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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Root and xylem anatomy varies with root length, root order, soil depth and environment in intermediate wheatgrass (Kernza®) and alfalfa

Abstract Background and Aims Deep roots (i.e. >1 m depth) are important for crops to access water when the topsoil is dry. Root anatomy and hydraulic conductance play important roles in the uptake of soil water, particularly water located deep in the soil. We investigated whether root and xylem anatomy vary as a function of root type, order and length, or with soil depth in roots of two deep-rooted perennial crops: intermediate wheatgrass [Thinopyrum intermedium (Kernza®)] and alfalfa (Medicago sativa). We linked the expression of these anatomical traits to the plants’ capacity to take up water from deep soil layers. Methods Using laser ablation tomography, we compared the roots of the two crops for cortical area, number and size of metaxylem vessels, and their estimated root axial hydraulic conductance (ERAHCe). The deepest roots investigated were located at soil depths of 2.25 and at 3.5 m in the field and in rhizoboxes, respectively. Anatomical differences were characterized along 1-m-long individual roots, among root types and orders, as well as between environmental conditions. Key Results For both crops, a decrease in the number and diameter, or both, of metaxylem vessels along individual root segments and with soil depth in the field resulted in a decrease in ERAHCe. Alfalfa, with a greater number of metaxylem vessels per root throughout the soil profile and, on average, a 4-fold greater ERAHCe, took up more water from the deep soil layers than intermediate wheatgrass. Root anatomical traits were significantly different across root types, classes and growth conditions. Conclusions Root anatomical traits are important tools for the selection of crops with enhanced exploitation of deep soil water. The development and breeding of perennial crops for improved subsoil exploitation will be aided by greater understanding of root phenotypes linked to deep root growth and activity.

Plant Sciences↗
DOE OSTI2023

Genomic prediction of switchgrass winter survivorship across diverse lowland populations

Abstract In the North-Central United States, lowland ecotype switchgrass can increase yield by up to 50% compared with locally adapted but early flowering cultivars. However, lowland ecotypes are not winter tolerant. The mechanism for winter damage is unknown but previously has been associated with late flowering time. This study investigated heading date (measured for two years) and winter survivorship (measured for three years) in a multi-generation population generated from two winter-hardy lowland individuals and diverse southern lowland populations. Sequencing data (311,776 markers) from 1,306 individuals were used to evaluate genome-wide trait prediction through cross-validation and progeny prediction (n = 52). Genetic variance for heading date and winter survivorship was additive with high narrow-sense heritability (0.64 and 0.71, respectively) and reliability (0.68 and 0.76, respectively). The initial negative correlation between winter survivorship and heading date degraded across generations (F1 r = −0.43, pseudo-F2 r = −0.28, pseudo-F2 progeny r = −0.15). Within-family predictive ability was moderately high for heading date and winter survivorship (0.53 and 0.52, respectively). A multi-trait model did not improve predictive ability for either trait. Progeny predictive ability was 0.71 for winter survivorship and 0.53 for heading date. These results suggest that lowland ecotype populations can obtain sufficient survival rates in the northern United States with two or three cycles of effective selection. Despite accurate genomic prediction, naturally occurring winter mortality successfully isolated winter tolerant genotypes and appears to be an efficient method to develop high-yielding, cold-tolerant switchgrass cultivars.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Sawfly Genomes Reveal Evolutionary Acquisitions That Fostered the Mega-Radiation of Parasitoid and Eusocial Hymenoptera

The tremendous diversity of Hymenoptera is commonly attributed to the evolution of parasitoidism in the last common ancestor of parasitoid sawflies (Orussidae) and wasp-waisted Hymenoptera (Apocrita). However, Apocrita and Orussidae differ dramatically in their species richness, indicating that the diversification of Apocrita was promoted by additional traits. These traits have remained elusive due to a paucity of sawfly genome sequences, in particular those of parasitoid sawflies. Here, we present comparative analyses of draft genomes of the primarily phytophagous sawfly Athalia rosae and the parasitoid sawfly Orussus abietinus. Our analyses revealed that the ancestral hymenopteran genome exhibited traits that were previously considered unique to eusocial Apocrita (e.g., low transposable element content and activity) and a wider gene repertoire than previously thought (e.g., genes for CO 2 detection). Moreover, we discovered that Apocrita evolved a significantly larger array of odorant receptors than sawflies, which could be relevant to the remarkable diversification of Apocrita by enabling efficient detection and reliable identification of hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Repeated horizontal gene transfer of GAL actose metabolism genes violates Dollo’s law of irreversible loss

