Author: orandall

Nematodes are among the top yield-robbers encountered by soybean farmers across the U.S. Almost all SCN resistant varieties in U.S. soybean production are derived from two genetic sources, imposing risk of genetic vulnerability and resistance breakdown. Soybean breeders and growers are limited in genetic sources for nematode resistance with competitive yield, which places U.S. soybean production at risk. Discovery of novel nematode resistance from genetically diverse sources is essential for sustainable soybean production. Deployment of resistant varieties will improve U.S. soybean production and protect yields and farmers’ income.

Our team has successfully developed a strong pipeline of soybean germplasm with resistance to SCN or RKN and competitive yield across all maturity groups. Based on previous discoveries, many genetic populations have been developed to confirm and deploy these genes for nematode resistance. In this new proposal, this team will use an integrated conventional and advanced genomic technologies to achieve the following objectives: 1) incorporate nematode resistance genes into elite high-yielding lines to develop SCN and/or RKN resistant soybean varieties in MG 0 through VIII; 2) identify novel sources of multiple nematode resistance from existing resistant sources or soybean germplasm from USDA Soybean Germplasm Collections; 3) map nematode resistance gene(s) to develop DNA markers for efficient breeding selection; and 4) incorporate SCN and/or RKN resistance into high-yielding lines with value-added seed composition or other key abiotic and biotic tolerance traits.

This work will benefit the entire value chain by providing new soybean varieties adapted to local growing conditions with resistance to multiple nematode species. This project will also provide new and improved materials to commercial and public breeders for use as parental stocks to develop high-yielding, nematode resistant varieties. DNA markers and QTL information generated will benefit soybean researchers, enabling marker-assisted selection and seeking understanding of the genetic mechanisms underlying nematode resistance.

Funder: U.S. Department of Energy

Amount: $333,489

PI: Zenglu Li, College of Agricultural and Environmental Sciences

Even in fungal model systems, up to 40% of genes have unknown or poorly characterized functions with no informative homologies in databases. Fungi tolerate a variety of stressful environments, including a wide range of temperature and moisture levels. The same fungal species isolated from different environments often shows variation in its genetic complement. Studies of pan-genomes (the full genetic complement of a species assembled from varied individuals) have identified core genes (present in all isolates), accessory genes (present in >1 isolate) and singleton genes (present in only 1 isolate). Accessory and singleton genes are much more likely to have an unknown or poorly characterized function, presumably because these genes have evolved or been retained only in a subset of environments.

We propose to exploit natural variation in two fungal species to identify genes of unknown function that allow them to survive across temperature and moisture ranges. We have previously collected isolates of the filamentous fungus Aspergillus fumigatus and the yeast Saccharomyces paradoxus from a range of urban, natural, and agricultural environments in North America. Our collection sites spanned a wide range of temperature and moisture levels, and we already have WGS data for many of the isolates.

We propose to construct pan-genomes for A. fumigatus and S. paradoxus and identify core, accessory, and singleton genes and genes of unknown or poorly characterized function. We will pick environmental isolates of A. fumigatus and S. paradoxus representing the environments with the most extreme temperatures (coldest and warmest) and humidity (driest and wettest) that also have the most genes of unknown or poorly characterized function. Transcriptomes will be analyzed from these strains grown under a variety of temperature and humidity levels. We will identify genes that are differentially expressed across conditions, especially those with unknown or poorly defined functions. We will create gene deletions and tags and use them in functional validation experiments for genes of unknown or poorly characterized function whose expression suggests roles in response to temperature and/or humidity variation.

Our ultimate goals are to reduce the number of genes of unknown/poorly characterized function in the filamentous fungus A. fumigatus and the yeast S. paradoxus and to discover new genes that are important for tolerance to a range of temperature and water-availability levels in these fungi. If this approach proves successful, it can be used for gene discovery in other fungi, including nonmodel systems that lack genetic tools and will allow improved prediction of the resilience of other species of environmental fungi. Though it is currently appreciated that there is environmental variation in species, this variation has not been used in the way we propose to assign gene function. Thus, the proposed experiments will serve as a guide for future work leveraging natural variation and phenotyping to assign function to fungal genes of unknown function, especially those that allow fungi to thrive in hostile environments. Understanding such genes will be helpful to the Army because fungi are notorious for degrading materials in the challenging environments where the Army’s missions often occur.

