Samuel Roberts Noble Foundation
Samuel Roberts Noble Foundation
Samuel Roberts Noble Foundation | Date: 2017-01-11
The present disclosure provides methods for regulating stomata in plants, improving drought tolerance, and increasing resistance to bacterial pathogens through overexpression of genes NHR1 or GCN4. Also provided are transgenic plants with improved drought tolerance and increased resistance to bacterial pathogens produced by such methods.
Roossinck M.J.,Samuel Roberts Noble Foundation
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2010
The vast majority of well-characterized eukaryotic viruses are those that cause acute or chronic infections in humans and domestic plants and animals. However, asymptomatic persistent viruses have been described in animals, and are thought to be sources for emerging acute viruses. Although not previously described in these terms, there are also many viruses of plants that maintain a persistent lifestyle. They have been largely ignored because they do not generally cause disease. The persistent viruses in plants belong to the family Partitiviridae or the genus Endornavirus. These groups also have members that infect fungi. Phylogenetic analysis of the partitivirus RNAdependent RNA polymerase genes suggests that these viruses have been transmitted between plants and fungi. Additional families of viruses traditionally thought to be fungal viruses are also found frequently in plants, and may represent a similar scenario of persistent lifestyles, and some acute or chronic viruses of crop plants may maintain a persistent lifestyle in wild plants. Persistent, chronic and acute lifestyles of plant viruses are contrasted from both a functional and evolutionary perspective, and the potential role of these lifestyles in host evolution is discussed. © 2010 The Royal Society.
Dai X.,Samuel Roberts Noble Foundation |
Zhao P.X.,Samuel Roberts Noble Foundation
Nucleic Acids Research | Year: 2011
Plant endogenous non-coding short small RNAs (20-24 nt), including microRNAs (miRNAs) and a subset of small interfering RNAs (ta-siRNAs), play important role in gene expression regulatory networks (GRNs). For example, many transcription factors and development-related genes have been reported as targets of these regulatory small RNAs. Although a number of miRNA target prediction algorithms and programs have been developed, most of them were designed for animal miRNAs which are significantly different from plant miRNAs in the target recognition process. These differences demand the development of separate plant miRNA (and ta-siRNA) target analysis tool(s). We present psRNATarget, a plant small RNA target analysis server, which features two important analysis functions: (i) reverse complementary matching between small RNA and target transcript using a proven scoring schema, and (ii) target-site accessibility evaluation by calculating unpaired energy (UPE) required to 'open' secondary structure around small RNA's target site on mRNA. The psRNATarget incorporates recent discoveries in plant miRNA target recognition, e.g. it distinguishes translational and post-transcriptional inhibition, and it reports the number of small RNA/target site pairs that may affect small RNA binding activity to target transcript. The psRNATarget server is designed for high-throughput analysis of next-generation data with an efficient distributed computing back-end pipeline that runs on a Linux cluster. The server front-end integrates three simplified user-friendly interfaces to accept user-submitted or preloaded small RNAs and transcript sequences; and outputs a comprehensive list of small RNA/target pairs along with the online tools for batch downloading, key word searching and results sorting. The psRNATarget server is freely available at http://plantgrn.noble.org/psRNATarget/. © 2011 The Author(s).
Udvardi M.,Samuel Roberts Noble Foundation |
Poole P.S.,John Innes Center
Annual Review of Plant Biology | Year: 2013
Symbiotic nitrogen fixation by rhizobia in legume root nodules injects approximately 40 million tonnes of nitrogen into agricultural systems each year. In exchange for reduced nitrogen from the bacteria, the plant provides rhizobia with reduced carbon and all the essential nutrients required for bacterial metabolism. Symbiotic nitrogen fixation requires exquisite integration of plant and bacterial metabolism. Central to this integration are transporters of both the plant and the rhizobia, which transfer elements and compounds across various plant membranes and the two bacterial membranes. Here we review current knowledge of legume and rhizobial transport and metabolism as they relate to symbiotic nitrogen fixation. Although all legume-rhizobia symbioses have many metabolic features in common, there are also interesting differences between them, which show that evolution has solved metabolic problems in different ways to achieve effective symbiosis in different systems. © Copyright ©2013 by Annual Reviews. All rights reserved.
Samuel Roberts Noble Foundation | Date: 2015-10-29
A system and methods for trapping animals including an enclosure adapted to be suspended above a trap area. The enclosure may be movable from the suspended position to a lowered position to enclose a trap area. The system further includes a user-directed control system to remotely control the position of the enclosure in order to trap animals within the enclosure.
