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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Complete Genome Sequence and Structure of the Oleaginous Rhodococcus opacus Strain PD630 Through Nanopore Technology

Rhodococcus bacterial strains are characterized by wide metabolic versatility and extraordinary resistance to environmental stresses. The high versatility and adaptability of Rhodococcus strains is partly related with large and complex genomes (up to 10.1 Mbp) including high genetic redundancy and the presence of several circular and linear (mega)plasmids, which harbour peculiar catabolic and biosynthetic genes. Within Rhodococcus genus, R. opacus strain PD630 is considered a model oleaginous strain for its ability to produce and accumulate lipids (mostly triacyglycerols, TAGs) using different carbon sources, including low-cost and renewable resources such as lignocellulose. Notably, under specific growth conditions, this strain is capable of accumulating up to 80% of its cellular dry weight in TAGs; that is a rare feature in the prokaryotic and eukaryotic kingdoms. Multi-omic approaches have been applied to obtain system-level information about metabolic and regulatory pathways involved in these biosynthetic processes. Novel molecular tools for genome editing (CRISPR/Cas9 and recombineering) have been recently developed highlighting the possible utilization of R. opacus PD630 as synthetic biology platform for lipids production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Addressing the pervasive scarcity of structural annotation in eukaryotic algae

Abstract Despite a continuous increase in algal genome sequencing, structural annotations of most algal genome assemblies remain unavailable. This pervasive scarcity of genome annotation has restricted rigorous investigation of these genomic resources and may have precipitated misleading biological interpretations. However, the annotation process for eukaryotic algal species is often challenging as genomic resources and transcriptomic evidence are not always available. To address this challenge, we benchmark the cutting-edge gene prediction methods that can be generalized for a broad range of non-model eukaryotes. Using the most accurate methods selected based on high-quality algal genomes, we predict structural annotations for 135 unannotated algal genomes. Using previously available genomic data pooled together with new data obtained in this study, we identified the core orthologous genes and the multi-gene phylogeny of eukaryotic algae, including of previously unexplored algal species. This study not only provides a benchmark for the use of structural annotation methods on a variety of non-model eukaryotes, but also compensates for missing data in the current spectrum of algal genomic resources. These results bring us one step closer to the full potential of eukaryotic algal genomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Crystallization↗
DOE OSTI2023

Novel candidate genes for lignin structure identified through genome-wide association study of naturally varying Populus trichocarpa

Populus is a promising lignocellulosic feedstock for biofuels and bioproducts. However, the cell wall biopolymer lignin is a major barrier in conversion of biomass to biofuels. To investigate the variability and underlying genetic basis of the complex structure of lignin, a population of 409 three-year-old, naturally varying Populus trichocarpa genotypes were characterized by heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR). A subsequent genome-wide association study (GWAS) was conducted using approximately 8.3 million single nucleotide polymorphisms (SNPs), which identified 756 genes that were significantly associated (−log 10 ( p -value)>6) with at least one lignin phenotype. Several promising candidate genes were identified, many of which have not previously been reported to be associated with lignin or cell wall biosynthesis. These results provide a resource for gaining insights into the molecular mechanisms of lignin biosynthesis and new targets for future genetic improvement in poplar.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet

Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a ‘poor man’s crop’, finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21 st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer

Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic experiments, and with accelerators like GPUs and TPUs making inference using large models rapid, genome-level structure prediction becomes an obvious aim. Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications. Here we describe our efforts to efficiently deploy the AlphaFold v.2 program, for full-proteome structure prediction, at scale on the Oak Ridge Leadership Computing Facility's resources, including the Summit supercomputer. We performed inference to produce the predicted structures for 40,526 protein sequences, corresponding to four prokaryotic proteomes and one plant proteome, using under 4,400 total Summit node hours, equivalent to using the majority of the supercomputer for a little over one hour. We also designed an optimized structure refinement that reduced the time for the relaxation stage of the AlphaFold pipeline by over 10X for longer sequences. We demonstrate the types of analyses that can be performed on proteome-scale collections of sequences, including a search for novel quaternary structures and implications for functional annotation.

