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DOE OSTI2025

Complete genome sequence of Sphingobium yanoikuyae strain CC4533

We have isolated a new strain of Sphingobium yanoikuyae , which belongs to the class Alphaproteobacteria, order Sphingomonadales, and family Sphingomonadaceae. This carotenoid-producing strain is capable of degrading xenobiotics and is tolerant to toxic levels of six heavy metals. We have designated the newly isolated strain of S. yanoikuyae as S. yanoikuyae strain CC4533 (hereafter called strain CC4533) because it was isolated from a contaminated Tris-Acetate-Phosphate (TAP) medium culture plate of a green micro-alga Chlamydomonas reinhardtii wild type strain CC4533. We sequenced the whole genome of strain CC4533 using the PacBio Sequel II Continuous Long Read technology and have submitted it to NCBI along with the SRA and PacBio methylation motif data. Additionally, we have submitted the PacBio methylome to REBASE, Ref#35996. We present the whole genome sequence of S. yanoikuyae strain CC4533 that offers insights into its coding and non-coding genes and its nearest taxonomic neighbors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Genomes of eight cultured microbes from soil sites in Wellesley, MA

We present the genomes of eight cultured microbes isolated from surface soil in Wellesley, MA. The dataset is useful for exploring genomic diversity among freshwater taxa including Pedobacter, Bacillus, Paenibacillus, Streptomyces, and Flavobacterium.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Genome_shuffling_enables_quantitative_trait_locus_mapping_in_Bacillus_subtilis

Genetic mapping is a powerful tool for eukaryotic genetics that has only been applied to bacteria in limited circumstances. Quantitative trait locus (QTL) mapping generally relies on sexual recombination to break linkages between genes, yet bacteria rarely undergo sufficient homologous recombination to generate suitable mapping populations. In this work, we used iterative biparental genome shuffling by protoplast fusion inBacillus subtilisto generate a population of bacteria with substantial random recombination throughout their genomes. Individual shuffled progeny were arrayed in well plates, resequenced, and characterized for a range of complex phenotypes including spore germination and swarming motility. Genetic mapping of the resulting phenotypes identified high-confidence QTLs of moderate size (∼10 kb), and these associations were validated through targeted genetic swaps. ThisB. subtilisQTL population can easily be used to map additional phenotypes, and the general approach for QTL mapping is applicable in a wide range of bacteria.

Bacillus subtilis↗

DOE OSTI2024

Longitudinal genome-wide association study reveals early QTL that predict biomass accumulation under cold stress in sorghum

Sorghum bicolor is a promising cellulosic feedstock crop for bioenergy due to its high biomass yields. However, early growth phases of sorghum are sensitive to cold stress, limiting its planting in temperate environments. Cold adaptability is crucial for cultivating bioenergy and grain sorghum at higher latitudes and elevations, or for extending the growing season. Identifying genes and alleles that enhance biomass accumulation under early cold stress can lead to improved sorghum varieties through breeding or genetic engineering. We conducted image-based phenotyping on 369 accessions from the sorghum Bioenergy Association Panel (BAP) in a controlled environment with early cold treatment. The BAP includes diverse accessions with dense genotyping and varied racial, geographical, and phenotypic backgrounds. Daily, non-destructive imaging allowed temporal analysis of growth-related traits and water use efficiency (WUE). A genome-wide association study (GWAS) was performed to identify genomic intervals and genes associated with cold stress response. The GWAS identified transient quantitative trait loci (QTL) strongly associated with growth-related traits, enabling an exploration of the genetic basis of cold stress response at different developmental stages. This analysis of daily growth traits, rather than endpoint traits, revealed early transient QTL predictive of final phenotypes. The study identified both known and novel candidate genes associated with growth-related traits and temporal responses to cold stress. The identified QTL and candidate genes contribute to understanding the genetic mechanisms underlying sorghum's response to cold stress. These findings can inform breeding and genetic engineering strategies to develop sorghum varieties with improved biomass yields and resilience to cold, facilitating earlier planting, extended growing seasons, and cultivation at higher latitudes and elevations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗

DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗

DOE OSTI2024

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2003

Is there a common mechanism underlying genomic instability, bystander effects and other nontargeted effects of exposure to ionizing radiation?

