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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗
DOE OSTI2019

Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation. We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs ( p -value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ 15 N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others. SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

09 BIOMASS FUELS↗
DOE OSTI2024

A systems genetic analysis identifies putative mechanisms and candidate genes regulating vessel traits in poplar wood

Wood is the water conducting tissue of tree stems. Like most angiosperm trees, poplar wood contains water-conducting vessel elements whose functional properties affect water transport and growth rates, as well as susceptibility to embolism and hydraulic failure during water stress and drought. Here we used a unique hybrid poplar pedigree carrying genomically characterized chromosomal insertions and deletions to undertake a systems genomics analysis of vessel traits. We assayed gene expression in wood forming tissues from clonal replicates of genotypes covering dosage quantitative trait loci with insertions and deletions, genotypes with extreme vessel trait phenotypes, and control genotypes. A gene co-expression analysis was used to assign genes to modules, which were then used in integrative analyses to identify modules associated with traits, to identify putative molecular and cellular processes associated with each module, and finally to identify candidate genes using multiple criteria including dosage responsiveness. These analyses identified known processes associated with vessel traits including stress response, abscisic acid and cell wall biosynthesis, and in addition identified previously unexplored processes including cell cycle and protein ubiquitination. We discuss our findings relative to component processes contributing to vessel trait variation including signaling, cell cycle, cell expansion, and cell differentiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Significance of lysogeny for the metabolism of Desulfovibrio spp. strains isolated from aquatic environments of Georgia

Sulphate-reducing bacteria (SRB) are ecologically important group of anaerobic micro-organisms that can reduce sulphate to form hydrogen sulphide-a toxic gas causing iron corrosion on metal surfaces. In this work, SRB strains were isolated from aquatic environments in the country of Georgia to determine their lysogenicity and the role of temperate phages in host metabolism. SRB strains were isolated in samples from the Black Sea coast of Georgia. Based on their genetic, cytological and physiological properties of bacteria, 10 Georgian isolates were assigned to the genus Desulfovibrio. Temperate bacteriophages were induced from three out of ten strains by UV-exposure. Comparison of metal (Fe and Cr) reduction and utilization of various carbon sources by the wild-type (lysogenic) bacterial strains and their UV-irradiated counterparts was done. Temperate phage in the cells of SRB could alter significant functions of bacteria and may have a contribution in the acquisition of different traits by SRB. This article pointed to a significant role for temperate bacteriophages in the metabolism and metabolic potential of host strains of SRB, which were first isolated from the aquatic environment of Georgia.

temperate phage↗
DOE OSTI2023

Automating methods for estimating metabolite volatility

The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate how volcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. With volcalc , we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. The volcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes

Despite an advanced ability to forecast ecosystem functions and climate at regional and global scales, little is known about relationships between local variations in water and carbon fluxes and large-scale phenomena. To enable data collection of local-scale ecosystem functions to support such investigations, we developed the EcoSpec system, a highly equipped remote sensing system that houses a hyperspectral radiometer (350–2500 nm) and five optical and infrared sensors in a compact tower. Its custom software controls the sequence and timing of movement of the sensors and system components and collects measurements at 12 locations around the tower. The data collected using the system was processed to remove sun-angle effects, and spectral vegetation indices computed from the data (i.e., the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), and Moisture Stress Index (MSI)) were compared with the fraction of photochemically active radiation (fPAR) and canopy temperature. The results showed that the NDVI, NDWI, and PRI were strongly correlated with fPAR; the MSI was correlated with canopy temperature at the diurnal scale. These correlations suggest that this type of near-surface remote sensing system would complement existing observatories to validate satellite remote sensing observations and link local and large-scale phenomena to improve our ability to forecast ecosystem functions and climate. The system is also relevant for precision agriculture to study crop growth, detect disease and pests, and compare traits of cultivars.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Effects of root litter traits on soil organic matter dynamics depend on decay stage and root branching order

Decaying roots contribute disproportionately to soil organic carbon (SOC) stocks in many ecosystems, yet few studies have examined the afterlife effects of root trait variability on the formation, stability and mineralization of SOC. In order to assess how root functional class (absorptive vs. transport) and mycorrhizal association (ectomycorrhizal vs. arbuscular mycorrhizal fungi) affect both formation and loss of SOC, we decayed lower-order absorptive (orders 1–2) and higher-order transport (orders 3–4) roots from six arbuscular mycorrhizal (AM) and six ectomycorrhizal (EcM) associated hardwood tree species in an isotopically distinct soil under laboratory conditions. We found that root litter effects on SOC differed significantly among root functional classes and mycorrhizal types. AM absorptive and transport roots (high in nitrogen and soluble compounds) contributed more to the formation of new mineral-associated organic carbon (MAOC), but also contributed to higher mineralization of native SOC (via priming effects). Moreover, absorptive AM roots formed MAOC gradually and rates saturated, whereas ECM roots formed MAOC more quickly, despite slower decay (via greater formation efficiency). Altogether, these findings demonstrate how different combinations of root traits might contribute to soil C balance, and that failure to account for the chemical and morphological heterogeneity of roots, as well their interactions with microbes over time, may lead to incorrect projections of SOC stocks and turnover.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Climate-Driven Legacies in Simulated Microbial Communities Alter Litter Decomposition Rates

