador and Mesoamerica. The collection is enriched with S. lycopersicum var. cerasiforme from the Amazonian region that has not been analyzed previously nor used extensively. The collection has been morphologically characterized showing diversity for fruit, flower and vegetative traits. Their genomes were sequenced in the Varitome project and are publicly available (solgenomics.net/projects/varitome). The identified SNPs have been annotated with respect to their impact and a total number of 37,974 out of 19,364,146 SNPs have been described as high impact by the SnpEeff analysis. GWAS has shown associations for different traits, demonstrating the potential of this collection for this kind of analysis. We have not only identified known QTLs and genes, but also new regions associated with traits such as fruit color, number of flowers per inflorescence or inflorescence architecture. To speed up and facilitate the use of this information, F2 populations were constructed by crossing the whole collection with three different parents. This F2 collection is useful for testing SNPs identified by GWAs, selection sweeps or any other candidate gene. All data is available on Solanaceae Genomics Network and the accession and F2 seeds are freely available at COMAV and at TGRC genebanks. All these resources together make this collection a good candidate for genetic studies.

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture.

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.

Linkage between the I-3 gene for resistance to Fusarium wilt race 3 and increased sensitivity to bacterial spot in tomato.

KEY MESSAGE: The negative association between the I - 3 gene and increased sensitivity to bacterial spot is due to linkage drag (not pleiotropy) and may be remedied by reducing the introgression size. Fusarium wilt is one of the most serious diseases of tomato (Solanum lycopersicum L.) throughout the world. There are three races of the pathogen (races 1, 2 and 3), and the deployment of three single, dominant resistance genes corresponding to each of these has been the primary means of controlling the disease. The I-3 gene was introgressed from S. pennellii and confers resistance to race 3. Although I-3 provides effective control, it is negatively associated with several horticultural traits, including increased sensitivity to bacterial spot disease (Xanthomonas spp.). To test the hypothesis that this association is due to linkage with unfavorable alleles rather than to pleiotropy, we used a map-based approach to develop a collection of recombinant inbred lines varying for portions of I-3 introgression. Progeny of recombinants were evaluated for bacterial spot severity in the field for three seasons, and disease severities were compared between I-3 introgression haplotypes for each recombinant. Results indicated that increased sensitivity to bacterial spot is not associated with the I-3 gene, but rather with an upstream region of the introgression. A survey of public and private inbred lines and hybrids indicates that the majority of modern I-3 germplasm contains a similarly sized introgression for which the negative association with bacterial spot likely persists. In light of this, it is expected that the development and utilization of a reduced I-3 introgression will significantly improve breeding efforts for resistance to Fusarium wilt race 3.

Comparative genomics and phylogenetic discordance of cultivated tomato and close wild relatives.

Background. Studies of ancestry are difficult in the tomato because it crosses with many wild relatives and species in the tomato clade that have diverged very recently. As a result, the phylogeny in relation to its closest relatives remains uncertain. By using the coding sequence from Solanum lycopersicum, S. galapagense, S. pimpinellifolium, S. corneliomuelleri, and S. tuberosum and the genomic sequence from S. lycopersicum 'Heinz', an heirloom line, S. lycopersicum 'Yellow Pear', and two of cultivated tomato's closest relatives, S. galapagense and S. pimpinellifolium, we have aimed to resolve the phylogenies of these closely related species as well as identify phylogenetic discordance in the reference cultivated tomato. Results. Divergence date estimates suggest that the divergence of S. lycopersicum, S. galapagense, and S. pimpinellifolium happened less than 0.5 MYA. Phylogenies based on 8,857 coding sequences support grouping of S. lycopersicum and S. galapagense, although two secondary trees are also highly represented. A total of 25 genes in our analysis had sites with evidence of positive selection along the S. lycopersicum lineage. Whole genome phylogenies showed that while incongruence is prevalent in genomic comparisons between these genotypes, likely as a result of introgression and incomplete lineage sorting, a primary phylogenetic history was strongly supported. Conclusions. Based on analysis of these genotypes, S. galapagense appears to be closely related to S. lycopersicum, suggesting they had a common ancestor prior to the arrival of an S. galapagense ancestor to the Galápagos Islands, but after divergence of the sequenced S. pimpinellifolium. Genes showing selection along the S. lycopersicum lineage may be important in domestication or selection occurring post-domestication. Further analysis of intraspecific data in these species will help to establish the evolutionary history of cultivated tomato. The use of an heirloom line is helpful in deducing true phylogenetic information of S. lycopersicum and identifying regions of introgression from wild species.

