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Nodulation competition is a key factor that limits symbiotic nitrogen fixation between rhizobia and their host legumes. Soybean root exudates (SREs) are thought to act as signals that influence Bradyrhizobium ability to colonize roots and to survive in the rhizosphere, and thus they act as a key determinant of nodulation competitiveness. In order to find the competitiveness-related genes in B. diazoefficiens, the transcriptome of two SREs treated B. diazoefficiens with completely different nodulation abilities (B. diazoefficiens 4534 and B. diazoefficiens 4222) were sequenced and compared. In SREs treated strain 4534 (SREs-4534), 253 unigenes were up-regulated and 204 unigenes were down-regulated. In SREs treated strain 4534 (SREs-4222), the numbers of up- and down-regulated unigenes were 108 and 185, respectively. There were considerable differences between the SREs-4534 and SREs-4222 gene expression profiles. Some differentially expressed genes are associated with a two-component system (i.g., nodW, phyR-σEcfG), bacterial chemotaxis (i.g., cheA, unigene04832), ABC transport proteins (i.g., unigene02212), IAA (indole-3-acetic acid) metabolism (i.g., nthA, nthB), and metabolic fitness (i.g., put.), which may explain the higher nodulation competitiveness of B. diazoefficiens in the rhizosphere. Our results provide a comprehensive transcriptomic resource for SREs treated B. diazoefficiens and will facilitate further studies on competitiveness-related genes in B. diazoefficiens.
Pubmed ID: 28887528
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Multi species reference database. Comprehensive plant biochemical pathway database, containing curated information from literature and computational analyses about genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsComputable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
View all literature mentionsSoftware for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data.
View all literature mentionsAn ALL in ONE tool for functional annotation of (novel) sequences and the analysis of annotation data. Blast2GO (B2G) joins in one universal application similarity search based GO annotation and functional analysis. B2G offers the possibility of direct statistical analysis on gene function information and visualization of relevant functional features on a highlighted GO direct acyclic graph (DAG). Furthermore B2G includes various statistics charts summarizing the results obtained at BLASTing, GO-mapping, annotation and enrichment analysis (Fisher''''s Exact Test). All analysis process steps are configurable and data import and export are supported at any stage. The application also accepts pre-existing BLAST or annotation files and takes them to subsequent steps. The tool offers a very suitable platform for high throughput functional genomics research in non-model species. B2G is a species-independent, intuitive and interactive desktop application which allows monitoring and comprehending the whole annotation and analysis process supported by additional features like GO Slim integration, evidence code (EC) consideration, a Batch-Mode or GO-Multilevel-Pies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsWeb server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
