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DOE OSTI2021

Development and validation of time‐domain 1 H‐NMR relaxometry correlation for high‐throughput phenotyping method for lipid contents of lignocellulosic feedstocks

Abstract The bioenergy crops such as energycane, miscanthus, and sorghum are being genetically modified using state of the art synthetic biotechnology techniques to accumulate energy‐rich molecules such as triacylglycerides (TAGs) in their vegetative cells to enhance their utility for biofuel production. During the initial genetic developmental phase, many hundreds of transgenic phenotypes are produced. The efficiency of the production pipeline requires early and minimally destructive determination of oil content in individuals. Current screening methods require time‐intensive sample preparation and extraction with chemical solvents for each plant tissue. A rapid screen will also be needed for developing industrial extraction as these crops become available. In the present study, we have devised a proton relaxation nuclear magnetic resonance ( 1 H‐NMR) method for single‐step, non‐invasive, and chemical‐free characterization of in‐situ lipids in untreated and pretreated lignocellulosic biomass. The systematic evaluation of NMR relaxation time distribution provided insight into the proton environment associated with the lipids in the biomass. It resolved two distinct lipid‐associated subpopulations of proton nuclei that characterize total in‐situ lipids into bound and free oil based on their “molecular tumbling” rate. The T1T2 correlation spectra also facilitated the resolution of the influence of various pretreatment procedures on the chemical composition of molecular and local 1 H population in each sample. Furthermore, we show that hydrothermally pretreated biomass is suitable for direct NMR analysis unlike dilute acid and alkaline pretreated biomass which needs an additional step for neutralization.

pretreatment↗

DOE OSTI2021

Identification and analysis of stem‐specific promoters from sugarcane and energy cane for oil accumulation in their stems

Abstract Considerable recent progress has been achieved in bioengineering oil accumulation in the vegetative tissues of plants, opening an opportunity for large scale production of biodiesel, jet fuel, lubricants, and high‐value lipid bioproducts. For the highly productive C4 crops, such as sugarcane, energy cane, Miscanthus, and fiber sorghums, the bulk of the biomass is the stem. However, little success has been made in accumulating oil in the stem. Since engineering a trait with a constitutive promoter often results in pleiotropic effects that counter trait improvement, identification of stem parenchyma‐specific promoters is a prerequisite for efficient use of the ample photoassimilates stored in mature stem parenchyma cells. In this study, we first identified two TST genes encoding homologues of tonoplast sugar transporters that were strongly and almost exclusively expressed in the stems of canes via a combination of RNA‐seq atlas analysis, in silico analysis of a sugarcane genome, phylogenetic analysis, and quantitative PCR analysis. They were further confirmed in the pith parenchyma cells of the mature stem by RNA in situ hybridization. When fused with the β‐Glucuronidase (GUS) reporter gene, the promoters of two alleles, TST2b‐1A and TST2b‐1C , from one TST gene demonstrated that they could drive the GUS expression exclusively in the stem in Arabidopsis.

09 BIOMASS FUELS↗

DOE OSTI2022

Emerging wild virus of native grass bioenergy feedstock is well–established in the Midwestern USA and associated with premature stand senescence

The North American native prairie grass Panicum virgatum (switchgrass) is a primary bioenergy feedstock candidate. Its widespread distribution and genetic diversity enable the possibility of developing this perennial grass for high production in a variety of conditions, including on marginal lands. A critical concern in feedstock development and deployment is the risk of novel pathogen emergence. Here we investigate the landscape-scale prevalence and epidemiology of a little-studied North American virus first detected in switchgrass and other grasses in bioenergy trials in the US Midwest. Switchgrass mosaic virus (SwMV, Genus Marafivirus, Family Tymoviridae) is transmitted by leafhoppers and phylogenetically sister to Maize rayado fino virus, a significant pathogen of maize in parts of the Americas. Our goal was to determine whether SwMV is uniquely limited to specific bioenergy trials or well-established and circulating more broadly. We used molecular diagnostics to quantify naturally occurring SwMV infection in leafhoppers and switchgrass in naturalistic stands throughout a large Midwestern landscape, and quantified leafhopper abundances and stand performance. Our analysis revealed that this apparently wild virus is well-established and widespread. Infection was present at nearly all sites, across diverse landscape contexts, with prevalences ranging as high as 33%–60%. Infection appeared to accumulate and persist in stands over time. It was associated with increases in premature stand senescence but not with reductions in stand height. Although wild viruses are believed to evolve benign relationships with their natural hosts, these data suggest that SwMV has potential to impact yield components. Viruses are frequently overlooked in crop development efforts, but represent the majority of emerging plant pathogens. For SwMV, it is imperative to quantify its impact on host performance, to identify the extent of any host resistance, and to assess any risks of virus spillover to agricultural plantings of other Poaceae species, including maize and sorghum.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Genetics of Flooding Tolerance in an F 2 Miscanthus sacchariflorus ssp. lutarioriparius × M. sinensis Population