Dollo’s law posits that evolutionary losses are irreversible, thereby narrowing the potential paths of evolutionary change. While phenotypic reversals to ancestral states have been observed, little is known about their underlying genetic causes. The genomes of budding yeasts have been shaped by extensive reductive evolution, such as reduced genome sizes and the losses of metabolic capabilities. However, the extent and mechanisms of trait reacquisition after gene loss in yeasts have not been thoroughly studied. Here, through phylogenomic analyses, we reconstructed the evolutionary history of the yeast galactose utilization pathway and observed widespread and repeated losses of the ability to utilize galactose, which occurred concurrently with the losses of GALactose (GAL) utilization genes. Unexpectedly, we detected multiple galactose-utilizing lineages that were deeply embedded within clades that underwent ancient losses of galactose utilization. We show that at least two, and possibly three, lineages reacquired the GAL pathway via yeast-to-yeast horizontal gene transfer. Our results show how trait reacquisition can occur tens of millions of years after an initial loss via horizontal gene transfer from distant relatives. Furthermore, these findings demonstrate that the losses of complex traits and even whole pathways are not always evolutionary dead-ends, highlighting how reversals to ancestral states can occur.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy

The photosynthetic capacity or the CO 2 -saturated photosynthetic rate (Vmax), chlorophyll, and nitrogen are closely linked leaf traits that determine C 4 crop photosynthesis and yield. Accurate, timely, rapid, and non-destructive approaches to predict leaf photosynthetic traits from hyperspectral reflectance are urgently needed for high-throughput crop monitoring to ensure food and bioenergy security. Therefore, this study thoroughly evaluated the state-of-the-art physically based radiative transfer models (RTMs), data-driven partial least squares regression (PLSR), and generalized PLSR (gPLSR) models to estimate leaf traits from leaf-clip hyperspectral reflectance, which was collected from maize (Zea mays L.) bioenergy plots with diverse genotypes, growth stages, treatments with nitrogen fertilizers, and ozone stresses in three growing seasons. The results show that leaf RTMs considering bidirectional effects can give accurate estimates of chlorophyll content (Pearson correlation r=0.95), while gPLSR enabled retrieval of leaf nitrogen concentration (r=0.85). Using PLSR with field measurements for training, the cross-validation indicates that V max can be well predicted from spectra (r=0.81). Here, the integration of chlorophyll content (strongly related to visible spectra) and nitrogen concentration (linked to shortwave infrared signals) can provide better predictions of V max (r=0.71) than only using either chlorophyll or nitrogen individually. This study highlights that leaf chlorophyll content and nitrogen concentration have key and unique contributions to V max prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Detection of the Metabolic Response to Drought Stress Using Hyperspectral Reflectance

Drought is the most important limitation on crop yield. Understanding and detecting drought stress in crops is vital for improving water use efficiency through effective breeding and management. Leaf reflectance spectroscopy offers a rapid, non-destructive alternative to traditional techniques for measuring plant traits involved in a drought response. We measured drought stress in six glasshouse-grown agronomic species using physiological, biochemical and spectral data. In contrast to physiological traits, leaf metabolite concentrations revealed drought stress before it was visible to the naked eye. We used full-spectrum leaf reflectance data to predict metabolite concentrations using partial least-squares regression, with validation R2 values of 0.49 to 0.87. We show for the first time that spectroscopy may be used for the quantitative estimation of proline and abscisic acid, demonstrating the first use of hyperspectral data to detect a phytohormone. We used linear discriminant analysis and partial least squares discriminant analysis to differentiate between droughted and watered plants based on measured traits (accuracy: 71%) and raw spectral data (66%). Finally, we validated our glasshouse-developed models in an independent field trial. We demonstrate that spectroscopy can detect drought stress via underlying biochemical changes, before visual differences occur, representing a powerful advance for measuring limitations on yield.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning

Abstract Artificial intelligence and machine learning (AI/ML) can be used to automatically analyze large image datasets. One valuable application of this approach is estimation of plant trait data contained within images. Here we review 39 papers that describe the development and/or application of such models for estimation of stomatal traits from epidermal micrographs. In doing so, we hope to provide plant biologists with a foundational understanding of AI/ML and summarize the current capabilities and limitations of published tools. While most models show human-level performance for stomatal density (SD) quantification at superhuman speed, they are often likely to be limited in how broadly they can be applied across phenotypic diversity associated with genetic, environmental, or developmental variation. Other models can make predictions across greater phenotypic diversity and/or additional stomatal/epidermal traits, but require significantly greater time investment to generate ground-truth data. We discuss the challenges and opportunities presented by AI/ML-enabled computer vision analysis, and make recommendations for future work to advance accelerated stomatal phenotyping.

