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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The Genetics of Biofuel Traits in Panicum Grasses: Developing a Model System with Diploid Panicum Hallii

Our DOE funded project focused on characterizing natural variation in C4 perennial grasses including switchgrass (Panicum virgatum) and Hall’s panicgrass (Panicum hallii). The main theme of our project was to better understand traits linked with plant performance and that impact the utility of plant biomass as a biofuel feedstock. In addition, our project developed tools and resources for studying genetic variation in Panicum hallii. Our project successfully screened both Panicum virgatum and Panicum hallii diverse natural collections for a host of phenotypes, developed genetic mapping populations for both species, completed genetic mapping for biofuel related traits, and helped in the development of genomic resources of Panicum hallii. Together, these studies have improved our understanding of the role of genetic and environmental factors in impacting plant performance. This information, along with new tools, will help foster the improvement of perennial grasses for feedstock applications.

09 BIOMASS FUELS↗
DOE OSTI2015

Species interactions differ in their genetic robustness

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica . The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The Genetic Architecture of Shoot and Root Trait Divergence Between Mesic and Xeric Ecotypes of a Perennial Grass

Environmental heterogeneity can drive patterns of functional trait variation and lead to the formation of locally adapted ecotypes. Plant ecotypes are often differentiated by suites of correlated root and shoot traits that share common genetic, developmental, and physiological relationships. For instance, although plant water loss is largely governed by shoot systems, root systems determine water access and constrain shoot water status. To evaluate the genetic basis of root and shoot trait divergence, we developed a recombinant inbred population derived from mesic and xeric ecotypes of the perennial grass Panicum hallii. Our study sheds light on the genetic architecture underlying the relationships between root and shoot traits. We identified several genomic “hotspots” which control suites of correlated root and shoot traits, thus indicating genetic coordination between plant organ systems in the process of ecotypic divergence. Genomic regions of colocalized quantitative trait locus (QTL) for the majority of shoot and root growth related traits were independent of colocalized QTL for shoot and root resource acquisition traits. The allelic effects of individual QTL underscore ecological specialization for drought adaptation between ecotypes and reveal possible hybrid breakdown through epistatic interactions. These results have implications for understanding the factors constraining or facilitating local adaptation in plants.

epistasis↗
NASA NTRS2020

Genetic Algorithm for Optimization of Neural Networks for Bayesian Inference of Model Uncertainty

The objective of this work was to develop a genetic optimization algorithm that can design a neural network capable of producing uncertainty estimates along with predictions. This algorithm is necessary because the inclusion of uncertainty modeling in a neural network greatly complicates the network’s design space, making the development of a converging model extremely difficult and time consuming. The genetic algorithm presented in this work uses a number of value ranges for various configurable neural network parameters to create a randomly generated population of network architectures. The initially generated population is then evolved over the course of several generations, with the best performing models breeding to produce novel network configurations. Mutations are randomly applied to the network designs to facilitate the development of adaptations beneficial to the task being performed. An experiment was conducted to validate the proposed algorithm, in which the genetic optimizer was tasked with producing a neural network capable of predicting the sound pressure level (SPL) resulting from jet-surface interaction (JSI) noise. The data used for this task was generated at the NASA Glenn Research Center in the Aero-Acoustic Propulsion Laboratory. Starting with an initial population size of 35 randomly generated networks, and evolved over the course of 10 generations, the genetic algorithm produced a design able to predict SPL as a result of JSI noise within 0.272 dB, on average.

Genetic algorithm↗
DOE OSTI2019

Dispersal of Amur tiger from spatial distribution and genetics within the eastern Changbai mountain of China

