Location: Plant Science Research
2024 Annual Report
Objectives
1. Develop genomic tools to enhance genetic selection of alfalfa for beneficial traits.
Subobjective 1.A: Develop a reference genome sequence for cultivated alfalfa to facilitate breeding and genome editing for agronomic traits.
Subobjective 1.B: Utilize universal DNA markers for accelerating breeding in alfalfa for improved forage digestibility.
Subobjective 1.C: Utilize universal DNA markers for accelerating breeding in alfalfa for root system architecture.
2. Establish innovative, science-based methods and standards for assessing and evaluating alfalfa quality for multiple end uses.
Subobjective 2.A: Develop new tools for enhancing nutritive value of alfalfa.
Subobjective 2.B: Investigate cell wall lignification and digestion in alfalfa with reduced lignin concentrations.
3. Develop germplasm and crop management strategies to enhance productivity and environmental resiliency of forages.
Subobjective 3.A: Evaluate expression of antimicrobial proteins for enhancing disease resistance in alfalfa.
Subobjective 3.B: Map genes for resistance to Aphanomyces root rot.
Subobjective 3.C: Evaluate seed treatments for enhancing germination and establishment of alfalfa plants.
Subobjective 3.D: Evaluate modified alfalfa plants for phosphate uptake to remediate soil and reclaim phosphate.
Subobjective 3.E: Evaluate alfalfa plants with an edited disease susceptibility gene for altered responses to pathogens.
Subobjective 3F: Develop genomic and management strategies to reduce winterkill and increase persistence of alfalfa.
4. Develop knowledge and tools to increase understanding of the interactions among forage crops, soil nutrients, soil and plant health, and animal productivity.
Sub-objective 4.A: Compare conventional and novel crop rotations utilizing forages for their effect on greenhouse gas emissions, C sequestration, nutrient cycling, and beneficial and pathogenic microbial populations.
Sub-objective 4B: Measure effects of dairy manure application on productivity of alfalfa and rotational crops, forage quality, and soil health.
Subobjective 4.C: Develop and utilize novel methods to identify and characterize pathogens of alfalfa.
Approach
Alfalfa is the most widely grown perennial forage crop in the U.S. and plays key roles in livestock nutrition, protecting water and soil resources, enhancing soil fertility, and sequestering soil carbon. However, there has been slow progress in alfalfa improvement and the contributions of alfalfa to agroecosystem sustainability are undervalued. To meet these needs, we aim to develop tools to accelerate breeding; test strategies to improve stand establishment and persistence; and measure carbon dioxide emissions, carbon sequestration, and nutrient cycling benefits of alfalfa in crop rotations and in the broader dairy production system. We will sequence and assemble the genome of alfalfa and provide web-accessible platforms to retrieve data. New breeding strategies including genome editing will be used for improving forage quality and stress tolerance. New seed treatments will be tested for improving stand establishment and soil indexing methods will be developed to determine risk of soilborne diseases. In-depth analyses of stem cell wall development and ruminal degradation will be done to gain a better understanding of developmental and structural changes that improve forage quality. Conventional and novel crop rotations utilizing forages will be evaluated for their effect on greenhouse gas emissions, carbon sequestration, nutrient cycling, and beneficial and pathogenic microbial populations. The effect of dairy manure application on productivity of alfalfa and rotational crops, forage quality, and soil health will be measured. The research will be of use to public and private plant breeders who will utilize the alfalfa genome sequence, markers, and breeding strategies in developing new cultivars; alfalfa farmers who will use soil indexing methods and seed fungicides to reduce damage from plant diseases; and the dairy food industry which has increased emphasis on reducing the environmental impacts of dairy, especially greenhouse gas emissions.