A number of nontargeted and delayed effects associated with radiation exposure have now been described. These include radiation-induced genomic instability, death-inducing and bystander effects, clastogenic factors and transgenerational effects. It is unlikely that these nontargeted effects are directly induced by cellular irradiation. Instead, it is proposed that some as yet to be identified secreted factor can be produced by irradiated cells that can stimulate effects in nonirradiated cells (death-inducing and bystander effects, clastogenic factors) and perpetuate genomic instability in the clonally expanded progeny of an irradiated cell. The proposed factor must be soluble and capable of being transported between cells by cell-to-cell gap junction communication channels. Furthermore, it must have the potential to stimulate cellular cytokines and/or reactive oxygen species. While it is difficult to imagine a role for such a secreted factor in contributing to transgenerational effects, the other nontargeted effects of radiation may all share a common mechanism.

Non-NASA Center↗

NASA NTRS2003

Radiation-induced genomic instability and its implications for radiation carcinogenesis

Radiation-induced genomic instability is characterized by an increased rate of genetic alterations including cytogenetic rearrangements, mutations, gene amplifications, transformation and cell death in the progeny of irradiated cells multiple generations after the initial insult. Chromosomal rearrangements are the best-characterized end point of radiation-induced genomic instability, and many of the rearrangements described are similar to those found in human cancers. Chromosome breakage syndromes are defined by chromosome instability, and individuals with these diseases are cancer prone. Consequently, chromosomal instability as a phenotype may underlie some fraction of those changes leading to cancer. Here we attempt to relate current knowledge regarding radiation-induced chromosome instability with the emerging molecular information on the chromosome breakage syndromes. The goal is to understand how genetic and epigenetic factors might influence the onset of chromosome instability and the role of chromosomal instability in carcinogenesis.

Review, Tutorial↗

NASA NTRS2002

Genomic instability and bystander effects: a paradigm shift in radiation biology?

A basic paradigm in radiobiology is that, following exposure to ionizing radiation, the deposition of energy in the cell nucleus and the resulting damage to DNA, the principal target, are responsible for the radiation's deleterious biological effects. Findings in two rapidly expanding fields of research--radiation-induced genomic instability and bystander effects--have caused us to reevaluate these central tenets. In this article, the potential influence of induced genomic instability and bystander effects on cellular injury after exposure to low-level radiation will be reviewed.

NASA Discipline Radiation Health↗

NASA NTRS2001

Extracellular signaling through the microenvironment: a hypothesis relating carcinogenesis, bystander effects, and genomic instability

Cell growth, differentiation and death are directed in large part by extracellular signaling through the interactions of cells with other cells and with the extracellular matrix; these interactions are in turn modulated by cytokines and growth factors, i.e. the microenvironment. Here we discuss the idea that extracellular signaling integrates multicellular damage responses that are important deterrents to the development of cancer through mechanisms that eliminate abnormal cells and inhibit neoplastic behavior. As an example, we discuss the action of transforming growth factor beta (TGFB1) as an extracellular sensor of damage. We propose that radiation-induced bystander effects and genomic instability are, respectively, positive and negative manifestations of this homeostatic process. Bystander effects exhibited predominantly after a low-dose or a nonhomogeneous radiation exposure are extracellular signaling pathways that modulate cellular repair and death programs. Persistent disruption of extracellular signaling after exposure to relatively high doses of ionizing radiation may lead to the accumulation of aberrant cells that are genomically unstable. Understanding radiation effects in terms of coordinated multicellular responses that affect decisions regarding the fate of a cell may necessitate re-evaluation of radiation dose and risk concepts and provide avenues for intervention.