The mechanisms underlying diversity-functioning relationships have been a consistent area of inquiry in biogeochemistry since the 1950s. Though these mechanisms remain unresolved in soil microbiomes, many approaches at varying scales have pointed to the same notion—composition matters. Confronting the methodological challenge arising from the complexity of microbiomes, this study used the model DEMENTpy, a trait-based modeling framework, to explore trait-based drivers of microbiome-dependent litter decomposition. We parameterized DEMENTpy for five sites along a climate gradient in Southern California, United States, and conducted reciprocal transplant simulations analogous to a prior empirical study. The simulations demonstrated climate-dependent legacy effects of microbial communities on plant litter decomposition across the gradient. This result is consistent with the previous empirical study across the same gradient. An analysis of community-level traits further suggests that a 3-way tradeoff among resource acquisition, stress tolerance, and yield strategies influences community assembly. Simulated litter decomposition was predictable with two community traits (indicative of two of the three strategies) plus local environment, regardless of the system state (transient vs. equilibrium). Although more empirical confirmation is still needed, community traits plus local environmental factors (e.g., environment and litter chemistry) may robustly predict litter decomposition across spatial-temporal scales. In conclusion, this study offers a potential trait-based explanation for climate-dependent community effects on litter decomposition with implications for improved understanding of whole-ecosystem functioning across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗
DOE OSTI2024

Halophytes and heavy metals: A multi‐omics approach to understand the role of gene and genome duplication in the abiotic stress tolerance of Cakile maritima

Abstract Premise The origin of diversity is a fundamental biological question. Gene duplications are one mechanism that provides raw material for the emergence of novel traits, but evolutionary outcomes depend on which genes are retained and how they become functionalized. Yet, following different duplication types (polyploidy and tandem duplication), the events driving gene retention and functionalization remain poorly understood. Here we usedCakile maritima, a species that is tolerant to salt and heavy metals and shares an ancient whole‐genome triplication with closely related salt‐sensitive mustard crops (Brassica), as a model to explore the evolution of abiotic stress tolerance following polyploidy. Methods Using a combination of ionomics, free amino acid profiling, and comparative genomics, we characterize aspects of salt stress response inC. maritimaand identify retained duplicate genes that have likely enabled adaptation to salt and mild levels of cadmium. Results Cakile maritimais tolerant to both cadmium and salt treatments through uptake of cadmium in the roots. Proline constitutes greater than 30% of the free amino acid pool inC. maritimaand likely contributes to abiotic stress tolerance. We find duplicated gene families are enriched in metabolic and transport processes and identify key transport genes that may be involved inC. maritimaabiotic stress tolerance. Conclusions These findings identify pathways and genes that could be used to enhance plant resilience and provide a putative understanding of the roles of duplication types and retention on the evolution of abiotic stress response.

Plant Sciences↗
DOE OSTI2021

Targeted DNA insertion in plants

Conventional methods of DNA sequence insertion into plants, using Agrobacterium -mediated transformation or microprojectile bombardment, result in the integration of the DNA at random sites in the genome. These plants may exhibit altered agronomic traits as a consequence of disruption or silencing of genes that serve a critical function. Also, genes of interest inserted at random sites are often not expressed at the desired level. For these reasons, targeted DNA insertion at suitable genomic sites in plants is a desirable alternative. In this paper we review approaches of targeted DNA insertion in plant genomes, discuss current technical challenges, and describe promising applications of targeted DNA insertion for crop genetic improvement.

Dong, Oliver Xiaoou↗
DOE OSTI2021

Global maximum carboxylation rate trait scaling in the Sheffield Dynamic Global Vegetation Model 1901-2012

This data package contains model output data and climate input data associated with the New Phytologist publication: Walker, A.P., Quaife, T., van Bodegom, P.M., De Kauwe, M.G., Keenan, T.F., Joiner, J., Lomas, M.R., MacBean, N., Xu, C., Yang, X., Woodward, F.I., 2017. The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production. New Phytologist 215, 1370–1386. https://doi.org/10.1111/nph.14623. This dataset contains maximum carboxylation rate at 25 ºC (Vcmax,25), Gross Primary Production (GPP), Net Biome Production (NBP), vegetation carbon, and soil carbon data from Sheffield Dynamic Global Vegetation Model (SDGVM) for multiple trait-scaling methods for scaling Vcmax,25 across Earth, and alternative instantaneous temperature scaling functions. Vcmax,25 values are mean top-leaf values taken during the growing seasons, which were defined as periods during which leaf area index (LAI) was greater than one. Vcmax,25 values were reported prior to scaling of Vcmax by water-stress or leaf-age. The attached metadata file (SDGVM_vcmax_dataset.docx) describes the methods used and explains the organization of data within the included .zip file. This metadata file is also included in PDF format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes

Abstract Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Biogeographic classification of streams using fish community– and trait–environment relationships