Funder: U.S. Department of the Army

Amount: $449,999

PI: Michelle Momany, Franklin College of Arts and Sciences, Department of Plant Biology

We propose to continue development of a groundwater-hydrologic model for southeast Georgia and surrounding region (Okefenokee Swamp and associated rivers). We will explore the role of groundwater flows across southeast Georgia for future climate and coastal development scenarios including the effective dispersion of scalars within the groundwater system. We will maintain a specific focus on net flow from groundwater into/out of the Okefenokee Swamp, Trail Ridge, and the St. Marys River and how this net flow is expected to change under future conditions. The model will allow us to quantify the fate of groundwater and solutes in the system. With the models we will be able to estimate impacts of mining on water levels and dispersion of solutes (tailings) in both groundwater and surface waters with particular focus on solutes potentially entering the Floridian aquifer, the Okefenokee Swamp, and the St. Marys River; how Floridan Aquifer withdrawals may influence the Okefenokee Swamp; and how mine operations and reclamation may affect the characteristics of the Surficial Aquifer and how such changes may influence the hydrologic characteristics of Trail Ridge and the Okefenokee Swamp.. Our initial

focus will be on the surficial and Floridian aquifer and their interaction with the Okefenokee Swamp and associated rivers. We will use the numerical model outputs to develop conceptual models of the water cycle in the region and estimates of solute dispersion and changes in surface water levels.

We will use the regional scale model as boundary conditions for two high resolution mine-specific models (Mission and Amelia mines). We will use these models to estimate impacts of mining on groundwater flows, water table elevations, and the dispersal of solutes under future climate scenarios.

If available, we will review the hydrologic model(s) prepared by Twin Pines’ consultants in order to understand key assumptions, model construction, and data sets and to possibly guide enhancements of our model.

Funder: Chemours Company

Amount: $552,950

PI: C. Brock Woodson, College of Engineering

The overall objective of this project is to improve the management of whiteflies and whitefly-transmitted viruses in vegetable crops in Georgia and other southeastern states. The whitefly, Bemisia tabaci, causes global economic losses including an epidemic by this pest and whitefly-transmitted viruses that severely impact vegetable and other crop production in the southeastern United States. The rapid evolution of insecticide-resistance in whitefly populations makes it unsustainable to use chemical control. We will investigate whiteflies and whitefly-transmitted viruses in vegetable cropping systems from the perspective of an ecology-based integrated pest-plant-virus management system.

Funder: USDA ARS

Amount: $4,011,522

PI: Allen Moore, College of Agricultural and Environmental Sciences

Several methods have been developed to inactivate virus particles. These inactivation methods must be effective and reliable to prevent the accidental spread of viruses. It is crucial to completely inactivate high-risk agents, such as SARS-CoV-2, before they are removed from high-level biocontainment facilities for further handling. However, it is unclear whether common methods of virus inactivation are effective in inactivating positive-sense RNA viruses. Positive-sense RNA viruses contain RNA genomes of positive polarity and include viruses which can cause serious illness in humans and often result in epidemics and pandemics. The genome of a positive-sense RNA directly serves as messenger RNA (mRNA), thus, can be immediately translated by host cells to produce infectious virions. Therefore, if viral RNA is not properly inactivated during inactivation procedures, the intact RNA can potentially cause infection if introduced into permissive cells. This underscores the need for inactivation protocols that ensure complete inactivation of viral RNA to prevent the accidental release of virus particles into the environment.

Validation for the absence of RNA infectivity after virus inactivation is rarely performed, raising significant biosecurity risks associated with positive-sense RNA viruses. Despite the widespread use of inactivating agents in research labs, there are no standardized protocols for validating RNA infectivity. Testing methods for RNA infectivity are cumbersome and require expertise in RNA, cell culture, and transfection techniques. This study will systematically evaluate the efficacy of existing viral RNA inactivation methods, focusing on their ability to render viral RNA non-infectious. We will develop reagents and protocols required for infectivity testing of viral RNA. By employing appropriate controls and rigorous validation techniques, we will establish standardized protocols for the inactivation of positive-sense viruses and their RNA.

