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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Persistence and plasticity in bacterial gene regulation

Organisms orchestrate cellular functions through transcription factor (TF) interactions with their target genes, although these regulatory relationships are largely unknown in most species. Here we report a high-throughput approach for characterizing TF-target gene interactions across species and its application to 354 TFs across 48 bacteria, generating 17,000 genome-wide binding maps. This dataset revealed themes of ancient conservation and rapid evolution of regulatory modules. We observed rewiring, where the TF sensing and regulatory role is maintained while the arrangement and identity of target genes diverges, in some cases encoding entirely new functions. We further integrated phenotypic information to define new functional regulatory modules and pathways. So, we identified 242 new TF DNA binding motifs, including a 70% increase of known Escherichia coli motifs and the first annotation in Pseudomonas simiae, revealing deep conservation in bacterial promoter architecture. Our method provides a versatile tool for functional characterization of genetic pathways in prokaryotes and eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Dynamic conformational switching underlies TFIIH function in transcription and DNA repair and impacts genetic diseases

Transcription factor IIH (TFIIH) is a protein assembly essential for transcription initiation and nucleotide excision repair (NER). Yet, understanding of the conformational switching underpinning these diverse TFIIH functions remains fragmentary. TFIIH mechanisms critically depend on two translocase subunits, XPB and XPD. To unravel their functions and regulation, we build cryo-EM based TFIIH models in transcription- and NER-competent states. Using simulations and graph-theoretical analysis methods, we reveal TFIIH’s global motions, define TFIIH partitioning into dynamic communities and show how TFIIH reshapes itself and self-regulates depending on functional context. Our study uncovers an internal regulatory mechanism that switches XPB and XPD activities making them mutually exclusive between NER and transcription initiation. By sequentially coordinating the XPB and XPD DNA-unwinding activities, the switch ensures precise DNA incision in NER. Mapping TFIIH disease mutations onto network models reveals clustering into distinct mechanistic classes, affecting translocase functions, protein interactions and interface dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗
DOE OSTI2025

Metal concentration and leaf spatial distribution assessed by synchrotron µXRF in Brazilian nickel hyperaccumulators

Background and Aims: The limited number of known hyperaccumulator species in tropical regions, including Brazil, has hampered the development of nickel (Ni) agromining. In addition, the mechanisms underlying metal accumulation and distribution in these species remain poorly understood, despite their pivotal role in identifying species with economic potential. Furthermore, this study assessed the accumulation potential and foliar spatial distribution of metals in three Brazilian hyperaccumulator species (Pfaffia sarcophylla, Justicia lanstyakii, and Lippia lupulina) growing in one of the world’s largest mafic–ultramafic complexes. Methods Concentrations of Ni and other metals in leaves were determined using portable X-ray fluorescence (pXRF) and inductively coupled plasma optical emission spectroscopy (ICP-OES). Synchrotron-based X-ray microfluorescence (SR-µXRF) was employed to map the spatial distribution of metals across intact leaves. Results: The results revealed leaf Ni concentrations ranging from 320 to 1,950 mg kg⁻ 1 in P. sarcophylla, 1,640 to 6,810 mg kg⁻ 1 in L. lupulina, and 1,990 to 4,900 mg kg⁻ 1 in J. lanstyakii. Nickel, Mn, and Co exhibited similar distribution patterns, concentrating mainly in the leaf margins and veins across all species, while Ca, K, and Mg co-localization suggests regulatory mechanisms for adaptation. Conclusion: Although these plants exhibited Ni hyperaccumulation, our findings suggest limited commercial potential for agromining. Further research on genetic variability and nutrient assimilation, particularly in P. sarcophylla, is recommended to elucidate the mechanisms underlying Ni accumulation and intraspecific variability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Knocking out the carboxyltransferase interactor 1 (CTI1) in Chlamydomonas boosted oil content by fivefold without affecting cell growth