Plant Sciences↗
DOE OSTI2025

Decoding crops one cell at a time: from cell atlases to single-cell genetics

Understanding the mechanisms underlying key agricultural traits remains a central challenge in crop research, but recent advances in technologies are providing powerful tools to address this issue. Among these, single-cell and spatial transcriptomics have revealed tissue heterogeneity and spatial organization, offering unique insights into cellular gene expression dynamics and the coordinated activity of multiple cell types. These approaches help uncover how specific cell types contribute to agricultural traits and refine candidate loci lists through integration with trait-associated loci. Additionally, single-cell and spatial transcriptomics have the potential to serve as cell-level readout platforms integrating cellular perturbations, enabling high-throughput discovery of causal relationships between genotype and gene expression at the cellular level in plants. Successful implementation will accelerate the identification of key genetic variants for crop improvement. Furthermore we review lessons learned from application of single-cell screening in mammalian cells, highlight major technical and biological barriers to its use in plants, and outline potential strategies to overcome these challenges. Together, the widespread application and integration of single-cell and spatial transcriptomics with other technologies enable not only the descriptive cataloging of cell states but also the causal interrogation of sequence functions and regulatory networks at cell type resolution, ultimately advancing gene function studies and accelerating crop improvement.

Cellular heterogeneity↗
DOE OSTI2023

Codon Optimization Improves the Prediction of Xylose Metabolism from Gene Content in Budding Yeasts

Xylose is the second most abundant monomeric sugar in plant biomass. Consequently, xylose catabolism is an ecologically important trait for saprotrophic organisms, as well as a fundamentally important trait for industries that hope to convert plant mass to renewable fuels and other bioproducts using microbial metabolism. Although common across fungi, xylose catabolism is rare within Saccharomycotina, the subphylum that contains most industrially relevant fermentative yeast species. The genomes of several yeasts unable to consume xylose have been previously reported to contain the full set of genes in the XYL pathway, suggesting the absence of a gene–trait correlation for xylose metabolism. Here, we measured growth on xylose and systematically identified XYL pathway orthologs across the genomes of 332 budding yeast species. Although the XYL pathway coevolved with xylose metabolism, we found that pathway presence only predicted xylose catabolism about half of the time, demonstrating that a complete XYL pathway is necessary, but not sufficient, for xylose catabolism. We also found that XYL1 copy number was positively correlated, after phylogenetic correction, with xylose utilization. We then quantified codon usage bias of XYL genes and found that XYL3 codon optimization was significantly higher, after phylogenetic correction, in species able to consume xylose. Finally, we showed that codon optimization of XYL2 was positively correlated, after phylogenetic correction, with growth rates in xylose medium. We conclude that gene content alone is a weak predictor of xylose metabolism and that using codon optimization enhances the prediction of xylose metabolism from yeast genome sequence data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Stomata in-sight: Integrating live confocal microscopy with leaf gas exchange and environmental control

Stomatal anatomy (aperture area, length, and width) influences leaf-level physiology traits including conductance to water vapor. Stomatal anatomy can be visualized in situ by microscopy, but the difficulty of regulating the atmospheric environment of a microscope stage means that the conditions under which imaging is done are rarely physiologically relevant. Alternatively, leaf gas exchange instruments that measure gas fluxes reflect stomatal anatomical characteristics in aggregate, but the relative strengths of anatomical traits to control water use (e.g. size vs density) cannot be firmly established. To reconcile the microscopic stomatal characteristics with leaf-level gas exchange, we describe a tool that combines laser scanning confocal microscopy, gas exchange instruments, and machine-learning image analysis to simultaneously observe anatomical characteristics of many (>40) stomata alongside leaf-level traits like photosynthesis, transpiration, and stomatal conductance. We demonstrate how the tool has the resolution capable of quantifying aperture sizes and variability in maize (Zea mays) leaves under 5 steady-state light/pCO 2 treatments while tightly controlling other environmental variables like relative humidity and temperature. A model used to calculate stomatal conductance from measured apertures and stomatal density accurately matched stomatal conductance measured by gas exchange. This technical advancement will provide insight on how stomatal anatomy and function trade off to influence stomatal conductance and leaf-level water use efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

