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Foliage diseases are prevalent in cucumber production and cause serious yield reduction across the world. Identifying resistance or susceptible genes under foliage-disease stress is essential for breeding resistant varieties, of which leaf-specific expressed susceptible genes are extremely important but rarely studied in crops. This study performed an in-depth mining of public transcriptome data both in different cucumber tissues and under downy mildew (DM) inoculation, and found that the expression of leaf-specific expressed transcription factor CsTCP14 was significantly increased after treatment with DM, as well as being upregulated under stress from another foliage disease, watermelon mosaic virus (WMV), in susceptible cucumbers. Furthermore, the Pearson correlation analysis identified genome-wide co-expressed defense genes with CsTCP14. A potential target CsNBS-LRR gene, Csa6M344280.1, was obtained as obviously reduced and was negatively correlated with the expression of the susceptible gene CsTCP14. Moreover, the interaction experiments of electrophoretic mobility shift assay (EMSA) and yeast one-hybrid assay (Y1H) were successfully executed to prove that CsTCP14 could transcriptionally repress the expression of the CsNBS-LRR gene, Csa6M344280.1, which resulted in inducing susceptibility to foliage diseases in cucumber. As such, we constructed a draft model showing that the leaf-specific expressed gene CsTCP14 was negatively regulating the defense gene Csa6M344280.1 to induce susceptibility to foliage diseases in cucumber. Therefore, this study explored key susceptible genes in response to foliage diseases based on a comprehensive analysis of public transcriptome data and provided an opportunity to breed new varieties that can resist foliage diseases in cucumber, as well as in other crops.
Pubmed ID: 31130701
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Software for the automated evaluation of behavior in a range of pre-clinical and neuroscience applications in basic and clinical psychopharmacology. Applications include phenotype characterization and studying the behavioral effects of pharmacologic substances.
View all literature mentionsTool used to design PCR primers from DNA sequence - often in high-throughput genomics applications. It does everything from mispriming libraries to sequence quality data to the generation of internal oligos.
View all literature mentionsA database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
View all literature mentionsCommercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsA subCELlular LOcalization predictor based on a multi-class support vector machine (SVM) classification system. CELLO uses 4 types of sequence coding schemes: the amino acid composition, the di-peptide composition, the partitioned amino acid composition and the sequence composition based on the physico-chemical properties of amino acids. They combine votes from these classifiers and use the jury votes to determine the final assignment.
View all literature mentionsPortal which provides access to scientific databases and software tools (i.e., resources) in different areas of life sciences including proteomics, genomics, phylogeny, systems biology, population genetics, transcriptomics etc. It contains resources from many different SIB groups as well as external institutions.
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.