NASA Discipline Radiation Health↗

NASA NTRS2001

Analysis of the myosins encoded in the recently completed Arabidopsis thaliana genome sequence

BACKGROUND: Three types of molecular motors play an important role in the organization, dynamics and transport processes associated with the cytoskeleton. The myosin family of molecular motors move cargo on actin filaments, whereas kinesin and dynein motors move cargo along microtubules. These motors have been highly characterized in non-plant systems and information is becoming available about plant motors. The actin cytoskeleton in plants has been shown to be involved in processes such as transportation, signaling, cell division, cytoplasmic streaming and morphogenesis. The role of myosin in these processes has been established in a few cases but many questions remain to be answered about the number, types and roles of myosins in plants. RESULTS: Using the motor domain of an Arabidopsis myosin we identified 17 myosin sequences in the Arabidopsis genome. Phylogenetic analysis of the Arabidopsis myosins with non-plant and plant myosins revealed that all the Arabidopsis myosins and other plant myosins fall into two groups - class VIII and class XI. These groups contain exclusively plant or algal myosins with no animal or fungal myosins. Exon/intron data suggest that the myosins are highly conserved and that some may be a result of gene duplication. CONCLUSIONS: Plant myosins are unlike myosins from any other organisms except algae. As a percentage of the total gene number, the number of myosins is small overall in Arabidopsis compared with the other sequenced eukaryotic genomes. There are, however, a large number of class XI myosins. The function of each myosin has yet to be determined.

NASA Discipline Plant Biology↗

NASA NTRS1996

Methanococcus jannaschii genome: revisited

Analysis of genomic sequences is necessarily an ongoing process. Initial gene assignments tend (wisely) to be on the conservative side (Venter, 1996). The analysis of the genome then grows in an iterative fashion as additional data and more sophisticated algorithms are brought to bear on the data. The present report is an emendation of the original gene list of Methanococcus jannaschii (Bult et al., 1996). By using a somewhat more updated database and more relaxed (and operator-intensive) pattern matching methods, we were able to add significantly to, and in a few cases amend, the gene identification table originally published by Bult et al. (1996).

Non-NASA Center↗

NASA NTRS1994

Transcription factor IID in the Archaea: sequences in the Thermococcus celer genome would encode a product closely related to the TATA-binding protein of eukaryotes

The first step in transcription initiation in eukaryotes is mediated by the TATA-binding protein, a subunit of the transcription factor IID complex. We have cloned and sequenced the gene for a presumptive homolog of this eukaryotic protein from Thermococcus celer, a member of the Archaea (formerly archaebacteria). The protein encoded by the archaeal gene is a tandem repeat of a conserved domain, corresponding to the repeated domain in its eukaryotic counterparts. Molecular phylogenetic analyses of the two halves of the repeat are consistent with the duplication occurring before the divergence of the archael and eukaryotic domains. In conjunction with previous observations of similarity in RNA polymerase subunit composition and sequences and the finding of a transcription factor IIB-like sequence in Pyrococcus woesei (a relative of T. celer) it appears that major features of the eukaryotic transcription apparatus were well-established before the origin of eukaryotic cellular organization. The divergence between the two halves of the archael protein is less than that between the halves of the individual eukaryotic sequences, indicating that the average rate of sequence change in the archael protein has been less than in its eukaryotic counterparts. To the extent that this lower rate applies to the genome as a whole, a clearer picture of the early genes (and gene families) that gave rise to present-day genomes is more apt to emerge from the study of sequences from the Archaea than from the corresponding sequences from eukaryotes.

NASA Discipline Exobiology↗

NASA NTRS1993

Origins of species: acquired genomes and individuality

Entire genomes with their accompanying protein synthetic systems are transferred throughout the biosphere primarily as bacteria and protists which become symbionts as they irreversibly integrate into pre-existing organisms to form more complex individuals. Individualization is stabilized by simultaneous transmission of once-separate heterologous genetic systems. The origin of new species is hypothesized to correlate with the acquisition, integration and subsequent inheritance of such acquired microbial genomes. These processes were recognized by Mereschkovsky ("Symbiogenesis" in Russian, 1909) and by Wallin ("Symbionticism", see p. 181, this issue).

