Characterizing genetic diversity and creating novel gene pools in rice for trait dissection and gene function discovery

Rice diversity is the foundation for rice improvement programs. At IRRI, over 100,000 rice accessions are deposited, and intelligent use of this diversity can not only help solve current production problems but also create future production opportunities and tackle climate change challenges. To fully explore and utilize rice diversity, two ingredients are needed: 1 - the genetic blueprints of diverse rice accessions in use, 2 - plant populations with recombined genotypes allowing expression of phenotypic variation and discovery of new genes/QTLs for use in breeding programs. Sequencing of the genomes & obtaining SNP genotypes of many rice accessions is feasible due to decreasing cost of advanced DNA sequencing technologies. Coupled with the creation of populations suitable for trait dissection / phenotyping, discovery of gene functions and allelic variations causal to important agronomic traits becomes possible. This in turn will provide rich biological evidences to the rice/cereal crop genome annotation community

Development of a novel data mining tool to find cis-elements in rice gene promoter regions

<p>Abstract</p> <p>Background</p> <p>Information on more than 35 000 full-length <it>Oryza sativa </it>cDNAs, together with associated microarray gene expression data collected under various treatment conditions, has made it feasible to identify motifs that are conserved in gene promoters and may act as <it>cis</it>-regulatory elements with key roles under the various conditions.</p> <p>Results</p> <p>We have developed a novel tool that searches for <it>cis</it>-element candidates in the upstream, downstream, or coding regions of differentially regulated genes. The tool first lists <it>cis-</it>element candidates by motif searching based on the supposition that if there are <it>cis-</it>elements playing important roles in the regulation of a given set of genes, they will be statistically overrepresented and will be conserved. Then it evaluates the likelihood scores of the listed candidate motifs by association rule analysis. This strategy depends on the idea that motifs overrepresented in the promoter region could play specific roles in the regulation of expression of these genes. The tool is designed so that any biological researchers can use it easily at the publicly accessible Internet site <url>http://hpc.irri.cgiar.org/tool/nias/ces</url>. We evaluated the accuracy and utility of the tool by using a dataset of auxin-inducible genes that have well-studied <it>cis-</it>elements. The test showed the effectiveness of the tool in identifying significant relationships between <it>cis-</it>element candidates and related sets of genes.</p> <p>Conclusion</p> <p>The tool lists possible <it>cis-</it>element motifs corresponding to genes of interest, and it will contribute to the deeper understanding of gene regulatory mechanisms in plants.</p

Rice-Infecting Pseudomonas Genomes Are Highly Accessorized and Harbor Multiple Putative Virulence Mechanisms to Cause Sheath Brown Rot

Sheath rot complex and seed discoloration in rice involve a number of pathogenic bacteria that cannot be associated with distinctive symptoms. These pathogens can easily travel on asymptomatic seeds and therefore represent a threat to rice cropping systems. Among the rice-infecting Pseudomonas, P. fuscovaginae has been associated with sheath brown rot disease in several rice growing areas around the world. The appearance of a similar Pseudomonas population, which here we named P. fuscovaginae-like, represents a perfect opportunity to understand common genomic features that can explain the infection mechanism in rice. We showed that the novel population is indeed closely related to P. fuscovaginae. A comparative genomics approach on eight rice-infecting Pseudomonas revealed heterogeneous genomes and a high number of strain-specific genes. The genomes of P. fuscovaginae-like harbor four secretion systems (Type I, II, III, and VI) and other important pathogenicity machinery that could probably facilitate rice colonization. We identified 123 core secreted proteins, most of which have strong signatures of positive selection suggesting functional adaptation. Transcript accumulation of putative pathogenicity-related genes during rice colonization revealed a concerted virulence mechanism. The study suggests that rice-infecting Pseudomonas causing sheath brown rot are intrinsically diverse and maintain a variable set of metabolic capabilities as a potential strategy to occupy a range of environments.Consortium for International Agricultural Research (CGIAR)Global Rice Science Partnership (GRiSP