CO2 refixation is higher in leaves of woody species with high mesophyll and stomatal resistances to CO2 diffusion

Abstract The percentage of respiratory and photorespiratory CO2 refixed in leaves (Pr) represents part of the CO2 used in photosynthesis. The importance of Pr as well as differences between species and functional types are still not well investigated. In this study, we examine how Pr differs between six temperate and boreal woody species: Betula pendula, Quercus robur, Larix decidua, Pinus sylvestris, Picea abies and Vaccinium vitis-idaea. The study covers early and late successional species, deciduous broadleaves, deciduous conifers, evergreen conifers and evergreen broadleaves. We investigated whether some species or functional types had higher refixation percentages than others, whether leaf traits could predict higher Pr and whether these traits and their impact on Pr changed during growing seasons. Photosynthesis CO2 response (A/Ci)-curves, measured early, mid and late season, were used to estimate and compare Pr, mesophyll resistance (rm) and stomatal resistance (rs) to CO2 diffusion. Additionally, light images and transmission electron microscope images were used to approximate the fraction of intercellular airspace and cell wall thickness. We found that evergreens, especially late successional species, refixed a significantly higher amount of CO2 than the other species throughout the entire growing season. In addition, rm, rs and leaf mass per area, traits that typically are higher in evergreen species, were also significantly, positively correlated with Pr. We suggest that this is due to higher rm decreasing diffusion of (photo) respiratory CO2 out of the leaf. Cell wall thickness had a positive effect on Pr and rm, while the fraction of intercellular airspace had no effect. Both were significantly different between evergreen conifers and other types. Our findings suggest that species with a higher rm use a greater fraction of mitochondria-derived CO2, especially when stomatal conductance is low. This should be taken into account when modeling the overall CO2 fertilization effect for terrestrial ecosystems dominated by high rm species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stability of tropical forest tree carbon-water relations in a rainfall exclusion treatment through shifts in effective water uptake depth

Increasing severity and frequency of drought is predicted for large portions of the terrestrial biosphere, with major impacts already documented in wet tropical forests. Using a 4-year rainfall exclusion experiment in the Daintree Rainforest in northeast Australia, we examined canopy tree responses to reduced precipitation and soil water availability by quantifying seasonal changes in plant hydraulic and carbon traits for 11 tree species between control and drought treatments. Even with reduced soil volumetric water content in the upper 1 m of soil in the drought treatment, we found no significant difference between treatments for predawn and midday leaf water potential, photosynthesis, stomatal conductance, foliar stable carbon isotope composition, leaf mass per area, turgor loss point, xylem vessel anatomy, or leaf and stem nonstructural carbohydrates. While empirical measurements of aboveground traits revealed homeostatic maintenance of plant water status and traits in response to reduced soil moisture, modeled belowground dynamics revealed that trees in the drought treatment shifted the depth from which water was acquired to deeper soil layers. Finally, these findings reveal that belowground acclimation of tree water uptake depth may buffer tropical rainforests from more severe droughts that may arise in future with climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tropical root responses to global changes: A synthesis

Tropical ecosystems face escalating global change. These shifts can disrupt tropical forests' carbon (C) balance and impact root dynamics. Since roots perform essential functions such as resource acquisition and tissue protection, root responses can inform about the strategies and vulnerabilities of ecosystems facing present and future global changes. However, root trait dynamics are poorly understood, especially in tropical ecosystems. We analyzed existing research on tropical root responses to key global change drivers: warming, drought, flooding, cyclones, nitrogen (N) deposition, elevated (e) CO 2 , and fires. Based on tree species- and community-level literature, we obtained 266 root trait observations from 93 studies across 24 tropical countries. We found differences in the proportion of root responsiveness to global change among different global change drivers but not among root categories. In particular, we observed that tropical root systems responded to warming and eCO 2 by increasing root biomass in species-scale studies. Drought increased the root: shoot ratio with no change in root biomass, indicating a decline in aboveground biomass. Despite N deposition being the most studied global change driver, it had some of the most variable effects on root characteristics, with few predictable responses. Episodic disturbances such as cyclones, fires, and flooding consistently resulted in a change in root trait expressions, with cyclones and fires increasing root production, potentially due to shifts in plant community and nutrient inputs, while flooding changed plant regulatory metabolisms due to low oxygen conditions. The data available to date clearly show that tropical forest root characteristics and dynamics are responding to global change, although in ways that are not always predictable. This synthesis indicates the need for replicated studies across root characteristics at species and community scales under different global change factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Delimiting the cryptic diversity and host preferences of Sycophila parasitoid wasps associated with oak galls using phylogenomic data