Progress Report
This is the final report for this project which terminated in January 2024. Over the life of this project, significant progress was made on all objectives and all milestones were met or substantially met. In support of Objective 1, a haplotype resolved reference genome for the alfalfa genotype RegenSY27x was completed and annotated. Long-read DNA sequences were assembled with the aid of genetic mapping and mapping chromosome interactions. Annotation was done with the use of sequenced gene transcripts from roots, nodules, leaves, stems, and flowers. The RegenSY27x assembly was uploaded to the Legume Information Systems website (LIS) and integrated into the blast alignment tool, the Genome Context Viewer tool, and other LIS tools. Assembly and annotation of eight additional genotypes varying in fall dormancy response is nearing completion. In collaborative research with researchers at Breeding Insight, Cornell University, a panel of 3,000 single nucleotide polymorphic (SNP) markers were developed and used to map the location of genes involved in resistance to the disease Aphanomyces root rot (ARR) as well as other agronomic traits. Candidate genes for resistance to race 1 and race 2 of ARR were identified, which can be verified and used for developing markers for breeding disease resistant alfalfa cultivars. Marker-trait analyses for stem strength, stem color, stem structure, and winter injury were completed using the Breeding Insight markers with genome wide association, random forest, support vector machine, and extreme gradient boost machine learning methods. Heritability was estimated for the five traits, and SNP markers linked to traits were identified. Data collection for stem digestibility traits was completed and marker-trait association analysis is in progress. The Breeding Insight SNP marker panel was also used for association mapping of root morphology traits to accelerate development of germplasm with improved nitrogen fixation, drought tolerance, and C-sequestration as well as to genotype populations tested for winter survival and plant biomass production. Machine learning was used to develop improved phenotyping methods for root traits and to develop an application for measuring forage maturity.
In support of Objective 2A, transgenic plants previously selected for expression of fatty acyl-coenzyme A (CoA) diphosphatase (FIT2) and acyl-CoA:diacylglycerol acyltransferase (DGAT2) were imaged using confocal microscopy to quantify the location and number of lipid droplets. The same plants were used to characterize lipid profiles and quantify gene expression. Additionally, plants with both FIT2 and DGAT2 were imaged, and tissue collected for lipid characterization and gene expression. All data for this project have been analyzed and a manuscript is in preparation. In support of Objective 2B, 800 clones of five selected cultivars/lines were established and overwintered in two geographical locations. These plants were harvested at vegetative, bud, early flower, and green pod stages at both locations. Physical stem characteristics were recorded, the seventh internode stored for future microscopic imaging and in vitro digestion analysis, and herbage was collected for forage quality analysis. In collaboration with the U.S. Dairy Forage Research Lab, a database of plant traits associated with animal production characteristics was developed.
In support of Objective 3, ten fungicides were tested for activity against pathogens causing seed rot and damping- off of alfalfa to identify those that could have broad activity. Several were selected for testing with single pathogen bioassays, bioassays with field soil, and field testing using treated seeds. A fungicide that combines metalaxyl, prothioconazole, and penflufen was found to have broad activity and could provide early season protection against target pathogens. Plants with mutated PHOSPHATE2 (PHO2) genes, which play pivotal roles in phosphate (Pi) signaling in plants, were mated with wildtype plants to transfer the Pi hyperaccumulation trait into different genetic backgrounds. Analysis of these plants identified a suite of single, double, triple, and quadruple mutations. A Pi analytical assay was developed to quantify Pi concentration in the mutant and wild-type plants and a 5 to 10x fold increase in Pi concentration was confirmed in the mutant plants. Field trials were attempted with the gene edited plants, but the high number of winter-killed plants prevented analysis of Pi uptake under field conditions. New experiments to measure Pi uptake in both the greenhouse and the field are underway.
In support of Objective 4A, 4 years (2020 – 2023) of eddy covariance data were collected in two fields managed with contrasting approaches to continuous living cover (CLC). The perennial CLC field consisted of an alfalfa- intermediate wheatgrass system, while the annual CLC consisted of silage corn-winter camelina- soybean (2020 – 2021) followed by spring wheat-winter camelina-soybean (2022 – 2023). Additional data collection included annual spring soil sampling to 90-cm depth to measure soil organic carbon (SOC), biweekly static-chamber based estimates of greenhouse gas (GHG) flux, crop leaf area index, crop height, and annual yield. Soil and GHG flux data from the project are currently being analyzed and will be published in multiple manuscripts in FY25. This experiment will continue into the next 5-year project. In support of Objective 4B, measuring the effects of dairy manure application on alfalfa productivity and soil health, the fifth and final year of soil sampling was conducted at three research locations across Minnesota in fall 2023. Soils have been