Samuel Roberts Noble Foundation | Date: 2015-03-18
A trail camera that provides improved image capture performance in no-light or low-light conditions by using an image sensor that is sensitive to low-light conditions and has a sensitivity range encompassing visible and near infrared wavelengths. The image sensor may produce monochromatic image signals to be more sensitive and provide higher contrast imagery in both day and night conditions. The trail camera may use multiple communications channels to wirelessly communicate both locally and via a wide-area communications network. The trail camera may have a wide field-of-view, and further incorporate a motion sensor that has a like, aligned field-of-view. The trail camera may communicate image data, both still images and video images, to a remote user over the wide-area communication network. The trail camera further may transmit captured video images to a remote user without material time-shift, allowing the user to monitor a targeted area, day or night, in real-time. The trail camera may use a local communication protocol to communicate with, including command and control of or receive information/data from, devices, mechanisms and/or sensors external to the trail camera.
Samuel Roberts Noble Foundation | Date: 2015-09-23
Some illustrative embodiments of a system for estimating forage growth at an area of interest may include a mobile support, a laser sensor, and an ultrasonic sensor. The laser sensor and the ultrasonic sensor may each be supported by the mobile support, and may each be configured to sense the forage growth at the area of interest. The laser sensor may generate laser forage data corresponding to the forage growth, and the ultrasonic sensor may generate ultrasonic forage data corresponding to the forage growth. A measured forage growth value may be determined as a function of the laser forage data and the ultrasonic forage data.
Agency: NSF | Branch: Standard Grant | Program: | Phase: ADVANCES IN BIO INFORMATICS | Award Amount: 815.31K | Year: 2015
Understanding the mechanisms of genotype and phenotype (G2P) associations has been an important and challenging task in modern biology. The challenge lies in the high-dimensional gene variables and the complexity of gene regulation and interactions that collectively define particular phenotypes (also called traits). The project will develop innovative methods, tools and bioinformatics systems to decipher the plant G2P associations through integrative genome-scale biological network and genome-wide association analysis. A breakthrough in this work will lead to a systems-level understanding of how biological processes, pathways and complex traits in plants are hierarchically regulated. Advancing such fundamental knowledge will greatly benefit modern genome-assisted plant breeding by providing the underlying regulatory mechanisms and key regulators of agriculturally important traits. This in turn will have great potential to be translated into new means of improving plant quality and production for agriculture, thus benefiting society as a whole. Cutting-edge technologies will be developed to study G2P associations in plants, providing excellent opportunities for training undergraduates, graduates and postdocs in interdisciplinary fields such as computational biology, bioinformatics, plant genomics, and statistical genetics, at the three institutes. Underrepresented minorities and women will be especially targeted in the recruitment of the project. The research will form the basis of the proposed educational workshops centering on bioinformatics and statistical genetics. Creative and innovative hands-on outreach activities will be arranged through the three institutes? outreach programs with local K-12 schools to inspire young minds to become bioinformatics scientists.
Innovative methods will be developed to analyze genome-scale biological networks and genome-wide associations through a fully integrated bioinformatics platform, enabling the discovery of G2P associations in plants. Specific aims of the project include 1) to develop novel top-down and bottom-up graphical Gaussian model (GGM) algorithms to reconstruct the hierarchical gene networks that control biological processes and pathways; 2) to develop models and algorithms that enable large-scale marker-trait association analysis with high precision using novel statistical genetics approaches; and 3) to develop a Graph-search-empowered integrative bioinformatics platform to facilitate the integration, deciphering and discovery of G2P associations. To validate our approaches and tools, public data from genome-wide plant omics studies and genome-wide association studies (GWAS) will be integrated and analyzed, associating traits with SNP markers and fine-tuning the prediction of phenotype-associated hierarchical and/or pleiotropic regulators and functional networks. The novel knowledge and analytic methods and tools yielded from this project will be disseminated into the public at large through presentations, publications and web applications. All the tools and data resources will be made freely available at http://plantgrn.org/ to the plant research communities, accelerating plant bioinformatics and plant science research, education and applications.