Abstract Cryptic species diversity is a major challenge regarding the species‐rich community of parasitoids attacking oak gall wasps due to a high degree of sexual dimorphism, morphological plasticity, small size and poorly known biology. As such, we know very little about the number of species present, nor the evolutionary forces responsible for generating this diversity. One hypothesis is that trait diversity in the gall wasps, including the morphology of the galls they induce, has evolved in response to selection imposed by the parasitoid community, with reciprocal selection driving diversification of the parasitoids. Using a rare, continental‐scale data set of Sycophila parasitoid wasps reared from 44 species of cynipid galls from 18 species of oak across the USA, we combined mitochondrial DNA barcodes, ultraconserved elements (UCEs), morphological and natural history data to delimit putative species. Using these results, we generate the first large‐scale assessment of ecological specialization and host association in this species‐rich group, with implications for evolutionary ecology and biocontrol. We find most Sycophila target specific subsets of available cynipid host galls with similar morphologies, and generally attack larger galls. Our results suggest that parasitoid wasps such as Sycophila have adaptations allowing them to exploit particular host trait combinations, while hosts with contrasting traits are resistant to attack. These findings support the tritrophic niche concept for the structuring of plant–herbivore–parasitoid communities.

Zhang, Yuanmeng M.↗
DOE OSTI2022

Phosphorus limitation of early growth differs between nitrogen‐fixing and nonfixing dry tropical forest tree species

Summary Tropical forests are often characterized by low soil phosphorus (P) availability, suggesting that P limits plant performance. However, how seedlings from different functional types respond to soil P availability is poorly known but important for understanding and modeling forest dynamics under changing environmental conditions. We grew four nitrogen (N)‐fixing Fabaceae and seven diverse non‐N‐fixing tropical dry forest tree species in a shade house under three P fertilization treatments and evaluated carbon (C) allocation responses, P demand, P‐use, investment in P acquisition traits, and correlations among P acquisition traits. Nitrogen fixers grew larger with increasing P addition in contrast to non‐N fixers, which showed fewer responses in C allocation and P use. Foliar P increased with P addition for both functional types, while P acquisition strategies did not vary among treatments but differed between functional types, with N fixers showing higher root phosphatase activity (RPA) than nonfixers. Growth responses suggest that N fixers are limited by P, but nonfixers may be limited by other resources. However, regardless of limitation, P acquisition traits such as mycorrhizal colonization and RPA were nonplastic across a steep P gradient. Differential limitation among plant functional types has implications for forest succession and earth system models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Signatures of local nitrogen adaptation in the Brachypodium distachyon root microbiome

Plants associate with diverse microbiomes that impact their fitness, yet the contribution of the microbiome to plant adaptation is uncertain. As plant recruitment of its microbiome can be both highly variable and genetically determined, we hypothesized this recruitment process may be the result of adaptive evolution, and contributing to plant local adaptation. We investigated the evolution and adaptive benefit of plant–microbiome recruitment by characterizing the rhizosphere communities across a genotypic panel of Brachypodium distachyon in a common garden experiment. By linking microbial communities to their host genotype's historic environment, we identified signatures of selection on plant–microbiome recruitment. Plant–microbiome composition was significantly correlated with the host genotype's historic environment, with enrichment of microbial traits aligned to local resource conditions. For example, genotypes from low-nitrogen environments recruited communities enriched in nitrogen acquisition traits. In a complementary experiment evaluating plant nitrogen response, these same genotypes were well-adapted to low-nitrogen environments, contingent on the presence of key nitrogen-cycling microbes. These results suggest that local adaptation in plants may partially be mediated by recruitment of beneficial microbiomes. This perspective suggests that plant adaptation may be an emergent property of host–microbe interactions, where evolutionary responses favor traits that promote recruitment of locally beneficial microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