Miscanthus is a warm-season, perennial grass cultivated as a feedstock for bioenergy and bioproducts. M. sacchariflorus ssp. lutarioriparius has high yield potential and is well-adapted to seasonal flooding, but little is known about the genetics of this adaptation. We conducted a quantitative trait locus (QTL) analysis on a population of 332 diploid Miscanthus ×giganteus (Mxg) F2s derived from an initial cross between diploid M. sacchariflorus ssp. lutarioriparius ‘PF30022’ and diploid M. sinensis ‘PMS-014’, followed by intermating 50 F 1 s. Using tanks in a greenhouse to assess the effects of partial submergence on actively growing plants, we compared an aerobic soil control to a 6-week flood treatment. The study's primary objectives were to (1) identify QTL for flooding tolerance in Miscanthus , (2) identify candidate genes and (3) compare ethylene response factors in Miscanthus with those in rice and Arabidopsis , sorghum and maize for binding site sequence homology and synteny, especially those associated with flooding tolerance. In total, 10 QTL and 66 candidate genes for partial submergence tolerance were identified (including many for ethylene signalling), a first report for Miscanthus . Notably, none of the Miscanthus candidates were orthologs of rice Sub1A, SK1 or SK2 , yet the ‘PF30022’ parent exhibited a snorkeling phenotype, indicating convergent evolution. This study will facilitate breeding of climate-resiliant Mxg.

abiotic stress tolerance↗

DOE OSTI2026

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

DOE OSTI2021

Plant Metabolic Network 15: A resource of genome-wide metabolism databases for 126 plants and algae

To understand and engineer plant metabolism, we need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we, in this study, generated genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants (https://plantcyc.org). Of these, 104 have not been reported before. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell type-specific metabolic pathways. This work shows the quality and quantity of our resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Increasing Rubisco as a simple means to enhance photosynthesis and productivity now without lowering nitrogen use efficiency

Summary Global demand for food may rise by 60% mid‐century. A central challenge is to meet this need using less land in a changing climate. Nearly all crop carbon is assimilated through Rubisco, which is catalytically slow, reactive with oxygen, and a major component of leaf nitrogen. Developing more efficient forms of Rubisco, or engineering CO 2 concentrating mechanisms into C 3 crops to competitively repress oxygenation, are major endeavors, which could hugely increase photosynthetic productivity (≥ 60%). New technologies are bringing this closer, but improvements remain in the discovery phase and have not been reduced to practice. A simpler shorter‐term strategy that could fill this time gap, but with smaller productivity increases (c. 10%) is to increase leaf Rubisco content. This has been demonstrated in initial field trials, improving the productivity of C 3 and C 4 crops. Combining three‐dimensional leaf canopies with metabolic models infers that a 20% increase in Rubisco increases canopy photosynthesis by 14% in sugarcane (C 4 ) and 9% in soybean (C 3 ). This is consistent with observed productivity increases in rice, maize, sorghum and sugarcane. Upregulation of Rubisco is calculated not to require more nitrogen per unit yield and although achieved transgenically to date, might be achieved using gene editing to produce transgene‐free gain of function mutations or using breeding.

