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.

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.

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.

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.

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.

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 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/.

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.

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.