10 research outputs found
Meta-analysis of genome-wide association studies provides insights into genetic control of tomato flavor
Tomato flavor has changed over the course of long-term domestication and intensive breeding. To understand the genetic control of flavor, we report the meta-analysis of genome-wide association studies (GWAS) using 775 tomato accessions and 2,316,117 SNPs from three GWAS panels. We discover 305 significant associations for the contents of sugars, acids, amino acids, and flavor-related volatiles. We demonstrate that fruit citrate and malate contents have been impacted by selection during domestication and improvement, while sugar content has undergone less stringent selection. We suggest that it may be possible to significantly increase volatiles that positively contribute to consumer preferences while reducing unpleasant volatiles, by selection of the relevant allele combinations. Our results provide genetic insights into the influence of human selection on tomato flavor and demonstrate the benefits obtained from meta-analysis.J-T.Z. was funded by a Chinese Scholarship Council (CSC) scholarship
Grafted Human Embryonic Progenitors Expressing Neurogenin-2 Stimulate Axonal Sprouting and Improve Motor Recovery after Severe Spinal Cord Injury
7 p.Background: Spinal cord injury (SCI) is a widely spread pathology with currently no effective treatment for any symptom. Regenerative medicine through cell transplantation is a very attractive strategy and may be used in different non-exclusive ways to promote functional recovery. We investigated functional and structural outcomes after grafting human embryonic neural progenitors (hENPs) in spinal cord-lesioned rats.Methods and Principal Findings: With the objective of translation to clinics we have chosen a paradigm of delayed grafting, i.e., one week after lesion, in a severe model of spinal cord compression in adult rats. hENPs were either naive or engineered to express Neurogenin 2 (Ngn2). Moreover, we have compared integrating and non-integrating lentiviral vectors, since the latter present reduced risks of insertional mutagenesis. We show that transplantation of hENPs transduced to express Ngn2 fully restore weight support and improve functional motor recovery after severe spinal cord compression at thoracic level. This was correlated with partial restoration of serotonin innervations at lumbar level, and translocation of 5HT1A receptors to the plasma membrane of motoneurons. Since hENPs were not detectable 4 weeks after grafting, transitory expression of Ngn2 appears sufficient to achieve motor recovery and to permit axonal regeneration. Importantly, we also demonstrate that transplantation of naive hENPs is detrimental to functional recovery.Conclusions and Significance: Transplantation and short-term survival of Ngn2-expressing hENPs restore weight support after SCI and partially restore serotonin fibers density and 5HT1A receptor pattern caudal to the lesion. Moreover, grafting of naive-hENPs was found to worsen the outcome versus injured only animals, thus pointing to the possible detrimental effect of stem cell-based therapy per se in SCI. This is of major importance given the increasing number of clinical trials involving cell grafting developed for SCI patients.This study was supported by the European Union FP6 "RESCUE" STREP; the "Institut pour la Recherche sur la Moelle Epiniere"; the "Academie de Medecine"; the "Societe Francaise de Neurochirurgie"; "Verticale" and the "Association Demain Debout Aquitaine". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Genomic variation in tomato, from wild ancestors to contemporary breeding accessions
[EN] Background: Domestication modifies the genomic variation of species. Quantifying this variation provides insights
into the domestication process, facilitates the management of resources used by breeders and germplasm centers,
and enables the design of experiments to associate traits with genes. We described and analyzed the genetic
diversity of 1,008 tomato accessions including Solanum lycopersicum var. lycopersicum (SLL), S. lycopersicum var.
cerasiforme (SLC), and S. pimpinellifolium (SP) that were genotyped using 7,720 SNPs. Additionally, we explored the
allelic frequency of six loci affecting fruit weight and shape to infer patterns of selection.
Results: Our results revealed a pattern of variation that strongly supported a two-step domestication process, occasional
hybridization in the wild, and differentiation through human selection. These interpretations were consistent with the
observed allele frequencies for the six loci affecting fruit weight and shape. Fruit weight was strongly selected in SLC in
the Andean region of Ecuador and Northern Peru prior to the domestication of tomato in Mesoamerica. Alleles affecting
fruit shape were differentially selected among SLL genetic subgroups. Our results also clarified the biological status of SLC.
True SLC was phylogenetically positioned between SP and SLL and its fruit morphology was diverse. SLC and “cherry
tomato” are not synonymous terms. The morphologically-based term “cherry tomato” included some SLC, contemporary
varieties, as well as many admixtures between SP and SLL. Contemporary SLL showed a moderate increase in nucleotide
diversity, when compared with vintage groups.
