Preventing crown gall disease using oncogene silencing or VirE1-expressing transgenics

Crown gall disease is caused by the ubiquitous soil bacterium Agrobacterium tumefaciens which transfers a portion if DNA (T-DNA) into the plant cell. Preventing infection by using the biocontrol strain Agrobacterium radiobacter K84 is currently the only defense for crown gall. Two different resistance strategies were examined in this work. The first was the use of VirE1-expressing transgenic Arabidopsis thaliana. VirE1 is the secretory chaperone of VirE2. VirE2 is exported into plant cells during infection and is essential for tumorigenesis. Once in plant cells VirE2, a single-stranded DNA binding protein, protects the single-stranded T-strand and also helps localize it to the nucleus. Since the interaction of VirE1 and VirE2 is favored over a VirE2 and T-strand interaction we hypothesized that plant expressed VirE1 would prevent VirE2 from binding the T-strand. One plant line exhibited 3.5-fold fewer tumors than wild-type plants. Some amino acid residues of VirE1 needed for interaction with VirE2 have also been identified in this work. This research provides further information about the VirE1-VirE2 interaction that may be used in future constructs for VirE1-mediated crown gall resistance. The other resistance strategy examined in this work is gene silencing of the A. tumefaciens oncogenes iaaM and ipt. These oncogenes are part of the T-DNA and once in the cells express auxin and cytokinin which cause gall growth. By generating constructs that made double-stranded RNA and creating transgenic apple tissue that expressed these constructs, sequence specific degradation of the target mRNA was initiated. Six apple lines were completely resistant to crown gall disease using gene silencing. These methods may be further improved and even combined to eventually create crown gall resistant transgenics for commercial production

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 datamanagement 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

Regulatory and DNA Repair Genes Contribute to the Desiccation Resistance of Sinorhizobium meliloti Rm1021 ▿

Sinorhizobium meliloti can form a nitrogen-fixing symbiotic relationship with alfalfa after bacteria in the soil infect emerging root hairs of the growing plant. To be successful at this, the bacteria must be able to survive in the soil between periods of active plant growth, including when conditions are dry. The ability of S. meliloti to withstand desiccation has been known for years, but genes that contribute to this phenotype have not been identified. Transposon mutagenesis was used in combination with novel screening techniques to identify four desiccation-sensitive mutants of S. meliloti Rm1021. DNA sequencing of the transposon insertion sites identified three genes with regulatory functions (relA, rpoE2, and hpr) and a DNA repair gene (uvrC). Various phenotypes of the mutants were determined, including their behavior on several indicator media and in symbiosis. All of the mutants formed an effective symbiosis with alfalfa. To test the hypothesis that UvrC-related excision repair was important in desiccation resistance, uvrA, uvrB, and uvrC deletion mutants were also constructed. These strains were sensitive to DNA damage induced by UV light and 4-NQO and were also desiccation sensitive. These data indicate that uvr gene-mediated DNA repair and the regulation of stress-induced pathways are important for desiccation resistance

Extension modules for storage, visualization and querying of genomic, genetic and breeding data in Tripal databases

Tripal is an open-source database platform primarily used for development of genomic, genetic and breeding databases. We report here on the release of the Chado Loader, Chado Data Display and Chado Search modules to extend the functionality of the core Tripal modules. These new extension modules provide additional tools for (1) data loading, (2) customized visualization and (3) advanced search functions for supported data types such as organism, marker, QTL/Mendelian Trait Loci, germplasm, map, project, phenotype, genotype and their respective metadata. The Chado Loader module provides data collection templates in Excel with defined metadata and data loaders with front end forms. The Chado Data Display module contains tools to visualize each data type and the metadata which can be used as is or customized as desired. The Chado Search module provides search and download functionality for the supported data types. Also included are the tools to visualize map and species summary. The use of materialized views in the Chado Search module enables better performance as well as flexibility of data modeling in Chado, allowing existing Tripal databases with different metadata types to utilize the module. These Tripal Extension modules are implemented in the Genome Database for Rosaceae (rosaceae.org), CottonGen (cottongen.org), Citrus Genome Database (citrusgenomedb.org), Genome Database for Vaccinium (vaccinium.org) and the Cool Season Food Legume Database (coolseasonfoodlegume.org). Database URL : https://www.citrusgenomedb.org/ , https://www.coolseasonfoodlegume.org/ , https://www.cottongen.org/ , https://www.rosaceae.org/ , https://www.vaccinium.org

Extension modules for storage, visualization and querying of genomic, genetic and breeding data in Tripal databases

Tripal is an open-source database platform primarily used for development of genomic, genetic and breeding databases. We report here on the release of the Chado Loader, Chado Data Display and Chado Search modules to extend the functionality of the core Tripal modules. These new extension modules provide additional tools for (1) data loading, (2) customized visualization and (3) advanced search functions for supported data types such as organism, marker, QTL/Mendelian Trait Loci, germplasm, map, project, phenotype, genotype and their respective metadata. The Chado Loader module provides data collection templates in Excel with defined metadata and data loaders with front end forms. The Chado Data Display module contains tools to visualize each data type and the metadata which can be used as is or customized as desired. The Chado Search module provides search and download functionality for the supported data types. Also included are the tools to visualize map and species summary. The use of materialized views in the Chado Search module enables better performance as well as flexibility of data modeling in Chado, allowing existing Tripal databases with different metadata types to utilize the module. These Tripal Extension modules are implemented in the Genome Database for Rosaceae (rosaceae.org), CottonGen (cottongen.org), Citrus Genome Database (citrusgenomedb.org), Genome Database for Vaccinium (vaccinium.org) and the Cool Season Food Legume Database (coolseasonfoodlegume.org). Database URL : https://www.citrusgenomedb.org/ , https://www.coolseasonfoodlegume.org/ , https://www.cottongen.org/ , https://www.rosaceae.org/ , https://www.vaccinium.org

CottonGen: The Community Database for Cotton Genomics, Genetics, and Breeding Research

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

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

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