Summary The first step in chloroplast de novo fatty acid synthesis is catalysed by acetyl‐CoA carboxylase (ACCase). As the rate‐limiting step for this pathway, ACCase is subject to both positive and negative regulation. In this study, we identify a Chlamydomonas homologue of the plant carboxyltransferase interactor 1 (CrCTI1) and show that this protein interacts with the Chlamydomonas α‐carboxyltransferase (Crα‐CT) subunit of the ACCase by yeast two‐hybrid protein–protein interaction assay. Three independent CRISPR‐Cas9 mediated knockout mutants for CrCTI1 each produced an ‘enhanced oil’ phenotype, accumulating 25% more total fatty acids and storing up to fivefold more triacylglycerols (TAGs) in lipid droplets. The TAG phenotype of the crcti1 mutants was not influenced by light but was affected by trophic growth conditions. By growing cells under heterotrophic conditions, we observed a crucial function of CrCTI1 in balancing lipid accumulation and cell growth. Mutating a previously mapped in vivo phosphorylation site (CrCTI1 Ser108 to either Ala or to Asp), did not affect the interaction with Crα‐CT. However, mutating all six predicted phosphorylation sites within Crα‐CT to create a phosphomimetic mutant reduced this pairwise interaction significantly. Comparative proteomic analyses of the crcti1 mutants and WT suggested a role for CrCTI1 in regulating carbon flux by coordinating carbon metabolism, antioxidant and fatty acid β‐oxidation pathways, to enable cells to adapt to carbon availability. Taken together, this study identifies CrCTI1 as a negative regulator of fatty acid synthesis in algae and provides a new molecular brick for the genetic engineering of microalgae for biotechnology purposes.

Li, Zhongze [Aix‐Marseille Université, CEA, CNRS, ↗
DOE OSTI2023

Generating Co-expression Networks for Three Cyanobacteria: Synechococcus sp. PCC 7942, Synechococcus sp. PCC 7002, Synechocystis sp. PCC 6803

Cyanobacteria are photosynthetic organisms capable of high growth rate and represent a promising bioplatform for harnessing the sun’s energy to make biofuel. Additionally, the process of photosynthesis absorbs CO2 from the environment. Understanding the metabolic processes involved in photosynthesis could lead to solutions to the recent rise of CO2 concentration in Earth’s atmosphere and the associated climate change. More research on the transcriptional regulation of these cells is needed to learn how to harness the untapped potential of cyanobacteria for these applications. Transcriptional analysis via RNA-seq provides an understanding of how gene expression changes at the mRNA level under diverse growing conditions. I systematically collected and analyzed RNA-Seq data obtained under a variety of conditions and available on the NCBI database for three cyanobacteria model organisms: Synechococcus elongatus sp. PCC 7942, Synechococcus sp. PCC 7002, and Synechocystis sp. PCC 6803. For each organism, the data was mapped to a reference genome to characterize the RNA expression profile. Samples were checked for quality based on the number of reads and the correlation of the expression profile between labeled replicates. All samples were transformed into transcripts per million reads, followed by a log transformation to account for the wide range of sample sizes. Gene co-expression networks were generated and analyzed for each species using Cytoscape. These networks provide a base level of gene expression for each species. The network topology and high-betweeness nodes of these networks need to be analyzed further to provide insight on potential ways to harness cyanobacteria genetics. Additionally, these datasets can be used together to form a core genome network analysis- one that includes only the genes that are homologous between the three species. This project has prepared the way for a more in-depth study on photosynthetic microbes on a genetic level.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Structural characterization and regulatory element analysis of the heart isoform of cytochrome c oxidase VIa

In order to investigate the mechanism(s) governing the striated muscle-specific expression of cytochrome c oxidase VIaH we have characterized the murine gene and analyzed its transcriptional regulatory elements in skeletal myogenic cell lines. The gene is single copy, spans 689 base pairs (bp), and is comprised of three exons. The 5'-ends of transcripts from the gene are heterogeneous, but the most abundant transcript includes a 5'-untranslated region of 30 nucleotides. When fused to the luciferase reporter gene, the 3.5-kilobase 5'-flanking region of the gene directed the expression of the heterologous protein selectively in differentiated Sol8 cells and transgenic mice, recapitulating the pattern of expression of the endogenous gene. Deletion analysis identified a 300-bp fragment sufficient to direct the myotube-specific expression of luciferase in Sol8 cells. The region lacks an apparent TATA element, and sequence motifs predicted to bind NRF-1, NRF-2, ox-box, or PPAR factors known to regulate other nuclear genes encoding mitochondrial proteins are not evident. Mutational analysis, however, identified two cis-elements necessary for the high level expression of the reporter protein: a MEF2 consensus element at -90 to -81 bp and an E-box element at -147 to -142 bp. Additional E-box motifs at closely located positions were mutated without loss of transcriptional activity. The dependence of transcriptional activation of cytochrome c oxidase VIaH on cis-elements similar to those found in contractile protein genes suggests that the striated muscle-specific expression is coregulated by mechanisms that control the lineage-specific expression of several contractile and cytosolic proteins.