Conclusions: This study presents a broad and detailed representation of the genomic variation in tomato. Tomato
domestication seems to have followed a two step-process; a first domestication in South America and a second step in
Mesoamerica. The distribution of fruit weight and shape alleles supports that domestication of SLC occurred in the
Andean region. Our results also clarify the biological status of SLC as true phylogenetic group within tomato. We detect
Ecuadorian and Peruvian accessions that may represent a pool of unexplored variation that could be of interest for crop
improvement.We are grateful to the gene banks for their collections that made this study possible. We thank Syngenta Seeds for providing genotyping data for 42 accessions. We would like to thank the Supercomputing and Bioinnovation Center (Universidad de Malaga, Spain) for providing computational resources to process the SNAPP phylogenetic tree. This research was supported in part by the USDA/NIFA funded SolCAP project under contract number to DF and USDA AFRI 2013-67013-21229 to EvdK and DF.Blanca Postigo, JM.; Montero Pau, J.; Sauvage, C.; Bauchet, G.; Illa, E.; Díez Niclós, MJTDJ.; Francis, D.... (2015). Genomic variation in tomato, from wild ancestors to contemporary breeding accessions. BMC Genomics. 16(257):1-19. https://doi.org/10.1186/s12864-015-1444-1S11916257Tanksley SD, McCouch SR. Seed banks and molecular maps: unlocking genetic potential from the wild. Science (80-). 1997;277:1063–6.Doebley JF, Gaut BS, Smith BD. The molecular genetics of crop domestication. 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High density genotype storage for plant breeding in the Chado schema of Breedbase.
Modern breeding programs routinely use genome-wide information for selecting individuals to advance. The large volumes of genotypic information required present a challenge for data storage and query efficiency. Major use cases require genotyping data to be linked with trait phenotyping data. In contrast to phenotyping data that are often stored in relational database schemas, next-generation genotyping data are traditionally stored in non-relational storage systems due to their extremely large scope. This study presents a novel data model implemented in Breedbase (https://breedbase.org/) for uniting relational phenotyping data and non-relational genotyping data within the open-source PostgreSQL database engine. Breedbase is an open-source, web-database designed to manage all of a breeder's informatics needs: management of field experiments, phenotypic and genotypic data collection and storage, and statistical analyses. The genotyping data is stored in a PostgreSQL data-type known as binary JavaScript Object Notation (JSONb), where the JSON structures closely follow the Variant Call Format (VCF) data model. The Breedbase genotyping data model can handle different ploidy levels, structural variants, and any genotype encoded in VCF. JSONb is both compressed and indexed, resulting in a space and time efficient system. Furthermore, file caching maximizes data retrieval performance. Integration of all breeding data within the Chado database schema retains referential integrity that may be lost when genotyping and phenotyping data are stored in separate systems. Benchmarking demonstrates that the system is fast enough for computation of a genomic relationship matrix (GRM) and genome wide association study (GWAS) for datasets involving 1,325 diploid Zea mays, 314 triploid Musa acuminata, and 924 diploid Manihot esculenta samples genotyped with 955,690, 142,119, and 287,952 genotype-by-sequencing (GBS) markers, respectively
Historical Introgressions from a Wild Relative of Modern Cassava Improved Important Traits and May Be Under Balancing Selection
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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
Breedbase: a digital ecosystem for modern plant breeding
Modern breeding methods integrate next-generation sequencing (NGS) 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/). Originally initiated as Cassavabase (https://cassavabase.org/) with the NextGen Cassava project (https://www.nextgencassava.org/), 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/) and packaged in a Docker image for deployment (https://dockerhub.com/breedbase/). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem
Use of modern tomato breeding germplasm for deciphering the genetic control of agronomical traits by Genome Wide Association study
Genomic Designing for Climate-Smart Tomato
Tomato is the first vegetable consumed in the world. It is grown in very different conditions and areas, mainly in field for processing tomatoes while fresh-market tomatoes are often produced in greenhouses. Tomato faces many environmental stresses, both biotic and abiotic. Today many new genomic resources are available allowing an acceleration of the genetic progress. In this chapter, we will first present the main challenges to breed climate-smart tomatoes. The breeding objectives relative to productivity, fruit quality, and adaptation to environmental stresses will be presented with a special focus on how climate change is impacting these objectives. In the second part, the genetic and genomic resources available will be presented. Then, traditional and molecular breeding techniques will be discussed. A special focus will then be presented on ecophysiological modeling, which could constitute an important strategy to define new ideotypes adapted to breeding objectives. Finally, we will illustrate how new biotechnological tools are implemented and could be used to breed climate-smart tomatoes