Abstract Population dispersal and migration often indicate an expanded habitat and reduced inbreeding probability, and to some extend reflects improvement in the condition of the population. The Amur tiger population in the northern region of the Changbai mountain in China mostly distributes along the Sino–Russian border, next to the population in southwest Primorye in Russia. The successful dispersal westward and transboundary movement are crucial for the persistence of the Amur tiger in this area. This study explored the spatial dispersal of the population, transboundary migration, and the genetic condition of the Amur tiger population within the northern Changbai mountain in China, using occurrence data and fecal samples. Our results from 2003 to 2016 showed that the Amur tiger population in this area was spreading westward at a speed of 12.83 ± 4.41 km every three years. Genetic diversity of the Amur tiger populations in southwest Primorye was slightly different than the population in our study area, and the potential individual migration rate between these two populations was shown to be about 13.04%. Furthermore, the relationships between genetic distances and spatial distances indicated the existence of serious limitations to the dispersal of the Amur tiger in China. This study provided important information about spatial dispersal, transboundary migration, and the genetic diversity of Amur tigers in China, showed the urgent need for Amur tiger habitat restoration, and suggested some important conservation measures, such as corridor construction to eliminate dispersal barriers and joint international conservation to promote trans‐boundary movement.

Ning, Yao↗
DOE OSTI2016

Genetic co-structuring in host-parasite systems: Empirical data from raccoons and raccoon ticks

Many aspects of parasite biology critically depend on their hosts, and understanding how host-parasite populations are co-structured can help improve our understanding of the ecology of parasites, their hosts, and host-parasite interactions. Here, this study utilized genetic data collected from raccoons (Procyon lotor), and a specialist parasite, the raccoon tick (Ixodes texanus), to test for genetic co-structuring of host-parasite populations at both landscape and host scales. At the landscape scale, our analyses revealed a significant correlation between genetic and geographic distance matrices (i.e., isolation by distance) in ticks, but not their hosts. While there are several mechanisms that could lead to a stronger pattern of isolation by distance in tick vs. raccoon datasets, our analyses suggest that at least one reason for the above pattern is the substantial increase in statistical power (due to the ≈8-fold increase in sample size) afforded by sampling parasites. Host-scale analyses indicated higher relatedness between ticks sampled from related vs. unrelated raccoons trapped within the same habitat patch, a pattern likely driven by increased contact rates between related hosts. Lastly, by utilizing fine-scale genetic data from both parasites and hosts, our analyses help improve our understanding of epidemiology and host ecology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The future of legume genetic data resources: Challenges, opportunities, and priorities

Abstract Legumes, comprising one of the largest, most diverse, and most economically important plant families, are the subject of vibrant research and development worldwide. Continued improvement of legume crops will benefit from the recent proliferation of genetic (including genomic) resources; but the diversity, scale, and complexity of these resources presents challenges to those managing and using them. A workshop held in March of 2019 addressed questions of data resources and priorities for the legumes. The workshop identified various needs and recommendations: (a) Develop strategies to effectively store, integrate, and relate genetic resources collected in different projects. (b) Leverage information collected across many legume species by standardizing data formats and ontologies, improving the state of metadata about datasets, and increasing use of the FAIR data principles. (c) Advocate for the critical role that curators exercise in integrating complex datasets into databases and adding high value metadata that enable downstream analytics and facilitate practical applications. (d) Implement standardized software and database development practices to best leverage limited developer time and expertise gained from the various legume (and other) species. (e) Develop tools and databases that can manage genetic information for the world's plant genetic resources, enabling efficient incorporation of important traits into breeding programs. (f) Centralize information on databases, tools, and training materials and establish funding streams to support training and outreach.