Plant Sciences↗

DOE OSTI2025

Holo-Omics disentangle drought response and biotic interactions among plant, endophyte and pathogen

Holo-omics provide a novel opportunity to study the interactions among fungi from different functional guilds in host plants in field conditions. We address the entangled responses of plant pathogenic and endophytic fungi associated with sorghum when droughted through the assembly of the most abundant fungal, endophyte genome from rhizospheric metagenomic sequences followed by a comparison of its metatranscriptome with the host plant metabolome and transcriptome. The rise in relative abundance of endophytic Acremonium persicinum (operational taxonomic unit 5 (OTU5)) in drought co-occurs with a rise in fungal membrane dynamics and plant metabolites, led by ethanolamine, a key phospholipid membrane component. The negative association between endophytic A. persicinum (OTU5) and plant pathogenic fungi co-occurs with a rise in expression of the endophyte's biosynthetic gene clusters coding for secondary compounds. Endophytic A. persicinum (OTU5) and plant pathogenic fungi are negatively associated under preflowering drought but not under postflowering drought, likely a consequence of variation in fungal fitness responses to changes in the availability of water and niche space caused by plant maturation over the growing season. Our findings suggest that the dynamic biotic interactions among host, beneficial and harmful microbiota in a changing environment can be disentangled by a blending of field observation, laboratory validation, holo-omics and ecological modelling.

Chen, Peilin↗

DOE OSTI2025

Towards engineering hybrid incompatibility in plants

The potential for gene flow between genetically modified organisms (GMOs) and non-GMO relatives poses a significant challenge to the development and regulatory approval of GMO crops (Wedger et al., 2024), for example, the spread of herbicide resistance transgenes from crops such as rice or sorghum to cross-pollinating weedy species. Addressing this concern, we developed Engineered Genetic Incompatibility (EGI) (Maselko et al., 2017), a system that establishes species-like barriers to gene flow between otherwise sexually compatible populations. EGI employs Programmable Transcriptional Activators (PTAs) to drive lethal over- and/or ectopic expression of tightly regulated genes following undesired hybridization events (Figure 1a,b). A benign mutation of the target promoter in the EGI organism protects it from ill effects of the PTA, which acts as a sentinel for the wild-type (WT) promoter sequence. Given numerous potential PTA targets, multiple mutually incompatible subpopulations are feasible (Maselko et al., 2020). EGI has been demonstrated in yeast as a proof-of-concept (Maselko et al., 2017) and in insects as a strategy for genetic biocontrol of pests (Maselko et al., 2020; Upadhyay et al., 2022). EGI in plants would provide a strategy to halt gene flow between engineered crops and their domestic and wild relatives without altering normal cultivation or propagation practices. Here, we present promising results towards the demonstration of EGI in plants and highlight technical challenges that still need to be overcome.

CRISPRa↗

DOE OSTI2025

Expression of a Bacterial Trehalose 6-Phosphate Synthase Gene otsA in Camelina sativa Seeds Promotes the Channelling of Carbon Towards Oil Accumulation

Improving seed oil yield is essential for developing Camelina sativa as a sustainable biofuel crop. Fatty acid synthesis depends on the production of acetyl-CoA from photosynthetically derived sugars. Trehalose 6-phosphate (T6P), a proxy for sucrose availability, can link sugar status to plant growth and development. Synthesised by trehalose 6-phosphate synthase (TPS) from UDP-glucose and glucose-6-phosphate, T6P plays a regulatory role in metabolism. Our previous studies on Arabidopsis transgenic lines constitutively expressing the E. coli otsA (encoding TPS) showed increased T6P levels and seed triacylglycerol, along with stunted growth. In the present study we express otsA in camelina under the control of a seed-specific Phaseolin promoter. Seeds of the resulting transgenic lines accumulated high levels of T6P, and a 15%–20% increase in total fatty acids and triacylglycerol compared to wild-type. Molecular analysis showed the transgenic seeds had reduced SnRK1 activity, elevated WRI1 protein levels, and increased the levels of WRI1 and its target genes, along with enhanced rates of fatty acid synthesis that increased seed weights relative to wild type. Notably, the increase in oil did not affect seed protein levels but did reduce the soluble metabolite fraction. Crucially, seed-specific expression of otsA mitigated the growth defects associated with constitutive otsA expression, and the transgenic lines showed normal seed development and germination. These findings demonstrate that targeted T6P modulation via seed-specific otsA expression is an effective metabolic engineering strategy to boost oil production in camelina and potentially in other oilseed crops and bioenergy crops such as energycane, sorghum and miscanthus.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