Challenges for FAIR-compliant description and comparison of crop phenotype data with standardized controlled vocabularies

Crop phenotypic data underpin many pre-breeding efforts to characterize variation within germplasm collections. Although there has been an increase in the global capacity for accumulating and comparing such data, a lack of consistency in the systematic description of metadata often limits integration and sharing. We therefore aimed to understand some of the challenges facing findable, accesible, interoperable and reusable (FAIR) curation and annotation of phenotypic data from minor and underutilized crops. We used bambara groundnut (Vigna subterranea) as an exemplar underutilized crop to assess the ability of the Crop Ontology system to facilitate curation of trait datasets, so that they are accessible for comparative analysis. This involved generating a controlled vocabulary Trait Dictionary of 134 terms. Systematic quantification of syntactic and semantic cohesiveness of the full set of 28 crop-specific COs identified inconsistencies between trait descriptor names, a relative lack of cross-referencing to other ontologies and a flat ontological structure for classifying traits. We also evaluated the Minimal Information About a Phenotyping Experiment and FAIR compliance of bambara trait datasets curated within the CropStoreDB schema. We discuss specifications for a more systematic and generic approach to trait controlled vocabularies, which would benefit from representation of terms that adhere to Open Biological and Biomedical Ontologies principles. In particular, we focus on the benefits of reuse of existing definitions within pre- and post-composed axioms from other domains in order to facilitate the curation and comparison of datasets from a wider range of crops. Database URL: https://www.cropstoredb.org/cs_bambara.html

Sequential MyD88-Independent and -Dependent Activation of Innate Immune Responses to Intracellular Bacterial Infection

AbstractMicrobial infections induce chemokine and cytokine cascades that coordinate innate immune defenses. Infection with the intracellular bacterial pathogen Listeria monocytogenes induces CCR2-dependent monocyte recruitment and activation, an essential response for host survival. Herein we show that invasive L. monocytogenes, but not killed or noninvasive bacteria, induce secretion of MCP-1, the requisite chemokine for monocyte recruitment. Induction of MCP-1, but not TNF or IL-12, following L. monocytogenes infection is MyD88 independent. Consistent with these results, MyD88 deficiency does not impair monocyte recruitment to L. monocytogenes infected spleens, but prevents monocyte activation. Our results indicate that distinct microbial signals activate innate immune responses in an ordered, step-wise fashion, providing a mechanism to specify and modulate antimicrobial effector functions