Bauchet, Guillaume J.↗
DOE OSTI2023

Demographic and genetic consequences of a steelhead supplementation program

Abstract Objective Supplementation of naturally spawning populations by the addition of hatchery-spawned individuals is commonly conducted for recovery of threatened and endangered populations and to support harvest opportunities. Our objective was to evaluate whether the use of a juvenile captive broodstock and an integrated paradigm could increase returns of steelhead, the anadromous form of Rainbow Trout Oncorhynchus mykiss, while avoiding negative genetic impacts commonly associated with hatchery propagation. Methods We analyzed 291 genetic markers in adult steelhead returning to an integrated population in southwest Washington over the course of 15 years. Reproductive success (RS) of fish spawning in the natural environment was evaluated by origin (hatchery versus natural) and return year. Data were then pooled over years to maximize sample sizes for comparing RS estimates among groups (i.e., estimation of relative reproductive success [RRS]). Result We observed a weak relationship between RS and origin (male p = 0.347; female p = 0.066), but a significant relationship between RS and return year (male p < 0.001, η2 = 0.896; female p ⟨ 0.001, η2 = 0.867) (i.e., hatchery- and natural-origin fish did well or poorly together each year). Estimates of RRS for fish spawned in the hatchery ranged from 2.4 to 6.4, indicating that fish spawned in the hatchery produced more returning adult progeny than did fish allowed to spawn in the natural environment. Estimates of RRS were ⟨1.0 for hatchery-origin fish spawning in the natural environment, but the difference was nonsignificant for males and marginally significant for females. Hatchery-origin fish exhibited reduced genetic diversity as well as evidence of increased temporal population structure. Conclusion We conclude that the program was successful in achieving an increase in adult returns but not in avoiding negative genetic effects on the population and that any lasting impacts of supplementation remain to be determined.

Smith, Christian T. (ORCID:0000000240522669)↗
DOE OSTI2020

Genetic control of root anatomical plasticity in maize

Root anatomical phenes have important roles in soil resource capture and plant performance; however, their phenotypic plasticity and genetic architecture is poorly understood. We hypothesized that (a) the responses of root anatomical phenes to water deficit (stress plasticity) and different environmental conditions (environmental plasticity) are genetically controlled and (b) stress and environmental plasticity are associated with different genetic loci than those controlling the expression of phenes under water-stress and well-watered conditions. Root anatomy was phenotyped in a large maize (Zea mays L.) association panel in the field with and without water deficit stress in Arizona and without water deficit stress in South Africa. Anatomical phenes displayed stress and environmental plasticity; many phenotypic responses to water deficit were adaptive, and the magnitude of response varied by genotype. We identified 57 candidate genes associated with stress and environmental plasticity and 64 candidate genes associated with phenes under well-watered and water-stress conditions in Arizona and under well-watered conditions in South Africa. Four candidate genes co-localized between plasticity groups or for phenes expressed under each condition. The genetic architecture of phenotypic plasticity is highly quantitative, and many distinct genes control plasticity in response to water deficit and different environments, which poses a challenge for breeding programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Searching the landscape of flux vacua with genetic algorithms

In this paper, we employ genetic algorithms to explore the landscape of type IIB flux vacua. We show that genetic algorithms can efficiently scan the landscape for viable solutions satisfying various criteria. More specifically, we consider a symmetric T 6 as well as the conifold region of a Calabi-Yau hypersurface. We argue that in both cases genetic algorithms are powerful tools for finding flux vacua with interesting phenomenological properties. We also compare genetic algorithms to algorithms based on different breeding mechanisms as well as random walk approaches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Selection-enriched genomic loci (SEGL) reveals genetic loci for environmental adaptation and photosynthetic productivity in Chlamydomonas reinhardtii

This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify “Selection-Enriched Genomic Loci” (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity. Increasing the photosynthetic efficiency of algae during biomass production is perhaps the most critical hurdle for economically sustainable algal based biofuels. This presents unique challenges because modifications designed to increase photosynthesis often result in decreased fitness, due to production of toxic reactive oxygen species when photosynthesis is not adequately regulated. These problems are exacerbated under natural and outdoor production environments because of the complex nature of photosynthesis and the multifaceted interactions between genetic, environmental and physiological factors. Here, we demonstrate a high throughput biotechnological screening approach that simultaneously produces algal strains with highly increased autotrophic productivity and identifies genomic loci contributing to these improvements. Our results demonstrate that Chlamydomonas reinhardtii exhibits high directed evolutionary capacity readily accessed through breeding and selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Genetic variation in the CYP1A1 gene is related to circulating PCB118 levels in a population-based sample