Non-NASA Center↗
DOE OSTI2022

Chromatin structure predicts survival in glioma patients

The pathological changes in epigenetics and gene regulation that accompany the progression of low-grade to high-grade gliomas are under-studied. The authors use a large set of paired atac-seq and RNA-seq data from surgically resected glioma specimens to infer gene regulatory relationships in glioma. Thirty-eight glioma patient samples underwent atac-seq sequencing and 16 samples underwent additional RNA-seq analysis. Using an atac-seq/RNA-seq correlation matrix, atac-seq peaks were paired with genes based on high correlation values (|r 2 | > 0.6). Samples clustered by IDH1 status but not by grade. Surprisingly there was a trend for IDH1 mutant samples to have more peaks. The majority of peaks are positively correlated with survival and positively correlated with gene expression. Constructing a model of the top six atac-seq peaks created a highly accurate survival prediction model (r 2 = 0.68). Four of these peaks were still significant after controlling for age, grade, pathology, IDH1 status and gender. Grade II, III, and IV (primary) samples have similar transcription factors and gene modules. However, grade IV (recurrent) samples have strikingly few peaks. Patient-derived glioma cultures showed decreased peak counts following radiation indicating that this may be radiation-induced. This study supports the notion that IDH1 mutant and IDH1 wildtype gliomas have different epigenetic landscapes and that accessible chromatin sites mapped by atac-seq peaks tend to be positively correlated with expression. The data in this study leads to a new model of treatment response wherein glioma cells respond to radiation therapy by closing open regions of DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bridging Hydrological Ensemble Simulation and Learning Using Deep Neural Operators

Ensemble-based simulation and learning (ESnL) has long been used in hydrology for parameter inference, but computational demands of process-based ESnL can be quite high. To address this issue, we propose a deep neural operator learning approach. Neural operators are generic machine learning algorithms that can learn functional mappings between infinite-dimensional spaces, providing a highly flexible tool for scientific machine learning. Our approach is built upon DeepONet, a specific deep neural operator, and is designed to address several common problems in hydrology, namely, model parameter estimation, prediction at ungaged locations, and uncertainty quantification. Here we demonstrate the effectiveness of our DeepONet-based workflow using an existing large model ensemble created for an eastern U.S. watershed that is instrumented with 10 streamflow gages. Results suggest DeepONet achieves high efficiency in learning an ML surrogate model from the model ensemble, with the modified Kling-Gupta Efficiency exceeding 0.9 on holdout test sets. Parameter inference, carried out using the trained DeepONet surrogate model and genetic algorithm, also yields robust results. Additionally, we formulate and train a separate DeepONet model for physics-informed, seq-to-seq streamflow forecasting, which further reduces biases in the pre-trained DeepONet surrogate model. While this study focuses primarily on a single watershed, our approach is general and may be extended to enable learning from model ensembles across multiple basins or models. Thus, this research represents a significant contribution to the application of hybrid machine learning in hydrology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Multispectral mapping of the Apollo 15-Apennine region - The identification and distribution of regional pyroclastic deposits

Multispectral mapping of the Apollo 15-Apennine region has allowed the identification of numerous dark mantle deposits of probable pyroclastic origin. The deposits display a low albedo, appear to mantle and slightly subdue subjacent terrain, are spectrally distinct on the multispectral maps (high in the infrared but low in the ultraviolet) and generally exhibit a weak depolarized 3.8 cm radar echo. These characteristics are consistent with an origin by pyroclastic eruption. The regional dark mantle deposits are commonly associated with vents along marginal fractures and faults near the base of the Apennines, thereby emphasizing the role of basin-controlled weaknesses in providing channels for the upward migration of magma generated at depth. The spectral properties of the pyroclastic deposits are incompatible with those of Apollo 15 green glass but the deposits may be composed of material similar to the Apollo 15 brown or yellow glass. If so, the widespread distribution of the deposits suggest that mare basalts genetically related to the brown or yellow glass may occur in the Apollo 15 region. Moreover, pyroclastic volcanic activity has apparently been a more important and widespread process in the Apollo 15-Apennine region than has previously been thought.