An ontology approach to comparative phenomics in plants.

BACKGROUND: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. RESULTS: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. CONCLUSIONS: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics that enhances the utility of model genetic organisms and can be readily applied to species with fewer genetic resources and less well-characterized genomes. In addition, these tools should enhance future efforts to explore the relationships among phenotypic similarity, gene function, and sequence similarity in plants, and to make genotype-to-phenotype predictions relevant to plant biology, crop improvement, and potentially even human health.

The Sol Genomics Network (SGN)--from genotype to phenotype to breeding.

The Sol Genomics Network (SGN, http://solgenomics.net) is a web portal with genomic and phenotypic data, and analysis tools for the Solanaceae family and close relatives. SGN hosts whole genome data for an increasing number of Solanaceae family members including tomato, potato, pepper, eggplant, tobacco and Nicotiana benthamiana. The database also stores loci and phenotype data, which researchers can upload and edit with user-friendly web interfaces. Tools such as BLAST, GBrowse and JBrowse for browsing genomes, expression and map data viewers, a locus community annotation system and a QTL analysis tools are available. A new tool was recently implemented to improve Virus-Induced Gene Silencing (VIGS) constructs called the SGN VIGS tool. With the growing genomic and phenotypic data in the database, SGN is now advancing to develop new web-based breeding tools and implement the code and database structure for other species or clade-specific databases.

solGS: a web-based tool for genomic selection.

BACKGROUND: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. RESULTS: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. CONCLUSIONS: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.

Analysis of wild-species introgressions in tomato inbreds uncovers ancestral origins.

BACKGROUND: Decades of intensive tomato breeding using wild-species germplasm have resulted in the genomes of domesticated germplasm (Solanum lycopersicum) being intertwined with introgressions from their wild relatives. Comparative analysis of genomes among cultivated tomatoes and wild species that have contributed genetic variation can help identify desirable genes, such as those conferring disease resistance. The ability to identify introgression position, borders, and contents can reveal ancestral origins and facilitate harnessing of wild variation in crop breeding. RESULTS: Here we present the whole-genome sequences of two tomato inbreds, Gh13 and BTI-87, both carrying the begomovirus resistance locus Ty-3 introgressed from wild tomato species. Introgressions of different sizes on chromosome 6 of Gh13 and BTI-87, both corresponding to the Ty-3 region, were identified as from a source close to the wild species S. chilense. Other introgressions were identified throughout the genomes of the inbreds and showed major differences in the breeding pedigrees of the two lines. Interestingly, additional large introgressions from the close tomato relative S. pimpinellifolium were identified in both lines. Some of the polymorphic regions were attributed to introgressions in the reference Heinz 1706 genome, indicating wild genome sequences in the reference tomato genome. CONCLUSIONS: The methods developed in this work can be used to delineate genome introgressions, and subsequently contribute to development of molecular markers to aid phenotypic selection, fine mapping and discovery of candidate genes for important phenotypes, and for identification of novel variation for tomato improvement. These universal methods can easily be applied to other crop plants.

From manual curation to visualization of gene families and networks across Solanaceae plant species.

High-quality manual annotation methods and practices need to be scaled to the increased rate of genomic data production. Curation based on gene families and gene networks is one approach that can significantly increase both curation efficiency and quality. The Sol Genomics Network (SGN; http://solgenomics.net) is a comparative genomics platform, with genetic, genomic and phenotypic information of the Solanaceae family and its closely related species that incorporates a community-based gene and phenotype curation system. In this article, we describe a manual curation system for gene families aimed at facilitating curation, querying and visualization of gene interaction patterns underlying complex biological processes, including an interface for efficiently capturing information from experiments with large data sets reported in the literature. Well-annotated multigene families are useful for further exploration of genome organization and gene evolution across species. As an example, we illustrate the system with the multigene transcription factor families, WRKY and Small Auxin Up-regulated RNA (SAUR), which both play important roles in responding to abiotic stresses in plants. Database URL: http://solgenomics.net/

The plant ontology as a tool for comparative plant anatomy and genomic analyses.