RNAi and genome editing of sugarcane: Progress and prospects

SUMMARY Sugarcane, which provides 80% of global table sugar and 40% of biofuel, presents unique breeding challenges due to its highly polyploid, heterozygous, and frequently aneuploid genome. Significant progress has been made in developing genetic resources, including the recently completed reference genome of the sugarcane cultivar R570 and pan‐genomic resources from sorghum, a closely related diploid species. Biotechnological approaches including RNA interference (RNAi), overexpression of transgenes, and gene editing technologies offer promising avenues for accelerating sugarcane improvement. These methods have successfully targeted genes involved in important traits such as sucrose accumulation, lignin biosynthesis, biomass oil accumulation, and stress response. One of the main transformation methods—biolistic gene transfer or Agrobacterium ‐mediated transformation—coupled with efficient tissue culture protocols, is typically used for implementing these biotechnology approaches. Emerging technologies show promise for overcoming current limitations. The use of morphogenic genes can help address genotype constraints and improve transformation efficiency. Tissue culture‐free technologies, such as spray‐induced gene silencing, virus‐induced gene silencing, or virus‐induced gene editing, offer potential for accelerating functional genomics studies. Additionally, novel approaches including base and prime editing, orthogonal synthetic transcription factors, and synthetic directed evolution present opportunities for enhancing sugarcane traits. These advances collectively aim to improve sugarcane's efficiency as a crop for both sugar and biofuel production. This review aims to discuss the progress made in sugarcane methodologies, with a focus on RNAi and gene editing approaches, how RNAi can be used to inform functional gene targets, and future improvements and applications.

Brant, Eleanor [Agronomy Department, Plant Molecul↗

DOE OSTI2026

Development of male-sterile lines of Setaria viridis to accelerate C 4 model plant genetics

Setaria viridis is a diploid C 4 grass in the Poaceae family, notable for its rapid life cycle of 6–8 weeks from sowing to seed—much shorter than the 4–5 months required by crops such as Zea mays and Sorghum bicolor . This fast growth makes S. viridis a valuable model for C 4 crop research. Genetic crosses are essential for studying gene function, but manual crossing is labor-intensive and time-consuming. Here, to address this, we developed a male-sterile line by targeting the S. viridis ortholog of Setaria italica NO POLLEN 1 ( SiNP1 ), which encodes a glucose–methanol–choline oxidoreductase required for pollen exine formation. Using Cas9 and TREX2 -mediated genome editing, we generated SiNP1 knockouts in both the S. viridis ME034V and A10.1 backgrounds that were fully male-sterile. Backcrossing T 0 male-sterile plants to ME034V wild-type followed by selfing yielded a stable BC 1 F 2 line homozygous for a 59 bp deletion in the S. viridis NO POLLEN 1 gene, easily genotyped by PCR and maintained by heterozygous siblings. Using this line, we developed a simple and efficient crossing protocol that eliminates the need for emasculation. This method enables a single person to perform up to 100 crosses per day—compared to 15 using traditional methods—and yields 20–32 F 1 hybrid seeds per panicle with 100% genetic purity. We also quantified pollen flow and outcrossing frequencies under greenhouse conditions to develop optimal bagging strategies and prevent unintended pollination. This resource accelerates genetic research in S. viridis , enhancing its utility as a premier C 4 model for mapping and functional genomics.

C4 research↗

DOE OSTI2022

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗

DOE OSTI2020

stovertillage2019-bc1040-060

As part of the Billion Ton resource assessment projections created in 2016 (see https://www.energy.gov/sites/prod/files/2016/12/f34/2016_billion_ton_rep...), this dataset was produced and titled a "base-case" scenario. This broader dataset provided an updated assessment of the potential economic availability of biomass resources from agricultural lands reported at the farmgate under conservative assumptions. Crop residues quantified in this dataset include corn stover, cereal (wheat, oats, and barley) straws, and sorghum stubble. We have isolated corn stover in this dataset. What is the purpose of the data set? Why were the data collected?* Per request for use in subsequent research, we have isolated corn stover in 2019 from the broader base-case projections and have provided tillage classification details from this projection. Tillage classification assumptions in this scenario allow a moderate deviation from a baseline situation (using historic CTIC data on tillage type used in counties for each crop). This dataset allowed moderate flexibility of farmers to put land into another tillage type (no till, conservation till, and reduced till) where a higher net present value was calculated.