Hawke, B. R.↗
NASA NTRS1993

Phenotypic characterization of xpr, a global regulator of extracellular virulence factors in Staphylococcus aureus

We recently described a Tn551 insertion in the chromosome of Staphylococcus aureus S6C that resulted in drastically reduced expression of extracellular lipase (M. S. Smeltzer, S. R. Gill, and J. J. Iandolo, J. Bacteriol. 174:4000-4006, 1992). The insertion was localized to a chromosomal site (designated omega 1058) distinct from the lipase structural gene (geh) and the accessory gene regulator (agr), both of which were structurally intact in the lipase-negative (Lip-) mutants. In this report, we describe a phenotypic comparison between strains S6C, a hyperproducer of enterotoxin B; KSI9051, a derivative of S6C carrying the Tn551 insertion at omega 1058; ISP546, an 8325-4 strain that carries a Tn551 insertion in the agr locus; and ISP479C, the parent strain of ISP546 cured of the Tn551 delivery plasmid pI258repA36. Compared with their respective parent strains, ISP546 and KSI9051 produced greatly reduced amounts of lipase, alpha-toxin, delta-toxin, protease, and nuclease. KSI9051 also produced reduced amounts of staphylococcal enterotoxin B. Coagulase production was increased in ISP546 but not in KSI9051. Using a mouse model, we also demonstrated that ISP546 and KSI9051 were far less virulent than ISP479C and S6C. We have designated the genetic element defined by the Tn551 insertion at omega 1058 xpr to denote its role as a regulator of extracellular protein synthesis. We conclude that xpr and agr are similar and possibly interactive regulatory genes that play an important role in pathogenesis of staphylococcal disease.

NASA Discipline Cell Biology↗
DOE OSTI2022

Registration of the sorghum carbon–partitioning nested association mapping (CP–NAM) population

The sorghum [ Sorghum bicolor (L.) Moench] carbon-partitioning nested association mapping (CP_NAM) (Reg. no. MP-4, NSL 542189 MAP) population was developed at Clemson University, SC, using 11 diverse, male founder accessions, each crossed with a recurrent female parent ‘Grassl’. The male parents represent all five major botanical races and the four major agronomic types: cellulosic (5), sweet (3), grain (2) and forage (1). A set of 11 recombinant inbred line (RIL) families CP_NAM01 to CP_NAM011 were maintained, which consisted of 2,484 (F 6 ) individuals. Each RIL family contained a minimum of 193 individuals (CP_NAM01) and a maximum of 287 individuals (CP_NAM06). For the development of this population, the founder lines were judiciously selected from the sorghum Bioenergy Association Panel based on carbon-partitioning phenotypes that make this population an ideal genetic resource for dissecting a wide range of agronomic and compositional traits for basic and applied research. The founder accessions of the CP_NAM were phenotypically characterized for various traits, including agronomic, biomass and related components, and additional compositional components. Each of the 11 F 6 RIL families of the CP_NAM were genotyped using genotyping-by-sequencing analysis, and 144,087 single nucleotide polymorphisms were generated for each individual. Genotypic information along with phenotypic data were used for the characterization of this population and to explore the range of phenotypes that permits the understanding of carbon-partitioning dynamics. This population is a unique resource for researchers to study a wide range of contrasting carbon-partitioning characteristics in sorghum to understand the genetic architecture underlying whole-plant carbon partitioning and allocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Pharmacological Profiling of a Brugia malayi Muscarinic Acetylcholine Receptor as a Putative Antiparasitic Target

The diversification of anthelmintic targets and mechanisms of action will help ensure the sustainable control of nematode infections in response to the growing threat of drug resistance. G protein-coupled receptors (GPCRs) are established drug targets in human medicine but remain unexploited as anthelmintic substrates despite their important roles in nematode neuromuscular and physiological processes. Bottlenecks in exploring the druggability of parasitic nematode GPCRs include a limited helminth genetic toolkit and difficulties establishing functional heterologous expression. In an effort to address some of these challenges, we profile the function and pharmacology of muscarinic acetylcholine receptors in the human parasite Brugia malayi, an etiological agent of human lymphatic filariasis. While acetylcholine-gated ion channels are intensely studied as targets of existing anthelmintics, comparatively little is known about metabotropic receptor contributions to parasite cholinergic signaling. Using multivariate phenotypic assays in microfilariae and adults, we show that nicotinic and muscarinic compounds disparately affect parasite fitness traits. We identify a putative G protein-linked acetylcholine receptor of B. malayi (Bma-GAR-3) that is highly expressed across intramammalian life stages and adapt spatial RNA in situ hybridization to map receptor transcripts to critical parasite tissues. Tissue-specific expression of Bma-gar-3 in Caenorhabditis elegans (body wall muscle, sensory neurons, and pharynx) enabled receptor deorphanization and pharmacological profiling in a nematode physiological context. Finally, we developed an image-based feeding assay as a reporter of pharyngeal activity to facilitate GPCR screening in parasitized strains. We expect that these receptor characterization approaches and improved knowledge of GARs as putative drug targets will further advance the study of GPCR biology across medically important nematodes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species