Abstract Aim Present a hybrid biogeographic and environmentally constrained clustering approach to classify ~853,000 stream reaches in the eastern United States. Examine the frequency of stream typologies in the landscape relative to anthropogenic stressors to identify potential stream conservation needs. Location Eastern United States. Methods Fish communities at 956 least‐disturbed sampling reaches were characterized using taxonomic and functional composition of native species. Environmental variables summarized within stream reaches included stream discharge, channel gradient, hydrologic regime, summer water temperature and boundaries of freshwater ecoregions. Multivariate regression trees were used to relate environmental variables to fish communities while simultaneously developing taxa‐ and trait‐specific biogeographic classifications. We then overlaid stream classifications with indices of anthropogenic disturbances to evaluate rarity and risk of complete loss of natural representation of stream types. Results Taxonomically based classes represented a combination of ecoregional boundaries and environmental gradients, whereas temperature gradients were most important in differentiating functional composition. An optimal taxonomy‐based classification contained 13 classes and explained 26.4% of community variation, and the optimal trait‐based classification contained 6 classes, explaining 25.2% of community variation. Overlaying class maps with an anthropogenic disturbance index revealed substantial variation in the severity of degradation among classes relative to their abundance in the landscape, especially rare classes (i.e., large rivers and cold headwater systems). Main conclusions We demonstrate the value of integrating local, regional and historical biogeographic factors with taxonomic and functional characteristics of freshwater biota to classify ecosystems based on mechanistic biota–environment relationships. This approach is important to addressing the challenge of developing stream classifications that reconcile the environmental drivers of community trait composition with the constraints of biogeographic regionality at large spatial scales. Furthermore, the spatially explicit and high‐resolution maps disseminated here can uniquely inform management decisions regarding anthropogenic threats to the biodiverse freshwaters of the eastern United States.

Troia, Matthew J.↗
DOE OSTI2020

Fungal community structure and function shifts with atmospheric nitrogen deposition

Fungal decomposition of soil organic matter depends on soil nitrogen (N) availability. This ecosystem process is being jeopardized by changes in N inputs that have resulted from a tripling of atmospheric N deposition in the last century. Soil fungi are impacted by atmospheric N deposition due to higher N availability, as soils are acidified, or as micronutrients become increasingly limiting. Fungal communities that persist with chronic N deposition may be enriched with traits that enable them to tolerate environmental stress, which may trade-off with traits enabling organic matter decomposition. We hypothesized that fungal communities would respond to N deposition by shifting community composition and functional gene abundances toward those that tolerate stress but are weak decomposers. We sampled soils at seven eastern US hardwood forests where ambient N deposition varied from 3.2 to 12.6 kg N ha -1 year -1 , five of which also have experimental plots where atmospheric N deposition was simulated through fertilizer application treatments (25–50 kg N ha -1 year -1 ). Fungal community and functional responses to fertilizer varied across the ambient N deposition gradient. Fungal biomass and richness increased with simulated N deposition at sites with low ambient deposition and decreased at sites with high ambient deposition. Fungal functional genes involved in hydrolysis of organic matter increased with ambient N deposition while genes involved in oxidation of organic matter decreased. One of four genes involved in generalized abiotic stress tolerance increased with ambient N deposition. In summary, we found that the divergent response to simulated N deposition depended on ambient N deposition levels. Fungal biomass, richness, and oxidative enzyme potential were reduced by N deposition where ambient N deposition was high suggesting fungal communities were pushed beyond an environmental stress threshold. Fungal community structure and function responses to N enrichment depended on ambient N deposition at a regional scale.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genome‐wide quantitative trait loci detection for biofuel traits in switchgrass ( Panicum virgatum L.)

Abstract Switchgrass ( Panicum virgatum L.) has been identified as a potential feedstock for cellulosic ethanol production in United States for its high biomass yield and adaptation to marginal lands. Composition of the cell wall plays an important role in bioethanol conversion. A total of 209 pseudo‐F 1 testcross progenies obtained from a biparental cross, AP13 × VS16, were grown at three locations from 2008 to 2011. Near‐infrared spectroscopy was used to estimate cell wall composition from biomass harvested at maturity. A linkage map of the pseudo‐F 1 testcross was constructed with 8,757 SNPs developed by genotyping‐by‐sequencing. Quantitative trait loci (QTL) analysis was performed on eight lignocellulosic traits, namely, klason lignin, sugar, glucose, xylose, hexose, ethanol, hexosoic ethanol, and cell wall ethanol conversion percentage. A total of 327 QTL were recorded for the eight lignocellulosic traits. We have identified 111 major regions in the switchgrass genome that underlie these lignocellulosic traits. Scanning of the genome sequence for genes flanking the QTL peaks, we identified 45 important genes that are involved in lignin biosynthesis, carbohydrate and sugar metabolism, and other biological and cellular functions. Identification of valuable genes associated with QTL along with pleotropic effects of the significant number of QTL suggests that simultaneous selection and genetic improvement of these traits are possible using marker‐assisted selection.

Ali, Shahjahan↗
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↗