Several of the polychlorinated biphenyls (PCBs), i.e. the dioxin-like PCBs, are known to induce the P450 enzymes CYP1A1, CYP1A2 and CYP1B1 by activating the aryl hydrocarbon receptor (Ah)-receptor. We evaluated if circulating levels of PCBs in a population sample were related to genetic variation in the genes encoding these CYPs. In the population-based Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study (1016 subjects all aged 70), 21 SNPs in the CYP1A1, CYP1A2 and CYP1B1 genes were genotyped. Sixteen PCB congeners were analysed by high-resolution chromatography coupled to high-resolution mass spectrometry (HRGC/ HRMS). Of the investigated relationships between SNPs in the CYP1A1, CYP1A2 and CYP1B1 and six PCBs (congeners 118, 126, 156, 169, 170 and 206) that captures >80% of the variation of all PCBs measured, only the relationship between CYP1A1 rs2470893 was significantly related to PCB118 levels following strict adjustment for multiple testing (p=0.00011). However, there were several additional SNPs in the CYP1A2 and CYP1B1 that showed nominally significant associations with PCB118 levels (p-values in the 0.003–0.05 range). Further, several SNPs in the CYP1B1 gene were related to both PCB156 and PCB206 with p-values in the 0.005–0.05 range. Very few associations with p<0.05 were seen for PCB126, PCB169 or PCB170. Genetic variation in the CYP1A1 was related to circulating PCB118 levels in the general elderly population. Genetic variation in CYP1A2 and CYP1B1 might also be associated with other PCBs. - Highlights: • We studied the relationship between PCBs and the genetic variation in the CYP genes. • Cross sectional data from a cohort of elderly were analysed. • The PCB levels were evaluated versus 21 SNPs in three CYP genes. • PCB 118 was related to variation in the CYP1A1 gene.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Genetic polymorphisms of GRIN2A and GRIN2B modify the neurobehavioral effects of low-level lead exposure in children

Highlights: • Genetic polymorphisms may increase adverse effects of Pb on neurobehavioral processes. • We studied 330 participants of the Casa Pia Dental Amalgams Trial in Children. • Adverse interactions were found with variants of GRIN2A and GRIN2B in boys. • Our results implicate genetic factors in defining susceptibility to Pb neurotoxicity. Lead (Pb) is neurotoxic and children are highly susceptible to this effect, particularly within the context of continuous low-level Pb exposure. A current major challenge is identification of children who may be uniquely susceptible to Pb toxicity because of genetic predisposition. Learning and memory are among the neurobehavioral processes that are most notably affected by Pb exposure, and modification of N-methyl-D-aspartate receptors (NMDAR) that regulate these processes during development are postulated to underlie these adverse effects of Pb. We examined the hypothesis that polymorphic variants of genes encoding glutamate receptor, ionotropic, NMDAR subunits 2A and 2B, GRIN2A and GRIN2B, exacerbate the adverse effects of Pb exposure on these processes in children. Participants were subjects who participated as children in the Casa Pia Dental Amalgam Clinical Trial and for whom baseline blood Pb concentrations and annual neurobehavioral test results over the 7 year course of the clinical trial were available. Genotyping assays were performed for variants of GRIN2A (rs727605 and rs1070503) and GRIN2B (rs7301328 and rs1806201) on biological samples acquired from 330 of the original 507 trial participants. Regression modeling strategies were employed to evaluate the association between genotype status, Pb exposure, and neurobehavioral test outcomes. Numerous significant adverse interaction effects between variants of both GRIN2A and GRIN2B, individually and in combination, and Pb exposure were observed particularly among boys, preferentially within the domains of Learning & Memory and Executive Function. In contrast, very few interaction effects were observed among similarly genotyped girls with comparable Pb exposure. These findings support observations of an essential role of GRIN2A and GRIN2B on developmental processes underlying learning and memory as well as other neurological functions in children and demonstrate, further, modification of Pb effects on these processes by specific variants of both GRIN2A and GRIN2B genes. These observations highlight the importance of genetic factors in defining susceptibility to Pb neurotoxicity and may have important public health implications for future strategies aimed at protecting children and adolescents from potential health risks associated with low-level Pb exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Genetic Susceptibility to Head and Neck Squamous Cell Carcinoma

