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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June 2018)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June 2018 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 12 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 1233 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A haplotype-resolved, chromosome-scale genome assembly for the southern live oak, Quercus virginiana

Hybridization is a major force driving diversification, migration, and adaptation in Quercus species. While population genetics and phylogenetics have traditionally been used for studying these processes, advances in sequencing technology now enable us to incorporate comparative and pan-genomic approaches as well. Here, we present a highly contiguous, chromosome-scale and haplotype-resolved genome assembly for the southern live oak, Quercus virginiana, the first reference genome for section Virentes, as part of the American Campus Tree Genomes program. Originating from a clone of Auburn University's historic “Toomer's Oak,” this assembly contributes to the pool of genomic resources for investigating recombination, haplotype variation, and structural genomic changes influencing hybridization potential in this clade and across Quercus. It also provides insights into the architecture of the putative centromeric regions within the genus. Alongside other oak references, the Q. virginiana genome will support research into the evolution and adaptation of the Quercus genus.

Quercus virginiana↗
DOE OSTI2024

Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel

Abstract Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)—an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (β-carotene, β-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside β-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June to October 2020)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June to October 2020 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 30 cm depth below surface to just above the cobble layer (~190-250 cm depth) at discrete depths every 40 cm for microbial analyses. A total of 35 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2848 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Real-time bioelectronic sensing of environmental contaminants

Real-time chemical sensing is crucial for applications in environmental and health monitoring. Biosensors can detect a variety of molecules through genetic circuits that use these chemicals to trigger the synthesis of a coloured protein, thereby producing an optical signal. However, the process of protein expression limits the speed of this sensing to approximately half an hour, and optical signals are often difficult to detect in situ. Here we combine synthetic biology and materials engineering to develop biosensors that produce electrical readouts and have detection times of minutes. Here we programmed Escherichia coli to produce an electrical current in response to specific chemicals using a modular, eight-component, synthetic electron transport chain. As designed, this strain produced current following exposure to thiosulfate, an anion that causes microbial blooms, within 2 min. This amperometric sensor was then modified to detect an endocrine disruptor. The incorporation of a protein switch into the synthetic pathway and encapsulation of the bacteria with conductive nanomaterials enabled the detection of the endocrine disruptor in urban waterway samples within 3 min. Our results provide design rules to sense various chemicals with mass-transport-limited detection times and a new platform for miniature, low-power bioelectronic sensors that safeguard ecological and human health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A MUC 5 B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality

A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post–COVID-19 pneumonia were performed in MVP subjects. The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (August 2015)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken August 29, 2015 at a location (KB1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples from a deep soil pit were collected from 0 to 234 cm depth below surface at discrete depths every ~10-20 cm for microbial analyses. 13 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores).This dataset includes a zip file of 2216 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Author Correction: Engineering self-deliverable ribonucleoproteins for genome editing in the brain

Correction to: Nature Communicationshttps://doi.org/10.1038/s41467-024-45998-2, published online 26 February 2024. In the Acknowledgements section of this article, the grant number relating to National Institutes of Health funding to J.A.D. was incorrectly given as RM1HG009490 and should have been U19NS132303. The grant number 2334028 relating to the National Science Foundation funding to J.A.D. was omitted. Funding from Hampton University Summer Undergraduate Research Program, Mr. Li Ka Shing, Emerson Collective and the Innovative Genomics Institute (IGI) were omitted. The original article has been corrected.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗
DOE OSTI2024

Molecular and Epidemiological Investigation of Fluconazole-resistant Candida parapsilosis —Georgia, United States, 2021

Abstract Background Reports of fluconazole-resistant Candida parapsilosis bloodstream infections are increasing. We describe a cluster of fluconazole-resistant C parapsilosis bloodstream infections identified in 2021 on routine surveillance by the Georgia Emerging Infections Program in conjunction with the Centers for Disease Control and Prevention. Methods Whole-genome sequencing was used to analyze C parapsilosis bloodstream infections isolates. Epidemiological data were obtained from medical records. A social network analysis was conducted using Georgia Hospital Discharge Data. Results Twenty fluconazole-resistant isolates were identified in 2021, representing the largest proportion (34%) of fluconazole-resistant C parapsilosis bloodstream infections identified in Georgia since surveillance began in 2008. All resistant isolates were closely genetically related and contained the Y132F mutation in the ERG11 gene. Patients with fluconazole-resistant isolates were more likely to have resided at long-term acute care hospitals compared with patients with susceptible isolates (P = .01). There was a trend toward increased mechanical ventilation and prior azole use in patients with fluconazole-resistant isolates. Social network analysis revealed that patients with fluconazole-resistant isolates interfaced with a distinct set of healthcare facilities centered around 2 long-term acute care hospitals compared with patients with susceptible isolates. Conclusions Whole-genome sequencing results showing that fluconazole-resistant C parapsilosis isolates from Georgia surveillance demonstrated low genetic diversity compared with susceptible isolates and their association with a facility network centered around 2 long-term acute care hospitals suggests clonal spread of fluconazole-resistant C parapsilosis. Further studies are needed to better understand the sudden emergence and transmission of fluconazole-resistant C parapsilosis.