Development of GCP Ontology for Sharing Crop Information

The Generation Challenge Programme (GCP &#x2013; &#x22;http://www.generationcp.org&#x22;:http://www.generationcp.org) is a globally distributed crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. GCP adopted the development paradigm of a &#x2018;model-driven architecture&#x2019; to achieve the interoperability and integration of diverse GCP data types that are available through distributed data sources and consumed by end-user data analysis tools. Its objective is to ensure semantic compatibility across the Consortium that will lead to the creation of robust global public goods from GCP research results. &#xd;&#xa;&#xd;&#xa;The GCP scientific domain model is an object model that encapsulates key crop science concepts and is documented using Unified Modeling Language (see GCP Models on &#x22;http://pantheon.generationcp.org/index.php&#x22;:http://pantheon.generationcp.org/index.php). &#xd;&#xa;&#xd;&#xa;At the core of the GCP architecture is a scientific domain model, which is heavily parameterized with GCP-indexed ontology terms. The GCP-indexed ontology reuses established international standards where available, converts other publicly available controlled vocabularies into formally managed ontology, and develops novel ontology if no public vocabularies yet exist. General and crop-specific GCP ontologies are being developed by crop teams involving GCP and external scientific experts &#x2013; in particular, for crop-specific ontology relating to plant anatomy, developmental stage, trait and phenotype for selected GCP crops. Crop ontologies are being developed for chickpea, maize, Musa, potato, rice, sorghum and wheat. The Bioversity crop descriptor lists already loaded into OBO format files provide the primary structure to develop the crop ontologies. Then, terms to be mapped to the ontologies are extracted from the crop databases where trait values have been stored by crop scientists. These sources allow the ontology teams to identify the most commonly used concept names and their interrelations. Experts validate the selection of keywords that will build the controlled vocabulary. &#xd;&#xa;&#xd;&#xa;These GCP ontologies will allow researchers and end users to query keywords related to traits, plant structure, growth stage, and molecular function, and link them to associated phenotyping and genotyping data sets including data on germplasm, crop physiology, geographic information, genes, QTL, etc. To reach that stage, the crop ontologies will be integrated into the data-entry user interface or data templates as picklists facilitating data annotation and submission of new terms. In addition, the GCP ontologies will be integrated with Plant Ontology (PO) and Gramene (Trait Ontology, TO; Environment Ontology, EO) to develop a common, internationally shared crop trait and anatomy ontology. The team will initiate collaboration with SONet (Scientific Observations Network) and OBOE (Extensible Observation Ontology), which proposed to integrate the GCP ontology as a study case.&#xd;&#xa;The Open Biomedical Ontologies (OBO) edit tool has been used to develop the ontologies for rice, wheat and maize traits, which are currently available at &#x22;http://cropforge.org/projects/gcpontology/&#x22;:http://cropforge.org/projects/gcpontology/ . The crop-specific work plans and ontologies related to other materials are published at &#x22;http://pantheon.generationcp.org&#x22;:http://pantheon.generationcp.org. &#xd;&#xa;The development and curation of general-purpose ontologies will be continued and made available on the Pantheon and CropForge websites

Rice Galaxy: An open resource for plant science

Background: Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high-density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non−computer savvy rice researchers. Findings: The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. The Rice Galaxy web server and deployment installer includes tools for designing single-nucleotide polymorphism assays, analyzing genome-wide association studies, population diversity, rice−bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented. Conclusions: Rice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science

Identification of orthologous regions associated with tissue growth under water-limited conditions

Plant recovery from early season drought is related to the amount of biomass retained during stress and biomass production after the end of stress. Reduction in leaf expansion is one of the first responses to water deficit. It is assumed that the control of tissue development under water deficit contributes to traits such as early vigor, as well as maintenance of growth of reproductive organs. To dissect the underlying mechanisms controlling tissue expansion under water-limited conditions, we used a multilevel approach combining quantitative genetics and genomics. To identify orthologous genetic regions controlling tissue growth under water-limited conditions a series of QTL mapping and microarray gene expression studies were conducted in rice and maize. Results of differentially expressed genes from microarray experiments, QTLs and candidate genes related to growth in the different species are compared on consensus maps (within species) and then on synteny maps (between species), to identify common genetic regions between rice and maize

Efecto del uso de un secador solar tipo invernadero para la deshidratación de alfalfa (Medicago sativa l. var. zaino)

El objetivo del estudio fue determinar el efecto del uso de un secador solar tipo invernadero para la deshidratación de alfalfa (Medicago sativa L. var Zaino), las variables evaluadas fueron la humedad relativa y temperatura dentro y fuera del secador solar, los porcentajes de proteína bruta y materia seca parcial. El tamaño de partícula de la alfalfa fue reducido manualmente previo a su ingreso al secador solar donde permaneció durante 4 días para su estudio. Se le realizó a la muestra 2 exámenes bromatológicos completos, el primero antes de ser ingresada la muestra al secador y la segunda al salir de el. La temperatura, humedad relativa y el contenido de materia seca parcial de la muestra fueron evaluadas diariamente. El secador solar tipo invernadero a pesar de alcanzar en su interior niveles de temperatura y humedad mayores a los alcanzados fuera del mismo, no es capaz de producir alfalfa deshidratada, debido a los factores climáticos que afectaron el área de la ciudad de Guatemala, durante el período de evaluación