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly available, collaborative effort to develop and maintain a controlled, structured vocabulary ('ontology') of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multispecies anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to >110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and quantitative trait loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs.

The Chado Natural Diversity module: a new generic database schema for large-scale phenotyping and genotyping data.

Linking phenotypic with genotypic diversity has become a major requirement for basic and applied genome-centric biological research. To meet this need, a comprehensive database backend for efficiently storing, querying and analyzing large experimental data sets is necessary. Chado, a generic, modular, community-based database schema is widely used in the biological community to store information associated with genome sequence data. To meet the need to also accommodate large-scale phenotyping and genotyping projects, a new Chado module called Natural Diversity has been developed. The module strictly adheres to the Chado remit of being generic and ontology driven. The flexibility of the new module is demonstrated in its capacity to store any type of experiment that either uses or generates specimens or stock organisms. Experiments may be grouped or structured hierarchically, whereas any kind of biological entity can be stored as the observed unit, from a specimen to be used in genotyping or phenotyping experiments, to a group of species collected in the field that will undergo further lab analysis. We describe details of the Natural Diversity module, including the design approach, the relational schema and use cases implemented in several databases.

The Sol Genomics Network (solgenomics.net): growing tomatoes using Perl.

The Sol Genomics Network (SGN; http://solgenomics.net/) is a clade-oriented database (COD) containing biological data for species in the Solanaceae and their close relatives, with data types ranging from chromosomes and genes to phenotypes and accessions. SGN hosts several genome maps and sequences, including a pre-release of the tomato (Solanum lycopersicum cv Heinz 1706) reference genome. A new transcriptome component has been added to store RNA-seq and microarray data. SGN is also an open source software project, continuously developing and improving a complex system for storing, integrating and analyzing data. All code and development work is publicly visible on GitHub (http://github.com). The database architecture combines SGN-specific schemas and the community-developed Chado schema (http://gmod.org/wiki/Chado) for compatibility with other genome databases. The SGN curation model is community-driven, allowing researchers to add and edit information using simple web tools. Currently, over a hundred community annotators help curate the database. SGN can be accessed at http://solgenomics.net/.

solQTL: a tool for QTL analysis, visualization and linking to genomes at SGN database.

BACKGROUND: A common approach to understanding the genetic basis of complex traits is through identification of associated quantitative trait loci (QTL). Fine mapping QTLs requires several generations of backcrosses and analysis of large populations, which is time-consuming and costly effort. Furthermore, as entire genomes are being sequenced and an increasing amount of genetic and expression data are being generated, a challenge remains: linking phenotypic variation to the underlying genomic variation. To identify candidate genes and understand the molecular basis underlying the phenotypic variation of traits, bioinformatic approaches are needed to exploit information such as genetic map, expression and whole genome sequence data of organisms in biological databases. DESCRIPTION: The Sol Genomics Network (SGN, http://solgenomics.net) is a primary repository for phenotypic, genetic, genomic, expression and metabolic data for the Solanaceae family and other related Asterids species and houses a variety of bioinformatics tools. SGN has implemented a new approach to QTL data organization, storage, analysis, and cross-links with other relevant data in internal and external databases. The new QTL module, solQTL, http://solgenomics.net/qtl/, employs a user-friendly web interface for uploading raw phenotype and genotype data to the database, R/QTL mapping software for on-the-fly QTL analysis and algorithms for online visualization and cross-referencing of QTLs to relevant datasets and tools such as the SGN Comparative Map Viewer and Genome Browser. Here, we describe the development of the solQTL module and demonstrate its application. CONCLUSIONS: solQTL allows Solanaceae researchers to upload raw genotype and phenotype data to SGN, perform QTL analysis and dynamically cross-link to relevant genetic, expression and genome annotations. Exploration and synthesis of the relevant data is expected to help facilitate identification of candidate genes underlying phenotypic variation and markers more closely linked to QTLs. solQTL is freely available on SGN and can be used in private or public mode.

