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Verticillium wilt, caused by Verticillium dahliae, is a devastating disease for many important crops, including cotton. Kiwellins (KWLs), a group of cysteine-rich proteins synthesized in many plants, have been shown to be involved in response to various phytopathogens. To evaluate genes for their function in resistance to Verticillium wilt, we investigated KWL homologs in cotton. Thirty-five KWL genes (GhKWLs) were identified from the genome of upland cotton (Gossypium hirsutum). Among them, GhKWL1 was shown to be localized in nucleus and cytosol, and its gene expression is induced by the infection of V. dahliae. We revealed that GhKWL1 was a positive regulator of GhERF105. Silencing of GhKWL1 resulted in a decrease, whereas overexpression led to an increase in resistance of transgenic plants to Verticillium wilt. Interestingly, through binding to GhKWL1, the pathogenic effector protein VdISC1 produced by V. dahliae could impair the defense response mediated by GhKWL1. Therefore, our study suggests there is a GhKWL1-mediated defense response in cotton, which can be hijacked by V. dahliae through the interaction of VdISC1 with GhKWL1.
Pubmed ID: 34298948
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Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.
View all literature mentionsA portal to biomedical and genomic information. NCBI creates public databases, conducts research in computational biology, develops software tools for analyzing genome data, and disseminates biomedical information for the better understanding of molecular processes affecting human health and disease.
View all literature mentionsDatabase and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes
View all literature mentionsCollection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.
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