Head-and-neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide, and its incidence is growing. Although environmental carcinogens and carcinogenic viruses are the main etiologic factors, genetic predisposition obviously plays a risk-modulating role, given that not all individuals exposed to these carcinogens experience the disease. This review highlights some aspects of genetic susceptibility to HNSCC: among others, genetic polymorphisms in biotransformation enzymes, DNA repair pathway, apoptotic pathway, human papillomavirus-related pathways, mitochondrial polymorphisms, and polymorphism related to the bilirubin-metabolized pathway. Furthermore, epigenetic variations, familial forms of HNSCC, functional assays for HNSCC risk assessment, and the implications and perspectives of research on genetic susceptibility in HNSCC are discussed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Evidence for a genetic basis in functional trait tradeoffs with microbial growth rate but not growth yield

Tradeoffs in microbial functional traits have been a focus of recently described ecological frameworks and of mathematical models of microbial community functioning. Tradeoffs in key traits such as growth rate, growth yield, resource acquisition, and stress tolerance may have either a genetic basis or a physiological basis, and the type of tradeoff can inform how traits are modeled and measured. Here we provide evidence that growth rate/decomposition and growth rate/stress tolerance tradeoffs have a primarily genetic basis in a phylogenetically diverse suite of ten leaf litter-inhabiting fungi. In contrast, growth yield tradeoffs with functional traits are more likely to have a physiological basis. Consideration of the type of tradeoff, genetic or physiological, should help to inform efforts to model microbial contributions to ecosystem processes, especially when considering different scales. Consideration of physiological tradeoffs may be important for understanding short-term variability (e.g., pulse events) and fine spatial scales, whereas genetic tradeoffs are likely to be useful for understanding regional- to continental-scale and medium- to long-term contributions of microbes to ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Genetic correlation network prediction of forest soil microbial functional organization

Soil ecological functions are largely determined by the activities of soil microorganisms, which, in turn, are regulated by relevant interactions between genes and their corresponding pathways. Therefore, the genetic network can theoretically elucidate the functional organization that supports complex microbial community functions, although this has not been previously attempted. We generated a genetic correlation network based on 5421 genes derived from metagenomes of forest soils, identifying 7191 positive and 123 negative correlation relationships. This network consisted of 27 clusters enriched with sets of genes within speci fi c functions, represented with corresponding cluster hubs. The clusters revealed a hierarchical architecture, re fl ecting the functional organization in the soil metagenomes. Positive correlations mapped functional associations, whereas negative correlations often mapped regulatory processes. The potential functions of uncharacterized genes were predicted based on the functions of located clusters. The global genetic correlation network highlights the functional organization in soil metagenomes and provides a resource for predicting gene functions. We anticipate that the genetic correlation network may be exploited to comprehensively decipher soil microbial commu

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Genetic risk for Alzheimer’s dementia predicts motor deficits through multi-omic systems in older adults

Alzheimer’s disease manifests with both cognitive and motor deficits. However, the degree to which genetic risk of Alzheimer’s dementia contributes to late-life motor impairment, and the specific molecular systems underlying these associations, are uncertain. Here, we adopted an integrative multi-omic approach to assess genetic influence on motor impairment in older adults and identified key molecular pathways that may mediate this risk. We built a polygenic risk score for clinical diagnosis of Alzheimer’s dementia (AD-PRS) and examined its relationship to several motor phenotypes in 1885 older individuals from two longitudinal aging cohorts. We found that AD-PRS was associated with a previously validated composite motor scores and their components. The major genetic risk factor for sporadic Alzheimer’s dementia, the APOE/TOMM40 locus, was not a major driver of these associations. To identify specific molecular features that potentially medicate the genetic risk into motor dysfunction, we examined brain multi-omics, including transcriptome, DNA methylation, histone acetylation (H3K9AC), and targeted proteomics, as well as diverse neuropathologies. We found that a small number of factors account for the majority of the influence of AD-PRS on motor function, which comprises paired helical filament tau-tangle density, H3K9AC in specific chromosomal regions encoding genes involved in neuromuscular process. These multi-omic factors have the potential to elucidate key molecular mechanisms developing motor impairment in the context of Alzheimer’s dementia.

60 APPLIED LIFE SCIENCES↗