dried, ground, and analyzed for soil fertility, SOC, and mineralizable carbon (C). Data analysis and manuscript preparation are underway. In support of process-based modelling to examine tradeoffs in C, water, and nutrient flows associated with dairy forage production, data analysis of baseline and alternative alfalfa management soil C modeling and life cycle analysis was completed, and the manuscript will be submitted this fiscal year in collaboration with university faculty. We found that in Minnesota and Wisconsin, GHG and fossil energy impact for haylage were 137 kg CO2 eq. per ton dry matter (DM) and 985 MJ per ton DM, respectively, at the point of harvest on-field. At the point of feeding stored forage, GHG emissions were 163 kg CO2 eq. per ton DM and fossil energy use was 1244 MJ per ton DM in the base case scenario. Fertility inputs, soil N2O emissions processes, and cropping related fuels are the single largest consistent contributors to impact. Simulated soil C storage by alfalfa had little impact on the overall C footprint of alfalfa hay or haylage on a 100-year time horizon, but greater frequency of alfalfa in rotations may decrease the overall C footprint of milk production by displacing more C-intensive annual forage such as silage corn. The climate mitigation potential of changes in SOC is not commonly or consistently included in C footprints of agricultural products. When assessing the net GHG impact of management practices, soil C storage is often aggregated with non-CO2 (N2O and CH4) emissions after converting all components to CO2 equivalents (CO2e) and assuming a given time horizon (TH), in what is known as stock change accounting. However, such analyses do not consider potential re-emission of soil C or apply consistent assumptions about time horizons. In our recently published manuscript, we demonstrate that tonne-year accounting provides a more conservative estimate of the emissions offsetting potential of soil C storage compared to stock change accounting. Tonne-year accounting can be used to reconcile differences in the context and timeframes of soil C sequestration and non-CO2 GHG emissions. Analysis of a microcosm experiment testing the roles of biotic and abiotic factors in determining how soil fungal communities respond to dairy manure amendments was completed. Similar to previous observations for bacteria, results suggest that indigenous soil fungi primarily respond to abiotic inputs associated with manure, and that individual taxa that responded to manure inputs varied among soils from different sites. However, manure tended to reduce fungal diversity consistently among soils. Few fungal taxa were associated with manure, and these did not tend to persist in soil. Additional metagenomic sequencing and reanalysis of microbial communities from soils that received a single high-rate application of manure were conducted. Preliminary results that manure had minimal impacts on the composition and diversity of soil communities, and that 'priming' effects were not apparent in the following growing season. Rather, within- and among-site spatial variation and crop rotational phase remained primary drivers of soil microbiomes at each time point. Soil, rhizosphere, and root samples were collected to evaluate the impacts of different manure application strategies on soil and alfalfa-associated microbiomes. Preliminary analyses suggest that surface broadcast and banding applications had greater impacts on soil communities than did shallow injection and were enriched with putative manure-borne bacteria. These differences were also reflected in microbial communities in alfalfa rhizospheres. Manuscripts describing the response of microbial communities to a single high-rate of dairy manure and cropping phase and the influence of manure application strategy on soil and alfalfa-associated microbiomes are in progress. Under Objective 4C, microbial communities in soil and plant samples were characterized in eight sites with poor alfalfa seedling establishment. Several novel alfalfa pathogens were identified and a widespread soybean pathogen was shown for the first time to cause root rot of alfalfa.
Accomplishments
Review Publications
Zhao, D., Mejia-Guerra, K., Mollinari, M., Samac, D.A., Irish, B.M., Heller-Uszynska, K., Beil, C., Sheehan, M. 2023. A public mid-density genotyping platform for alfalfa (Medicago sativa L.). Genetic Resources. 4(8):55-63. https://doi.org/10.46265/genresj.EMOR6509.
Poudel, K., Sheaffer, C., Jungers, J., Weihs, B.J., Lamb, J., Bauder, S., Piscasso, V., Heuschele, D.J., Xu, Z. 2023. Quantifying winter survival of alfalfa (Medicago sativa L.). Agronomy Journal. 116(1):170-179. https://doi.org/10.1002/agj2.21487.
Bhandari, K., Rusch, H., Heuschele, D.J. 2023. Alfalfa stem cell wall digestibility: current knowledge and future research directions. Agronomy. 13(12). Article 2875. https://doi.org/10.3390/agronomy13122875.
Moya, Y.S., Medina, C., Herrera, B., Chamba, F., Yu, L., Xu, Z., Samac, D.A. 2023. Genetic mapping of tolerance to bacterial stem blight caused by Pseudomonas syringae pv. syringae in alfalfa (Medicago sativa L.). Plants. 13(1). https://doi.org/10.3390/plants13010110.
Alexander, J.R., Gamble, J.D., Venterea, R.T. 2024. Stock change accounting overestimates the potential climate benefit of soil carbon storage. Soil Science Society of America Journal. 88:745–752. https://doi.org/10.1002/saj2.20643.
Lipps, S., Castell-Miller, C.V., Morris, C.E., Ishii, S., Samac, D.A. 2024. Diversity of strains in the Pseudomonas syringae complex causing bacterial stem blight of alfalfa (Medicago sativa) in the United States. Phytopathology. 114(4):802-812. https://doi.org/10.1094/PHYTO-02-23-0059-R.