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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Genomic insights into the origin, domestication and diversification of Brassica juncea

Despite early domestication around 3000 BC, the evolutionary history of the ancient allotetraploid species Brassica juncea (L.) Czern & Coss remains uncertain. Here, we report a chromosome-scale de novo assembly of a yellow-seeded B. juncea genome by integrating long-read and short-read sequencing, optical mapping and Hi-C technologies. Nuclear and organelle phylogenies of 480 accessions worldwide supported that B. juncea is most likely a single origin in West Asia, 8,000–14,000 years ago, via natural interspecific hybridization. Subsequently, new crop types evolved through spontaneous gene mutations and introgressions along three independent routes of eastward expansion. Selective sweeps, genome-wide trait associations and tissue-specific RNA-sequencing analysis shed light on the domestication history of flowering time and seed weight, and on human selection for morphological diversification in this versatile species. Our data provide a comprehensive insight into the origin and domestication and a foundation for genomics-based breeding of B. juncea.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genomes of multicellular algal sisters to land plants illuminate signaling network evolution

Zygnematophyceae are the algal sisters of land plants. Here we sequenced four genomes of filamentous Zygnematophyceae, including chromosome-scale assemblies for three strains of Zygnema circumcarinatum . We inferred traits in the ancestor of Zygnematophyceae and land plants that might have ushered in the conquest of land by plants: expanded genes for signaling cascades, environmental response, and multicellular growth. Zygnematophyceae and land plants share all the major enzymes for cell wall synthesis and remodifications, and gene gains shaped this toolkit. Co-expression network analyses uncover gene cohorts that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

GriddingMachine, a database and software for Earth system modeling at global and regional scales

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

58 GEOSCIENCES↗
DOE OSTI2023

Benefits of symbiotic ectomycorrhizal fungi to plant water relations depend on plant genotype in pinyon pine

Rhizosphere microbes, such as root-associated fungi, can improve plant access to soil resources, affecting plant health, productivity, and stress tolerance. While mycorrhizal associations are ubiquitous, plant–microbe interactions can be species specific. Here we show that the specificity of the effects of microbial symbionts on plant function can go beyond species level: colonization of roots by ectomycorrhizal fungi (EMF) of the genus Geopora has opposite effects on water uptake, and stomatal control of desiccation in drought tolerant and intolerant genotypes of pinyon pine (Pinus edulis Engelm.). These results demonstrate, for the first time, that microorganisms can have significant and opposite effects on important plant functional traits like stomatal control of desiccation that are associated with differential mortality and growth in nature. They also highlight that appropriate pairing of plant genotypes and microbial associates will be important for mitigating climate change impacts on vegetation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗
DOE OSTI2025

Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.

Computational biology and bioinformatics↗
DOE OSTI2026

Flash flourishing of Northern Hemisphere vegetation and its drivers

Rapid surges in vegetation growth—defined by thresholds in growth rate and duration—are critical yet understudied indicators of ecosystem responses to environmental change. Here, we investigate spatiotemporal patterns of such abrupt, short-lived flash flourishing events across the northern extratropical latitudes (NEL) from 2003 to 2022. We find more frequent occurrence of flash flourishing events at high latitudes (≥45° N), where their incidence is 1.6 times higher than at mid-latitudes. Moreover, there is an increasing tendency in frequency, duration, and intensity of flash flourishing events over the past two decades, alongside consistent rises in vegetation indices across onset, post-onset, and entire phases. Model simulations attribute these multiyear increases primarily to elevated atmospheric CO 2 , while temperature and radiation predominantly control phase-specific variability, with onset traits strongly predicting subsequent phenological responses. Together, these findings identify the patterns and drivers of NEL flash flourishing and highlight their large-scale impacts on ecosystem dynamics, offering critical insights for model improvement and the assessment of ecological shifts.