Abstract Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI’s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States

Abstract Cyanobacteria and cyanotoxin producing cyanobacterial blooms are a trending focus of current research. Many studies focus on bloom events in lentic environments such as lakes or ponds. Comparatively few studies have explored lotic environments and fewer still have examined the cyanobacterial communities and potential cyanotoxin producers during ambient, non-bloom conditions. Here we used a metagenomics-based approach to profile non-bloom microbial communities and cyanobacteria in 12 major U.S. rivers at multiple time points during the summer months of 2019. Our data show that U.S. rivers possess microbial communities that are taxonomically rich, yet largely consistent across geographic location and time. Within these communities, cyanobacteria often comprise significant portions and frequently include multiple species with known cyanotoxin producing strains. We further characterized these potential cyanotoxin producing taxa by deep sequencing amplicons of the microcystin E ( mcyE ) gene. We found that rivers containing the highest levels of potential cyanotoxin producing cyanobacteria consistently possess taxa with the genetic potential for cyanotoxin production and that, among these taxa, the predominant genus of origin for the mcyE gene is Microcystis . Combined, these data provide a unique perspective on cyanobacteria and potential cyanotoxin producing taxa that exist in large rivers across the U.S. and can be used to better understand the ambient conditions that may precede bloom events in lotic freshwater ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mapping the Path Forward to Next Generation Algal Technologies: Workshop on Understanding the Rules of Life and Complexity in Algal Systems

Algal technology offers enormous potential as a source of renewable biomass and bioproducts for fuels, biochemicals, nutrients, and numerous other applications. While tremendous opportunities exist, significant challenges are also present in harnessing and utilizing this valuable and potentially sustainable bioproduction platform. Funded by a joint partnership between the Bioenergy Technologies Office (BETO) at the Department of Energy (DOE) and the National Science Foundation (NSF), the recent virtual workshop, "Understanding the Rules of Life: Complexity in Algal Systems Workshop," was organized to bring together thought leaders from academia, national laboratories and other government agencies, and industry to identify key challenges and propose research strategies to overcome these barriers. Two parallel sessions were undertaken: 1) algae strain and toolkit development and 2) algal ecosystem and microbiome dynamics, in order to advance algae engineering and cultivation efforts. In each session, attendees discussed the most pressing challenges from the perspective of model systems and omics analysis. Themes such as genetic engineering toolboxes, translation from the laboratory to outdoor cultivation, functional genomics, metabolomics, algal ecology, consortial design, microbiome dynamics, mathematical models, and data analytics emerged from the discussion. Overall, this workshop has served to elucidate the key hurdles and many opportunities present as we continue to advance algal science and technology from the laboratory and into the commercial realm.

09 BIOMASS FUELS↗
DOE OSTI2021

The Ancient Salicoid Genome Duplication Event: A Platform for Reconstruction of De Novo Gene Evolution in Populus trichocarpa

Orphan genes are characteristic genomic features that have no detectable homology to genes in any other species and represent an important attribute of genome evolution as sources of novel genetic functions. Here, we identified 445 genes specific to Populus trichocarpa. Of these, we performed deeper reconstruction of 13 orphan genes to provide evidence of de novo gene evolution. Populus and its sister genera Salix are particularly well suited for the study of orphan gene evolution because of the Salicoid whole-genome duplication event which resulted in highly syntenic sister chromosomal segments across the Salicaceae. We leveraged this genomic feature to reconstruct de novo gene evolution from intergenera, interspecies, and intragenomic perspectives by comparing the syntenic regions within the P. trichocarpa reference, then P. deltoides, and finally Salix purpurea. Furthermore, we demonstrated that 86.5% of the putative orphan genes had evidence of transcription. Additionally, we also utilized the Populus genome-wide association mapping panel, a collection of 1,084 undomesticated P. trichocarpa genotypes to further determine putative regulatory networks of orphan genes using expression quantitative trait loci (eQTL) mapping. Functional enrichment of these eQTL subnetworks identified common biological themes associated with orphan genes such as response to stress and defense response. We also identify a putative cis-element for a de novo gene and leverage conserved synteny to describe evolution of a putative transcription factor binding site. Overall, 45% of orphan genes were captured in trans-eQTL networks.

59 BASIC BIOLOGICAL SCIENCES↗