A community-based annotation framework for linking solanaceae genomes with phenomes.

The amount of biological data available in the public domain is growing exponentially, and there is an increasing need for infrastructural and human resources to organize, store, and present the data in a proper context. Model organism databases (MODs) invest great efforts to functionally annotate genomes and phenomes by in-house curators. The SOL Genomics Network (SGN; http://www.sgn.cornell.edu) is a clade-oriented database (COD), which provides a more scalable and comparative framework for biological information. SGN has recently spearheaded a new approach by developing community annotation tools to expand its curational capacity. These tools effectively allow some curation to be delegated to qualified researchers, while, at the same time, preserving the in-house curators' full editorial control. Here we describe the background, features, implementation, results, and development road map of SGN's community annotation tools for curating genotypes and phenotypes. Since the inception of this project in late 2006, interest and participation from the Solanaceae research community has been strong and growing continuously to the extent that we plan to expand the framework to accommodate more plant taxa. All data, tools, and code developed at SGN are freely available to download and adapt.

The SGN comparative map viewer.

MOTIVATION: With the rapid accumulation of genetic data for a multitude of different species, the availability of intuitive comparative genomic tools becomes an important requirement for the research community. Here we describe a web-based comparative viewer for mapping data, including genetic, physical and cytological maps, that is part of the SGN website (http://sgn.cornell.edu/) but that can also be installed and adapted for other websites. In addition to viewing and comparing different maps stored in the SGN database, the viewer allows users to upload their own maps and compare them to other maps in the system. The viewer is implemented in object oriented Perl, with a simple extensible interface to write data adapters for other relational database schemas and flat file formats.

Abscisic acid deficiency in the tomato mutant high-pigment 3 leading to increased plastid number and higher fruit lycopene content.

Carotenoids are present in most tissues of higher plants where they play a variety of essential roles. To study the regulation of carotenoid biosynthesis, we have isolated novel mutations in tomato (Solanum lycopersicum) with altered pigmentation of fruit or flowers. Here we describe the isolation and analysis of a tomato mutant, high-pigment 3 (hp3), that accumulates 30% more carotenoids in the mature fruit. Higher concentrations of carotenoids and chlorophyll were also measured in leaves and the pericarp of green fruit. The mutation in hp3 had occurred in the gene for zeaxanthin epoxidase (Zep), which converts zeaxanthin to violaxanthin. Consequently, leaves of the mutant lack violaxanthin and neoxanthin, and flowers contain only minute quantities of these xanthophylls. The concentration in the hp3 mutant of abscisic acid (ABA), which is derived from xanthophylls, is 75% lower than the normal level, making hp3 an ABA-deficient mutant. The plastid compartment size in fruit cells is at least twofold larger in hp3 plants compared with the wild-type. The transcript level in the green fruit of FtsZ, which encodes a tubulin-like protein involved in plastid division, is 60% higher in hp3 than in the wild-type, suggesting that increased plastid division is responsible for this phenomenon. Elevated fruit pigmentation and plastid compartment size were also observed in the ABA-deficient mutants flacca and sitiens. Taken together, these results suggest that ABA deficiency in the tomato mutant hp3 leads to enlargement of the plastid compartment size, probably by increasing plastid division, thus enabling greater biosynthesis and a higher storage capacity of the pigments.

Regulation of LANCEOLATE by miR319 is required for compound-leaf development in tomato.

Plant leaves show pronounced plasticity of size and form. In the classical, partially dominant mutation Lanceolate (La), the large compound leaves of tomato (Solanum lycopersicum) are converted into small simple ones. We show that LA encodes a transcription factor from the TCP family containing an miR319-binding site. Five independent La isolates are gain-of-function alleles that result from point mutations within the miR319-binding site and confer partial resistance of the La transcripts to microRNA (miRNA)-directed inhibition. The reduced sensitivity to miRNA regulation leads to elevated LA expression in very young La leaf primordia and to precocious differentiation of leaf margins. In contrast, downregulation of several LA-like genes using ectopic expression of miR319 resulted in larger leaflets and continuous growth of leaf margins. Our results imply that regulation of LA by miR319 defines a flexible window of morphogenetic competence along the developing leaf margin that is required for leaf elaboration.