Misas, Elizabeth (ORCID:0000000162437716)↗
DOE OSTI2025

Genetic Identification of Lamprey Genera and Anadromous Ecotypes in Watersheds of the Northeastern Pacific Ocean

ABSTRACT Nonparasitic, nonmigratory Western Brook Lamprey (WBL; Lampetra ayresii ), and parasitic, anadromous Western River Lamprey (WRL; L. ayresii ) are sympatric lampreys that likely represent different life history variations of a single species. Novel genetic tools are critical for differentiating WBL and WRL, whose larvae preclude morphological identification (ID) and will enable comprehensive assessment of imperiled native lampreys of the Northeastern Pacific (including WBL, WRL, and Pacific Lamprey, Entosphenus tridentatus ). We developed 47 candidate single nucleotide polymorphism (SNP) markers using whole genome resequencing of WBL ( N = 24) and WRL ( N = 15) from Ksi Ts'oohl Ts'ap Creek (Nass River, British Columbia, Canada) which are likely ecotypes distinguished by few divergent SNPs across multiple chromosomes. We used five novel candidate SNPs to perform genetic ID of WBL and WRL ecotypes in collections of mixed native lampreys from lower Columbia River tributaries ( N = 1474), Ksi Ts'oohl Ts'ap Creek ( N = 352), and ocean phase WRL from the Georgia Basin (Salish Sea, British Columbia, Canada; N = 91). Two previously published SNPs were used to ID genera, Entosphenus versus Lampetra . Morphological ID utilized photographs collected from a subset of genotyped lampreys, and high concordance was demonstrated between ID methods for genera (99%) and Lampetra ecotypes (> 98%). We characterized spatial and temporal composition of lamprey genera and ecotypes surveyed across NE Pacific tributaries under the expectation these compositions would be similar across nearby sites and across years at the same site. Proportions of lamprey genera were highly variable within regions and across years; however, Lampetra ecotypic proportions were spatially and temporally stable. WRL were rare in lower Columbia tributaries (~1% average rate among Lampetra ) and common further north (> 40% of Lampetra ). Genetic ID methods are powerful monitoring tools that create the novel ability to ascertain genera and ecotypes regardless of life stage, while increasing the efficiency of surveys by eliminating time‐intensive morphological data collection.

Silver, G. S. [Columbia River Inter‐Tribal Fish Co↗
DOE OSTI2021

Genetic determinants of endophytism in the Arabidopsis root mycobiome

The roots of Arabidopsis thaliana host diverse fungal communities that affect plant health and disease states. Here, we sequence the genomes of 41 fungal isolates representative of the A. thaliana root mycobiota for comparative analysis with other 79 plant-associated fungi. Our analyses indicate that root mycobiota members evolved from ancestors with diverse lifestyles and retain large repertoires of plant cell wall-degrading enzymes (PCWDEs) and effector-like small secreted proteins. We identify a set of 84 gene families associated with endophytism, including genes encoding PCWDEs acting on xylan (family GH10) and cellulose (family AA9). Transcripts encoding these enzymes are also part of a conserved transcriptional program activated by phylogenetically-distant mycobiota members upon host contact. Recolonization experiments with individual fungi indicate that strains with detrimental effects in mono-association with the host colonize roots more aggressively than those with beneficial activities, and dominate in natural root samples. Furthermore, we show that the pectin-degrading enzyme family PL1_7 links aggressiveness of endophytic colonization to plant health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The AXEAP2 program for K β X-ray emission spectra analysis using artificial intelligence

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant K β XES of 3 d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 ( AXEAP2 ), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3 d electron spin state, 3 d –3 p electron exchange force and K β emission core-hole lifetime.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transcriptional networks underlying a primary ovarian insufficiency disorder in alligators naturally exposed to EDCs

Interactions between the endocrine system and environmental contaminants are responsible for impairing reproductive development and function. Despite the taxonomic diversity of affected species and attendant complexity inherent to natural systems, the underlying signaling pathways and cellular consequences are mostly studied in lab models. To resolve the genetic and endocrine pathways that mediate affected ovarian function in organisms exposed to endocrine disrupting contaminants in their natural environments, we assessed broad-scale transcriptional and steroidogenic responses to exogenous gonadotropin stimulation in juvenile alligators (Alligator missippiensis) originating from a lake with well-documented pollution (Lake Apopka, FL) and a nearby reference site (Lake Woodruff, FL). Here, we found that individuals from Lake Apopka are characterized by hyperandrogenism and display hyper-sensitive transcriptional responses to gonadotropin stimulation when compared to individuals from Lake Woodruff. Site-specific transcriptomic divergence appears to be driven by wholly distinct subsets of transcriptional regulators, indicating alterations to fundamental genetic pathways governing ovarian function. Consistent with broad-scale transcriptional differences, ovaries of Lake Apopka alligators displayed impediments to folliculogenesis, with larger germinal beds and decreased numbers of late-stage follicles. After resolving the ovarian transcriptome into clusters of co-expressed genes, most site-associated modules were correlated to ovarian follicule phenotypes across individuals. However, expression of two site-specific clusters were independent of ovarian cellular architecture and are hypothesized to represent alterations to cell-autonomous transcriptional programs. Collectively, our findings provide high resolution mapping of transcriptional patterns to specific reproductive function and advance our mechanistic understanding regarding impaired reproductive health in an established model of environmental endocrine disruption.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Updates to the Alliance of Genome Resources central infrastructure

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific “landing pages” and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (June to October 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken at three time points from June 12, 2019 to October 23,2019 at a location (PTT1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples were collected from 60 to 180 cm below surface every 30cm for microbial analyses through metagenomic sequencing. 15 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 780 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (May to September 2017)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken roughly every month in the period May 18 to September 13 in 2017 at a location (Pit2) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Cores were taken with a hand-auger and separated into 5-20 cm segments based on soil horizonation down to 150 cm depth below surface. Each segment was subsampled for microbial analyses. Corresponding 16S rRNA gene amplicon data is available at the NCBI Single Read Archive (SRA) Database BioProject ID PRJNA626616, and soil geochemistry data at doi:10.15485/1631972. 40 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 6993 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs generated from the Wind River Basin (WRB). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