Agency: NSF | Branch: Continuing grant | Program: | Phase: PLANT GENOME RESEARCH PROJECT | Award Amount: 1.76M | Year: 2015
PI: Wolf Scheible (The Samuel Roberts Noble Foundation)
Co-PIs: Michael Udvardi and Patrick Xuechun Zhao (The Samuel Roberts Noble Foundation) and Hideki Takahashi (Michigan State University)
Key Collaborators: Michael Sussman (University of Wisconsin-Madison), Hiroo Fukuda (University of Tokyo, Japan), and Fiona McAlister (Southern Oklahoma Technology Center, Ardmore, OK)
Small signaling peptides (SSPs) emerge as an important class of regulatory molecules in plants, especially in the control of plant growth and development in response to environmental cues. Only a few of the many SSPs encoded in plant genomes have been characterized functionally in plants. In this respect, SSP-encoding genes represent some of the potentially most important dark matter of plant genomes. Medicago truncatula is a premier model legume species, which is closely related to the most important forage species in the USA, Medicago sativa (alfalfa), and to food legumes such as soybean and common bean. Legumes are key components of sustainable agricultural systems because they form symbioses with bacteria called rhizobia that reduce molecular nitrogen to ammonium in specialized root organs called nodules. Symbiotic nitrogen fixation provides legumes with a source of nitrogen, obviating the need for synthetic nitrogen fertilizers for these important crop species. Recently, it has become clear that SSPs can control both nodule and root development in legumes and the hunt is on for more SSPs that control important developmental traits in legumes of importance to agriculture. A priority objective of this project therefore is to identify novel SSPs that affect root and nodule development in M. truncatula, with a long-term view of using SSPs in non-transgenic approaches to improve plants for agriculture. Datasets and biological materials generated in this project will be made available through appropriate biological databases and stock centers. A database (MtSSPdb) will be developed and maintained for both project and public access to store, link and present the information on the comparative genomics of peptide-coding genes and to integrate and manage all experimental data emerging from this project. With regard to outreach and training, the project will leverage existing programs to provide research training for postdoctoral associates and graduate, undergraduate and high school students.
A multidisciplinary strategy will be implemented, including bioinformatics, chemical genomics, genetics, biochemistry, molecular and developmental biology. Activities of this project comprise a genome-wide survey of SSP-encoding genes in Medicago truncatula and the identification of macronutrient (N, P, S, and K) -responsive SSP-encoding genes from transcriptome data. A library of genome-encoded, synthetic peptides will be established as a community resource for biochemical genetics and used to screen for developmental and molecular phenotypes in M. truncatula. Constitutive overexpression lines will be produced in Arabidopsis thaliana and M. truncatula for selected SSP-encoding genes that are prioritized because they have been shown to be either strongly responsive to macronutrients (N, P, S, K), produce strong visual/molecular phenotypes when chemically synthesized peptides are exogenously applied to M. truncatula, and/or have their mature peptides predicted to be produced through posttranslational modifications that make chemical synthesis and/or exogenous application impracticable. The synthetic peptides will be further tested for their effects on root nodule development and nitrogen fixation in M. truncatula. The Medicago HAPMAP genotypes will be employed to identify genetic loci associated with natural diversity in response to bioactive peptides, and specific SSPs will also be tested for their efficacy in improving alfalfa performance in the field. Identification of a peptide receptor through genetic or chemo-proteomic approaches is another activity included in this project.
Agency: NSF | Branch: Standard Grant | Program: | Phase: PLANT GENOME RESEARCH PROJECT | Award Amount: 499.79K | Year: 2015
Nitrogen (N) is an essential element of many biomolecules and is crucial for life on earth. Nitrogen is a key driver of plant productivity for food, feed, fiber and fuel, and insufficient N in soils often limits agricultural productivity. Industrial/synthetic N-fertilizers have removed the N-limitation in many agricultural systems, although over-use of N-fertilizers threatens the environment and, ultimately, the sustainability of such systems. On the other hand, millions of resource poor farmers, especially in developing countries, cannot afford the expensive N-fertilizers to boost production and as a result suffer from very low crop yields. There is growing international awareness of these two main problems associated with N in agriculture as well as the need to coordinate funding and research to solve the problems at an international level. This project will establish the Plant Nitrogen Network (PlaNNet), an NSF Research Coordination Network (RCN) of researchers and other stake-holders within the U.S.A. and around the world that will play a leading role in designing and implementing research and development (R&D) strategies to address the problems of N in agriculture in different parts of the world.
Global challenges require global responses. Feeding 9 billion people in 2050 and maintaining stable food supplies into the distant future will require more-sustainable solutions to agricultures N problems. Lack of coordination in R&D related to plant-N results in a global effort that is not as focused, efficient, and effective as it could be. This RCN aims to coordinate research activities related to the supply and utilization of N by plants with the long-term objective of enhancing the efficiency and sustainability of N-use in agriculture. Research challenges and opportunities include improving nitrogen use efficiency (NUE) in crop and pasture plants and exploiting biological nitrogen fixation in both natural and synthetic systems. Optimization of N-use in agriculture will also require improved agriculture management practices. PlaNNet will help to connect basic and applied researchers to facilitate a concerted effort to solve agricultures N-problems. Research coordination network (RCN) activities will include: (i) development of a networking website that includes information about hundreds of researchers within the U.S.A. and around the world who are involved in plant N-related research, opportunities for collaboration, and educational resources; (ii) annual Workshops-Without-Walls, virtual meetings that will involve hundreds of participants in presentations, discussions, and consensus-building related to plant-N research and development; and (iii) satellite workshops at major conferences focused on specific aspects of plant N and agriculture. The activities of the RCN will be coordinated by a PlaNNet Steering Committee (SC) that will be composed of a broad cross section of the nitrogen research community balanced among different demographic groups.