A systems-wide comparison of red rice (Oryza longistaminata) tissues identifies rhizome specific genes and proteins that are targets for cultivated rice improvement.

BACKGROUND: The rhizome, the original stem of land plants, enables species to invade new territory and is a critical component of perenniality, especially in grasses. Red rice (Oryza longistaminata) is a perennial wild rice species with many valuable traits that could be used to improve cultivated rice cultivars, including rhizomatousness, disease resistance and drought tolerance. Despite these features, little is known about the molecular mechanisms that contribute to rhizome growth, development and function in this plant. RESULTS: We used an integrated approach to compare the transcriptome, proteome and metabolome of the rhizome to other tissues of red rice. 116 Gb of transcriptome sequence was obtained from various tissues and used to identify rhizome-specific and preferentially expressed genes, including transcription factors and hormone metabolism and stress response-related genes. Proteomics and metabolomics approaches identified 41 proteins and more than 100 primary metabolites and plant hormones with rhizome preferential accumulation. Of particular interest was the identification of a large number of gene transcripts from Magnaportha oryzae, the fungus that causes rice blast disease in cultivated rice, even though the red rice plants showed no sign of disease. CONCLUSIONS: A significant set of genes, proteins and metabolites appear to be specifically or preferentially expressed in the rhizome of O. longistaminata. The presence of M. oryzae gene transcripts at a high level in apparently healthy plants suggests that red rice is resistant to this pathogen, and may be able to provide genes to cultivated rice that will enable resistance to rice blast disease.

Next-generation sequencing-based transcriptomic and proteomic analysis of the common reed, Phragmites australis (Poaceae), reveals genes involved in invasiveness and rhizome specificity.

PREMISE OF THE STUDY: The common reed (Phragmites australis), one of the most widely distributed of all angiosperms, uses its rhizomes (underground stems) to invade new territory, making it one of the most successful weedy species worldwide. Characterization of the rhizome transcriptome and proteome is needed to identify candidate genes and proteins involved in rhizome growth, development, metabolism, and invasiveness. METHODS: We employed next-generation sequencing technologies including 454 and Illumina platforms to characterize the reed rhizome transcriptome and used quantitative proteomics techniques to identify the rhizome proteome. KEY RESULTS: Combining 336514 Roche 454 Titanium reads and 103350802 Illumina paired-end reads in a de novo hybrid assembly yielded 124450 unique transcripts with an average length of 549 bp, of which 54317 were annotated. Rhizome-specific and differentially expressed transcripts were identified between rhizome apical tips (apical meristematic region) and rhizome elongation zones. A total of 1280 nonredundant proteins were identified and quantified using GeLC-MS/MS based label-free proteomics, where 174 and 77 proteins were preferentially expressed in the rhizome elongation zone and apical tip tissues, respectively. Genes involved in allelopathy and in controlling development and potentially invasiveness were identified. CONCLUSIONS: In addition to being a valuable sequence and protein data resource for studying plant rhizome species, our results provide useful insights into identifying specific genes and proteins with potential roles in rhizome differentiation, development, and function.

Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.).

A transcript map has been constructed by the development and integration of genic molecular markers (GMMs) including single nucleotide polymorphism (SNP), genic microsatellite or simple sequence repeat (SSR) and intron spanning region (ISR)-based markers, on an inter-specific mapping population of chickpea, the third food legume crop of the world and the first food legume crop of India. For SNP discovery through allele re-sequencing, primer pairs were designed for 688 genes/expressed sequence tags (ESTs) of chickpea and 657 genes/ESTs of closely related species of chickpea. High-quality sequence data obtained for 220 candidate genic regions on 2-20 genotypes representing 9 Cicer species provided 1,893 SNPs with an average frequency of 1/35.83 bp and 0.34 PIC (polymorphism information content) value. On an average 2.9 haplotypes were present in 220 candidate genic regions with an average haplotype diversity of 0.6326. SNP2CAPS analysis of 220 sequence alignments, as mentioned above, provided a total of 192 CAPS candidates. Experimental analysis of these 192 CAPS candidates together with 87 CAPS candidates identified earlier through in silico mining of ESTs provided scorable amplification in 173 (62.01%) cases of which predicted assays were validated in 143 (82.66%) cases (CGMM). Alignments of chickpea unigenes with Medicago truncatula genome were used to develop 121 intron spanning region (CISR) markers of which 87 yielded scorable products. In addition, optimization of 77 EST-derived SSR (ICCeM) markers provided 51 scorable markers. Screening of easily assayable 281 markers including 143 CGMMs, 87 CISRs and 51 ICCeMs on 5 parental genotypes of three mapping populations identified 104 polymorphic markers including 90 markers on the inter-specific mapping population. Sixty-two of these GMMs together with 218 earlier published markers (including 64 GMM loci) and 20 other unpublished markers could be integrated into this genetic map. A genetic map developed here, therefore, has a total of 300 loci including 126 GMM loci and spans 766.56 cM, with an average inter-marker distance of 2.55 cM. In summary, this is the first report on the development of large-scale genic markers including development of easily assayable markers and a transcript map of chickpea. These resources should be useful not only for genome analysis and genetics and breeding applications of chickpea, but also for comparative legume genomics.

SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.

BACKGROUND: SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. RESULTS: There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at http://sswap.info (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at http://sswap.info/protocol.jsp, developer tools at http://sswap.info/developer.jsp, and a portal to third-party ontologies at http://sswapmeet.sswap.info (a "swap meet"). CONCLUSION: SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the confounding of content, structure, and presentation. SSWAP is novel by establishing the concept of a canonical yet mutable OWL DL graph that allows data and service providers to describe their resources, to allow discovery servers to offer semantically rich search engines, to allow clients to discover and invoke those resources, and to allow providers to respond with semantically tagged data. SSWAP allows for a mix-and-match of terms from both new and legacy third-party ontologies in these graphs.