NASA Discipline Exobiology↗

NASA NTRS2005

Genome-wide transcriptional analysis of flagellar regeneration in Chlamydomonas reinhardtii identifies orthologs of ciliary disease genes

The important role that cilia and flagella play in human disease creates an urgent need to identify genes involved in ciliary assembly and function. The strong and specific induction of flagellar-coding genes during flagellar regeneration in Chlamydomonas reinhardtii suggests that transcriptional profiling of such cells would reveal new flagella-related genes. We have conducted a genome-wide analysis of RNA transcript levels during flagellar regeneration in Chlamydomonas by using maskless photolithography method-produced DNA oligonucleotide microarrays with unique probe sequences for all exons of the 19,803 predicted genes. This analysis represents previously uncharacterized whole-genome transcriptional activity profiling study in this important model organism. Analysis of strongly induced genes reveals a large set of known flagellar components and also identifies a number of important disease-related proteins as being involved with cilia and flagella, including the zebrafish polycystic kidney genes Qilin, Reptin, and Pontin, as well as the testis-expressed tubby-like protein TULP2.

Polycystic Kidney Diseases/genetics↗

NASA NTRSDate not supplied

Determining Chlamydomonas reinhardtii resistance to ionizing radiation at a genome-wide scale

Spaceflight is a complex mixture of abiotic stresses that causes a myriad of cellular responses including increased genome-wide mutation load. The impact of spaceflight on mutation load is not well understood for most organisms and is especially critical to characterize for candidate microorganisms that could be part of biological life support systems. Prior research in our laboratory revealed an unexpectedly high level of mutation during spaceflight in the eukaryotic green algae, C. reinhardtii. Based on the spectrum of base changes observed, we concluded that the mutations were generated through a molecular mechanism unique to the spaceflight environment. Spaceflight is a complex set of stresses, and we are using an Earth-based analog to test ionizing radiation as a potential causative variable for the unique mutation spectrum observed in spaceflight. C. reinhardtii was grown exposed to chronic radiation from a Cesium-137 source. Four biological replicate cultures of wild-type cells were grown in gas permeable plastic tissue culture bags in liquid media following the design used on the International Space Station (ISS) during the previous space algae experiment. Radiation levels for this experiment approximate ionizing radiation observed on the moon, in low Earth orbit (LEO), and on Earth. Cells from each replicate were passaged to inoculate the next cycle of growth, then samples were taken from each culture to characterize cell morphology, quantify biomass, and extract DNA. Whole genome sequencing from each culture will be used to identify the frequency and types of mutations in each radiation level. In growth cycles 3 and 4, there was a significant increase in biomass accumulation under lunar radiation level compared to LEO or Earth radiation levels. These results such that ionizing radiation affected growth of C. reinhardtii.

Microbiology↗

NASA NTRSDate not supplied

Space Algae: Understanding the Genomic Impacts on Microalgae After Growth in the International Space Station

Plants and microbes can be used for biological support of crewed space missions. The radiation and microgravity environment of spaceflight is expected to increase genetic mutation of all organisms. It is essential to understand how spaceflight impacts mutation rates in photosynthetic organisms to enable appropriate countermeasures and ensure productivity during long duration and deep space missions. The Space Algae flight experiments to the International Space Station (ISS) are studying the genomic stability of microalgae that could potentially be used in biological life support systems. Space Algae-1 grew ultraviolet light mutagenized Chlamydomonas reinhardtii in the VEGGIE plant growth chamber for approximately 40 mitotic generations over one month on the ISS. Whole genome sequencing from pooled cell samples every 10 generations revealed that spaceflight cultures had an ~50% increase in DNA polymorphisms relative to ground controls. These mutations had a novel base substitution signature and suggested a risk that microalgae may be unstable for long-term production in space. Space Algae-2 is focusing on the edible cyanobacterium Arthrospira platensis, commonly known as Spirulina. This experiment seeks to grow serial cultures to allow the organism to evolve in long-term spaceflight. Biological responses of the cells to spaceflight will be assessed with multi-omics analyses to determine mutation load, gene/protein expression, metabolic/nutritional composition, and cell morphology.

Algae↗