Gao, Mu↗
DOE OSTI2026

Structure and sequence evolution in the pennycress ( Thlaspi arvense ) pangenome

Eukaryotic genomes harbor many forms of variation, including nucleotide diversity and structural polymorphisms, which experience natural selection and contribute to genome evolution and biodiversity. Harnessing this variation for agriculture hinges on our ability to detect, quantify, catalog, and deploy genetic diversity. Here, we explore seven complete genomes of the emerging biofuel crop pennycress ( Thlaspi arvense ) drawn from across the species' current genetic diversity to catalog variation in genome structure and content. Across this new pangenome resource, we find contrasting evolutionary modes in different genomic zones. Gene-poor, repeat-rich pericentromeric regions experience frequent rearrangements, including repeated centromere repositioning. By contrast, conserved gene-dense chromosome arms maintain large-scale synteny across accessions even in fast-evolving NOD-like receptor immune genes, where microsynteny breaks down across species, but gene cluster positioning macrosynteny is maintained. Our findings highlight that multiple elements of the genome experience dynamic evolution that conserves functional content on the chromosome scale but allows repositioning and presence–absence variation on a local scale. This diversity is invisible to classical reference-based strategies and highlights the strength and utility of pangenomic resources. These results provide a valuable case study of rapid genomic structural evolution within a species and powerful resources for crop development in an emerging biofuel crop.

Thlaspi arvense↗
DOE OSTI2024

Tertiary folds of the SL5 RNA from the 5 ' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T’s “arms.” Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4 to 6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across these human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9 to 8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4 to 9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities and notable differences, with implications for potential protein-binding modes and therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees

There is overwhelming evidence that forest trees are locally adapted to climate. Thus, genecological models based on population phenotypes have been used to measure local adaptation, infer genetic maladaptation to climate, and guide assisted migration. However, instead of phenotypes, there is increasing interest in using genomic data for gene resource management. We used whole-genome resequencing and common-garden experiments to understand the genetic architecture of adaptive traits in black cottonwood. We studied the potential of using genome-wide association studies (GWAS) and genomic prediction to detect causal loci, identify climate-adapted phenotypes, and inform gene resource management. We analyzed population structure by partitioning phenotypic and genomic (single-nucleotide polymorphism) variation among 840 genotypes collected from 91 stands along 16 rivers. Most phenotypic variation (60 to 81%) occurred among populations and was strongly associated with climate. Population phenotypes were predicted well using genomic data (e.g., predictive abilityr> 0.9) but almost as well using climate or geography (r> 0.8). In contrast, genomic prediction within populations was poor (r< 0.2). We identified many GWAS associations among populations, but most appeared to be spurious based on pooled within-population analyses. Hierarchical partitioning of linkage disequilibrium and haplotype sharing suggested that within-population genomic prediction and GWAS were poor because allele frequencies of causal loci and linked markers differed among populations. Given the urgent need to conserve natural populations and ecosystems, our results suggest that climate variables alone can be used to predict population phenotypes, delineate seed zones and deployment zones, and guide assisted migration.

Science & Technology - Other Topics↗
DOE OSTI2021

High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function

Computational biology is one of many scientific disciplines ripe for innovation and acceleration with the advent of high-performance computing (HPC). In recent years, the field of machine learning has also seen significant benefits from adopting HPC practices. In this work, we present a novel HPC pipeline that incorporates various machine-learning approaches for structure-based functional annotation of proteins on the scale of whole genomes. Our pipeline makes extensive use of deep learning and provides computational insights into best practices for training advanced deep-learning models for high-throughput data such as proteomics data. We showcase methodologies our pipeline currently supports and detail future tasks for our pipeline to envelop, including large-scale sequence comparison using SAdLSA and prediction of protein tertiary structures using AlphaFold2.

Gao, Mu↗
DOE OSTI2021

A viral RNA hijacks host machinery using dynamic conformational changes of a tRNA-like structure

Viruses require multifunctional structured RNAs to hijack their host’s biochemistry, but their mechanisms can be obscured by the difficulty of solving conformationally dynamic RNA structures. Using cryo–electron microscopy (cryo-EM), we visualized the structure of the mysterious viral transfer RNA (tRNA)–like structure (TLS) from the brome mosaic virus, which affects replication, translation, and genome encapsidation. Structures in isolation and those bound to tyrosyl-tRNA synthetase (TyrRS) show that this ~55-kilodalton purported tRNA mimic undergoes large conformational rearrangements to bind TyrRS in a form that differs substantially from that of tRNA. Our study reveals how viral RNAs can use a combination of static and dynamic RNA structures to bind host machinery through highly noncanonical interactions, and we highlight the utility of cryo-EM for visualizing small, conformationally dynamic structured RNAs.