Kong, Xiangxu [Nanjing University of Information S↗
DOE OSTI2021

Pests, diseases, and aridity have shaped the genome of Corymbia citriodora

Corymbia citriodora is a member of the predominantly Southern Hemisphere Myrtaceae family, which includes the eucalypts (Eucalyptus, Corymbia and Angophora; ~800 species). Corymbia is grown for timber, pulp and paper, and essential oils in Australia, South Africa, Asia, and Brazil, maintaining a high-growth rate under marginal conditions due to drought, poor-quality soil, and biotic stresses. To dissect the genetic basis of these desirable traits, we sequenced and assembled the 408 Mb genome of Corymbia citriodora, anchored into eleven chromosomes. Comparative analysis with Eucalyptus grandis reveals high synteny, although the two diverged approximately 60 million years ago and have different genome sizes (408 vs 641 Mb), with few large intra-chromosomal rearrangements. C. citriodora shares an ancient whole-genome duplication event with E. grandis but has undergone tandem gene family expansions related to terpene biosynthesis, innate pathogen resistance, and leaf wax formation, enabling their successful adaptation to biotic/abiotic stresses and arid conditions of the Australian continent.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deep ocean metagenomes provide insight into the metabolic architecture of bathypelagic microbial communities

The deep sea, the largest ocean’s compartment, drives planetary-scale biogeochemical cycling. Yet, the functional exploration of its microbial communities lags far behind other environments. Here we analyze 58 metagenomes from tropical and subtropical deep oceans to generate the Malaspina Gene Database. Free-living or particle-attached lifestyles drive functional differences in bathypelagic prokaryotic communities, regardless of their biogeography. Ammonia and CO oxidation pathways are enriched in the free-living microbial communities and dissimilatory nitrate reduction to ammonium and H 2 oxidation pathways in the particle-attached, while the Calvin Benson-Bassham cycle is the most prevalent inorganic carbon fixation pathway in both size fractions. Reconstruction of the Malaspina Deep Metagenome-Assembled Genomes reveals unique non-cyanobacterial diazotrophic bacteria and chemolithoautotrophic prokaryotes. The widespread potential to grow both autotrophically and heterotrophically suggests that mixotrophy is an ecologically relevant trait in the deep ocean. These results expand our understanding of the functional microbial structure and metabolic capabilities of the largest Earth aquatic ecosystem.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural basis underlying the synergism of NADase and SLO during group A Streptococcus infection

Group A Streptococcus (GAS) is a strict human pathogen possessing a unique pathogenic trait that utilizes the cooperative activity of NAD + -glycohydrolase (NADase) and Streptolysin O (SLO) to enhance its virulence. How NADase interacts with SLO to synergistically promote GAS cytotoxicity and intracellular survival is a long-standing question. Here, the structure and dynamic nature of the NADase/SLO complex are elucidated by X-ray crystallography and small-angle scattering, illustrating atomic details of the complex interface and functionally relevant conformations. Structure-guided studies reveal a salt-bridge interaction between NADase and SLO is important to cytotoxicity and resistance to phagocytic killing during GAS infection. Furthermore, the biological significance of the NADase/SLO complex in GAS virulence is demonstrated in a murine infection model. Overall, this work delivers the structure-functional relationship of the NADase/SLO complex and pinpoints the key interacting residues that are central to the coordinated actions of NADase and SLO in the pathogenesis of GAS infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Split selectable marker systems utilizing inteins facilitate gene stacking in plants

The ability to stack multiple genes in plants is of great importance in the development of crops with desirable traits but can be challenging due to limited selectable marker options. Here we establish split selectable marker systems using protein splicing elements called “inteins” for Agrobacterium-mediated co-transformation in plants. First, we show that such a split selectable marker system can be used effectively in plants to reconstitute a visible marker, RUBY, from two non-functional fragments through tobacco leaf infiltration. Next, to determine the general applicability of our split selectable marker systems, we demonstrate the utility of these systems in the model plants Arabidopsis and poplar by successfully stacking two reporters eYGFPuv and RUBY, using split Kanamycin or Hygromycin resistance markers. In conclusion, this method enables robust plant co-transformation, providing a valuable tool for the simultaneous insertion of multiple genes into both herbaceous and woody plants efficiently.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structural and biophysical insights into targeting of claudin-4 by a synthetic antibody fragment