Funder: Centers for Disease Control and Prevention 

Amount: $846,421 

PI: Lok Joshi, College of Veterinary Medicine 

New theoretical and experimental methods in chemical physics being developed by the PIs provide great opportunities for the study of molecular species and chemical reactions of fundamental importance in combustion processes. In this research, high level quantum mechanical formalisms are a significant source of critical predictions concerning molecular systems that may be challenging for experiments. Moreover, our helium droplet experiments have opened whole new vistas for the spectroscopic study of molecular species relevant to combustion environments. Theoretical developments proposed herein include a focus on obtaining highly accurate energetics for species pertinent to elementary reactions. Experimental developments include strategies to characterize transient combustion intermediates associated with low temperature hydrocarbon oxidation processes, which have been difficult to probe with other methodologies. The combination of theory and experiment to solve problems inaccessible to either alone is a hallmark of this research.

Funder: U.S. Department of Energy 

Amount: $927,610 

PI: Gary Douberly, Franklin College of Arts and Sciences, Department of Chemistry

The broader impact of this Partnerships for Innovation – Research Partnerships (PFI-RP) project is to enhance the reliability and security of electrical devices and networks within modern infrastructure including, but not limited to, buildings, manufacturing systems, and hospitals. This PFI-RP project introduces a smart sensor capable of detecting anomalies, pinpointing their locations, and diagnosing issues in electrical devices and networks. The algorithms and designs developed may also contribute to the broader field of anomaly detection and diagnosis beyond electrical signals. The project team will provide training to undergraduate and graduate students, in addition to middle school teachers. Collaborations with the Peach State Louis Stokes Alliances for Minority Participation (LSAMP) and the NSF Research Experiences for Undergraduates (REU) programs will be nurtured to support these efforts. Strategic partnerships with industry leaders offer vital insights and provide educational and leadership opportunities for graduate students and postdoctoral researchers. The project brings together a strong partnership between academia and prominent industry leaders, including General Electric (GE), United States Robins Air Force Base (RAFB), Siemens America (Siemens), and NEC Laboratories America (NEC) to explore the commercialization of an electrical sensing technology for scalable anomaly detection and diagnosis in electrical devices and networks. The impact spans from small-scale applications (e.g., homes, buildings, factories) to large-scale scenarios (e.g., distribution networks to transmission networks of main grids). This adaptability facilitates dynamic data processing, allowing the installation of varying numbers of smart sensors. Additionally, the technology offers customized programming and low-cost, flexible deployments, which can be easily installed by plugging into an electrical outlet in residential and commercial settings.

Funder: National Science Foundation 

Amount: $1,000,000 

PI: Jin Ye, College of Engineering 

Proteoglycans harboring heparan sulfate (HS) chains are widely found on cell surfaces and in extracellular matrices where they interact with growth factors, receptors, morphogens, and extracellular matrix components and play critical roles in processes such as cell survival, division, migration, differentiation, pathogen binding, and cancer development. HS biosynthesis is a complex process involving initial formation of a linker glycan on proteoglycan core proteins, priming and extension of the HS chains’ polymer backbone, facilitated by the EXT1-EXT2 heterodimeric co-polymerase complex. Homozygous defects in either of these proteins cause embryonic lethality, and heterozygous loss of function has clinical ramifications, including benign tumors. We recently solved the structure of the human EXT1- 2 heterodimeric co-polymerase in complex, providing insights into HS chain synthesis. EXT1 and EXT2 form an obligate heterocomplex of the two homologous proteins. Each protein contains two separate predicted catalytic domains, yet only one of the two domains is active in each protein suggesting that the monomers share catalytic functions. We also discovered an interaction between EXT1-2 and the HS priming enzyme EXTL3. These studies raise important new questions about HS synthesis in vivo and the nature and pathology of HME mutations. This research will advance our understanding of HS biology and its roles in health and disease. Unraveling the mechanisms governing HS backbone synthesis will shed light on the molecular basis of HS-mediated cellular processes and pave the way for future development of targeted interventions.