Science & Technology - Other Topics↗
DOE OSTI2023

Two major chromosome evolution events with unrivaled conserved gene content in pomegranate

Pomegranate has a unique evolutionary history given that different cultivars have eight or nine bivalent chromosomes with possible crossability between the two classes. Therefore, it is important to study chromosome evolution in pomegranate to understand the dynamics of its population. Here, we de novo assembled the Azerbaijani cultivar “Azerbaijan guloyshasi” (AG2017; 2n = 16) and re-sequenced six cultivars to track the evolution of pomegranate and to compare it with previously published de novo assembled and re-sequenced cultivars. High synteny was observed between AG2017, Bhagawa (2n = 16), Tunisia (2n = 16), and Dabenzi (2n = 18), but these four cultivars diverged from the cultivar Taishanhong (2n = 18) with several rearrangements indicating the presence of two major chromosome evolution events. Major presence/absence variations were not observed as >99% of the five genomes aligned across the cultivars, while >99% of the pan-genic content was represented by Tunisia and Taishanhong only. We also revisited the divergence between soft- and hard-seeded cultivars with less structured population genomic data, compared to previous studies, to refine the selected genomic regions and detect global migration routes for pomegranate. We reported a unique admixture between soft- and hard-seeded cultivars that can be exploited to improve the diversity, quality, and adaptability of local pomegranate varieties around the world. Our study adds body knowledge to understanding the evolution of the pomegranate genome and its implications for the population structure of global pomegranate diversity, as well as planning breeding programs aiming to develop improved cultivars.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Structural basis for a highly conserved RNA-mediated enteroviral genome replication

Abstract Enteroviruses contain conserved RNA structures at the extreme 5′ end of their genomes that recruit essential proteins 3CD and PCBP2 to promote genome replication. However, the high-resolution structures and mechanisms of these replication-linked RNAs (REPLRs) are limited. Here, we determined the crystal structures of the coxsackievirus B3 and rhinoviruses B14 and C15 REPLRs at 1.54, 2.2 and 2.54 Å resolution, revealing a highly conserved H-type four-way junction fold with co-axially stacked sA-sD and sB-sC helices that are stabilized by a long-range A•C•U base-triple. Such conserved features observed in the crystal structures also allowed us to predict the models of several other enteroviral REPLRs using homology modeling, which generated models almost identical to the experimentally determined structures. Moreover, our structure-guided binding studies with recombinantly purified full-length human PCBP2 showed that two previously proposed binding sites, the sB-loop and 3′ spacer, reside proximally and bind a single PCBP2. Additionally, the DNA oligos complementary to the 3′ spacer, the high-affinity PCBP2 binding site, abrogated its interactions with enteroviral REPLRs, suggesting the critical roles of this single-stranded region in recruiting PCBP2 for enteroviral genome replication and illuminating the promising prospects of developing therapeutics against enteroviral infections targeting this replication platform.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Biochemical and structural basis for YTH domain of human YTHDC1 binding to methylated adenine in DNA

The recently characterized mammalian writer (methyltransferase) and eraser (demethylase) of the DNA N6-methyladenine (N6mA) methyl mark act on single-stranded (ss) and transiently-unpaired DNA. As YTH domain-containing proteins bind N6mA-containing RNA in mammalian cells, we investigated whether mammalian YTH domains are also methyl mark readers of N6mA DNA. Here, we show that the YTH domain of YTHDC1 (known to localize in the nucleus) binds ssDNA containing N6mA, with a 10 nM dissociation constant. This binding is stronger by a factor of 5 than in an RNA context, tested under the same conditions. However, the YTH domains of YTHDF2 and YTHDF1 (predominantly cytoplasmic) exhibited the opposite effect with ~1.5–2× stronger binding to ssRNA containing N6mA than to the corresponding DNA. We determined two structures of the YTH domain of YTHDC1 in complex with N6mA-containing ssDNA, which illustrated that YTHDC1 binds the methylated adenine in a single-stranded region flanked by duplexed DNA. We discuss the hypothesis that the writer-reader-eraser of N6mA-containining ssDNA is associated with maintaining genome stability. Structural comparison of YTH and SRA domains (the latter a DNA 5-methylcytosine reader) revealed them to be diverse members of a larger family of DNA/RNA modification readers, apparently having originated from bacterial modification-dependent restriction enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