Claudins are a 27-member family of ~25 kDa membrane proteins that integrate into tight junctions to form molecular barriers at the paracellular spaces between endothelial and epithelial cells. As the backbone of tight junction structure and function, claudins are attractive targets for modulating tissue permeability to deliver drugs or treat disease. However, structures of claudins are limited due to their small sizes and physicochemical properties—these traits also make therapy development a challenge. Here we report the development of a synthetic antibody fragment (sFab) that binds human claudin-4 and the determination of a high-resolution structure of it bound to claudin-4/enterotoxin complexes using cryogenic electron microscopy. Structural and biophysical results reveal this sFabs mechanism of select binding to human claudin-4 over other homologous claudins and establish the ability of sFabs to bind hard-to-target claudins to probe tight junction structure and function. The findings provide a framework for tight junction modulation by sFabs for tissue-selective therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Grassland carbon-water cycling is minimally impacted by a photovoltaic array

Agrivoltaic systems, whereby photovoltaic arrays are co-located with crop or forage production, can alleviate the tension between expanding solar development and loss of agricultural land. However, the ecological ramifications of these arrays are poorly known. We used field measurements and a plant hydraulic model to quantify carbon-water cycling in a semi-arid C 3 perennial grassland growing beneath a single-axis tracking solar array in Colorado, USA. Although the agrivoltaic array reduced light availability by 38%, net photosynthesis and aboveground net primary productivity were reduced by only 6–7% while evapotranspiration decreased by 1.3%. The minimal changes in carbon-water cycling occurred largely because plant photosynthetic traits underneath the panels changed to take advantage of the dynamic shading environment. Our results indicate that agrivoltaic systems can serve as a scalable way to expand solar energy production while maintaining ecosystem function in managed grasslands, especially in climates where water is more limiting than light.

14 SOLAR ENERGY↗
DOE OSTI2025

Next-generation electronics by co-design with chalcogenide materials

As Moore’s law approaches its limits, chalcogenides offer a promising route to next-generation computing and sensing, thanks to their topological, magnetoelectric, excitonic, and spintronic properties. Yet the same traits that make them appealing, e.g., exotic properties at monolayer thickness, clean van der Waals interfaces, and strong many-body effects, also heighten sensitivity to fabrication, hindering translation into scalable devices. Progress is further constrained by fragmented knowledge across synthesis, processing, and integration, and by the lack of systematic links between fabrication parameters and performance metrics. This Perspective examines key obstacles in controlling chalcogenide heterostructures and stresses the need for an integrated co-design framework, uniting materials growth, processing, and device architecture to accelerate practical technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enhanced microbial production of protocatechuate from engineered sorghum using an integrated feedstock-to-product conversion technology

Building a stronger bioeconomy requires production capabilities that are largely generated through microbial genetic engineering. Plant feedstocks can additionally be genetically engineered to generate desirable feedstock traits and provide precursors for direct microbial conversion into desired products. The oleaginous yeast Rhodosporidium toruloides is a promising organism for this type of conversion as it can grow on a wide range of deconstructed biomass and consume a variety of carbon sources. Here, we leveraged R. toruloides native p-coumaric acid consumption pathway to accumulate protocatechuate (PCA) from 4-hydroxybenzoate (4HBA) released from a sorghum feedstock line genetically engineered to overproduce 4HBA. We did so by generating and evaluating an R. toruloides strain that accumulates PCA, RSΔ12623. We then show that at two scales a cholinium lysinate pretreatment with enzymatic saccharification successfully extracts 95% of the 4HBA from the engineered sorghum biomass while producing deconstructed lignin that can be more efficiently depolymerized in a subsequent thermochemical reaction. We also demonstrate that strain RSΔ12623 can convert more than 95% of 4HBA to PCA while consuming >95% of the glucose and >80% of the xylose present in sorghum hydrolysates. Finally, to evaluate the scalability of such fermentations, we conducted the conversion of 4HBA to PCA in a 2 L bioreactor under controlled conditions. Importantly, this work demonstrates the potential of purposefully producing aromatic precursors in planta that can be liberated during biomass deconstruction for direct microbial conversion to desirable bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Variable lignin structure revealed in Populus leaves

NMR analysis of Populus leaves revealed lignin traits such as condensed syringyl units and both erythron / threo conformations of the β-O-4 linkage. Lignin structure was also well correlated with certain metabolites such as salicin derivatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