Davis, Maggie R.↗

DOE OSTI2020

CA-ResidueRetentionAssumptionsBT16-BaseCase

As part of the Billion Ton resource assessment projections created in 2016 (see https://www.energy.gov/sites/prod/files/2016/12/f34/2016_billion_ton_report_12.2.16_0.pdf, DOI: 10.2172/1435342) -henceforth "BT16", this dataset was used as an assumption to limit the availability of residues under a "base-case" scenario (BC1). Crop residues that had this assumption applied include corn stover, cereal (wheat, oats, and barley) straws, and sorghum stubble. What is the purpose of the data set? Why were the data collected? Per request for use in subsequent research, we have summarized assumptions for California only and selected years (2020, 2030, 2040) that were used in the BT16's base-case projections for agricultural residues and have provided details by tillage class that limited residue availability for harvest (dry tons of residues that must remain). Note: '10' is a high number that assures that no residue harvested could occur. Note: Tillage classification assumptions are also of importance: a low flexibility was applied, allowing a moderate deviation from a baseline situation (using historic CTIC data on tillage type used in counties for each crop). A moderate flexibility, allows farmers to put land into another tillage type (no till, conservation till, and reduced till) where a higher net present value was calculated. This dataset includes all allowable tillage types by crop, but each tillage type may not have occurred in BT16 simulations.

Davis, Maggie↗

DOE OSTI2021

yuwangcn/C4_dynamic_model

A dynamic systems model of C4 photosynthesis was developed based on the previous NADP-ME metabolic model for maize (Wang et al., 2014 ab). The NADP-ME metabolic model is an ordinary differential equation model including all individual steps in C4 photosynthetic carbon metabolism. Here, the model is extended to include posttranslational regulation and temperature response of enzyme activities, dynamic stomata conductance, and leaf energy balance. This model is written in Matlab (R2019a) Steady-state and dynamic gas exchange data for maize (B73), sugarcane (CP88-1762) and sorghum (Tx430) were measured in a greenhouse in Urbana, IL from July 25, 2019 through August 8, 2019. Data include: CO2 response curves Light response curves Photosynthetic induction curves measured in the transition from darkness to high light (1800 μmol m-2 s-1), data logged every 1 min. Photosynthetic induction in the transition from darkness to high light (1800 μmol m-2 s-1) to determine the kinetics of rubisco activation in these C4 crops (τ_Rubisco), data logged every 10 s. Gas exchange under fluctuating light. After dark adaptation, the leaves undergo three light change steps, light intensity was set as 1800 µmol m-2 s-1, 200 µmol m-2 s-1 and 1800 µmol m-2 s-1 for each 1800 s step.

Wang, Yu↗

DOE OSTI2024

raogroupuiuc/yl_variantcalling

NGS analysis for mutation analysis in Yarrowia lipolytica evolved strains. Yarrowia lipolytica, an oleaginous yeast, shows promise for industrial fermentation due to its robust acetyl-CoA flux and well-developed genetic engineering tools. However, its lack of an active xylose metabolism restricts the conversion of cellulosic sugars to valuable products. To address this, metabolic engineering, and adaptive laboratory evolution (ALE) were applied to the Y. lipolytica PO1f strain, resulting in an efficient xylose-assimilating strain (XEV). Whole-genome sequencing (WGS) of the XEV followed by reverse engineering revealed that the amplification of the heterologous oxidoreductase pathway and a mutation in the GTPase-activating protein gene (YALI0B12100g) might be the primary reasons for improved xylose assimilation in the XEV strain. When a sorghum hydrolysate was used, the XEV strain showed superior xylose consumption and lipid production compared to its parental strain (X123). This study advances our understanding of xylose metabolism in Y. lipolytica and proposes effective metabolic engineering strategies for optimizing lignocellulosic hydrolysates.

Deewan, Anshu↗

DOE OSTI2025

cabbi-bio/sorghum-sugarcane-RBCS-RAF1-2024

This repository includes data sets and R scripts that were used to perform analysis and produce figures for the following publication: Salesse-Smith, C. E. et al. "Adapting C4 photosynthesis to atmospheric change and increasing productivity by elevating Rubisco content in sorghum and sugarcane." Proceedings of the National Academy of Sciences 122, e2419943122 (2025) doi:10.1073/pnas.2419943122.

Salesse-Smith, Coralie↗