ABSTRACT
Fusarium wilt is one of the major biotic stresses reducing chickpea productivity. The use of wilt-resistant cultivars is the most appropriate means to combat the disease and secure productivity. As a step towards understanding the molecular basis of wilt resistance in chickpea, we investigated the transcriptomes of wilt-susceptible and wilt-resistant cultivars under both Fusarium oxysporum f.sp. ciceri (Foc) challenged and unchallenged conditions. Transcriptome profiling using LongSAGE provided a valuable insight into the molecular interactions between chickpea and Foc, which revealed several known as well as novel genes with differential or unique expression patterns in chickpea contributing to lignification, hormonal homeostasis, plant defense signaling, ROS homeostasis, R-gene mediated defense, etc. Similarly, several Foc genes characteristically required for survival and growth of the pathogen were expressed only in the susceptible cultivar with null expression of most of these genes in the resistant cultivar. This study provides a rich resource for functional characterization of the genes involved in resistance mechanism and their use in breeding for sustainable wilt-resistance. Additionally, it provides pathogen targets facilitating the development of novel control strategies.
Subject(s)
Cicer/genetics , Fusarium/pathogenicity , Host-Pathogen Interactions , Plant Immunity , Transcriptome , Cicer/immunology , Cicer/microbiology , Genes, PlantABSTRACT
Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.
Subject(s)
Computational Biology/methods , Molecular Biology/methods , Molecular Sequence Annotation , Proteins/physiology , Algorithms , Animals , Databases, Protein , Exoribonucleases/classification , Exoribonucleases/genetics , Exoribonucleases/physiology , Forecasting , Humans , Proteins/chemistry , Proteins/classification , Proteins/genetics , Species SpecificityABSTRACT
Anvaya is a workflow environment for automated genome analysis that provides an interface for several bioinformatics tools and databases, loosely coupled together in a coordinated system, enabling the execution of a set of analyses tools in series or in parallel. It is a client-server workflow environment that has an advantage over existing software as it enables extensive pre & post processing of biological data in an efficient manner. "Anvaya" offers the user, novel functionalities to carry out exhaustive comparative analysis via "custom tools," which are tools with new functionality not available in standard tools, and "built-in PERL parsers," which automate data-flow between tools that hitherto, required manual intervention. It also provides a set of 11 pre-defined workflows for frequently used pipelines in genome annotation and comparative genomics ranging from EST assembly and annotation to phylogenetic reconstruction and microarray analysis. It provides a platform that serves as a single-stop solution for biologists to carry out hassle-free and comprehensive analysis, without being bothered about the nuances involved in tool installation, command line parameters, format conversions required to connect tools and manage/process multiple data sets at a single instance.
Subject(s)
Genome , Genomics/methods , Software , Databases, Factual , Expressed Sequence Tags , Internet , Phylogeny , WorkflowABSTRACT
Salmonella enterica is an animal and zoonotic pathogen of worldwide importance and may be classified into serovars differing in virulence and host range. We sequenced and annotated the genomes of serovar Typhimurium, Choleraesuis, Dublin, and Gallinarum strains of defined virulence in each of three food-producing animal hosts. This provides valuable measures of intraserovar diversity and opportunities to formally link genotypes to phenotypes in target animals.