Funder: National Institutes of Health 

Amount: $1,331,828 

PI: Kelley Moremen, Franklin College of Arts and Sciences, Department of Biochemistry and Molecular Biology 

The project will advance scientific understanding of the effect of multiple stressors on aquatic species of interest to the Department of Defense (DoD) and promote the resilience of the spotted turtle (Clemmys guttata) under anthropogenic and climate-induced stressors on DoD installations. The relative vulnerability of coastal and inland spotted turtle populations to hydrologic alterations, connectivity, and susceptibility will be evaluated using an interdisciplinary approach composed of laboratory, field, and model work. The spotted turtle is currently under review for federal listing. All populations are vulnerable under climate scenarios that reduce wetland hydroperiod. Coastal populations are additionally vulnerable to wetland loss and saltwater intrusion from sea level rise and overwash during major storm events. Thus, hydrology is considered the major climate-induced stressor. Landscape stressors include distance to other suitable wetlands, road density, woody encroachment, and accessibility to potential poaching – a major threat to the species. Field work will focus on turtle movement, population surveys, quantifying stressors at occupied sites, collecting blood samples for measurement of chemical stressors and characterizing turtle health. Lab work will test the effects of salinity and temperature on physiological and immune responses in turtles. The omics-based assays will be conducted on a subset of biological samples collected from the field survey and controlled lab experiments. Our proposal will improve fundamental understanding of how multiple stressors interact to affect the resilience of spotted turtle populations. In addition to providing baseline population data for monitoring future trends, our work would quantify stressors and identify which stressors spotted turtles are most sensitive to, helping prioritize management actions and best management practices (BMPs) for the species.

Funder: U.S. Department of Defense 

Amount: $2,208,377 

PI: Tracey Tuberville, Warnell School of Forestry and Natural Resources

As the U.S. invests in efforts to build its capacity to lead the world in the development of artificial intelligence and other areas of computer science, it faces a critical workforce bottleneck, a shortage of computer scientists to meet workforce demands in industry and academia, coupled with a lack of gender and racial diversity. One way to effectively expand and diversify the computer science workforce is to develop a pathway from community colleges to undergraduate and graduate degree programs. Community college transfer students in computer science are a particularly high-achieving and diverse group, and community colleges are a primary entry point into higher education for many Students of Color, women, first-generation college students, and others who hold a combination of these and other historically minoritized identities in higher education. Despite the talents and assets that transfer students bring to the computer science major, they also face unnecessary barriers at their universities, which constrain their opportunities to become leaders in their field. The goal of this project is to produce new knowledge that will address these barriers and guide efforts to transform university structures, policies, and practices to foster success among community college transfer students in computer science. This study will engage a convergent, multi-phase mixed methods design. Drawing on five years of longitudinal survey and interview data from computer science transfer students and other key university agents (e.g., university faculty, staff, administrators) across six campuses in the California State University system, the project aims to address the following overarching research questions: (1) What are the structures, policies, and practices that community college transfer students identify in shaping their degree trajectories in computer science? (2) From the perspective of key university agents (e.g., advising staff, faculty, administrators), what are the relevant structures, policies, and practices that shape community college transfer student degree trajectories and opportunities in computer science? The inquiry will be informed by social cognitive career theory (SCCT) and theories of administrative burden and street-level bureaucracy. The quantitative stream of this work will rely on descriptive and multivariate analysis of student surveys and registrar data. The qualitative stream of this research will use phenomenological methods, relying on student and university agent interview data to better understand the experienced phenomena (i.e., structures, policies, and practices that shape transfer student trajectories in computer science). This approach aligns with the research questions, which collectively focus on how participants with varying positionalities (e.g., student, staff, faculty) make meaning of the structures, policies, and practices that shape community college transfer student success and degree trajectories.

Funder: National Science Foundation 

Amount: $1,496,458 

PI: Jennifer Blaney, Louise McBee Institute of Higher Education