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At least 163 records · Page 9

Hidden diversity: Transcriptomic and photosynthetic variation among common ‘wild type’ Chlamydomonas strains

The unicellular green alga Chlamydomonas reinhardtii is a widely studied reference organism, particularly in photosynthesis research. It employs photoprotective mechanisms, such as state transitions (ST) and non-photochemical quenching (NPQ), to cope with rapid light changes. Most widely used strains share a recent common ancestor yet differ by up to ~50 000 nuclear variants—genetic diversity that is often overlooked. Even among ‘wild type’ strains, we document significant phenotypic differences, such as pigment accumulation, and nutrient utilization. To elucidate the basis for this variation, we compared transcriptomes and physiological traits of seven commonly used laboratory strains, including the reference strain and the CLiP mutant library parental strain. Despite identical growth conditions, ~40% of genes were differentially expressed between strains. Most of these differences are attributable to changes that have accrued during laboratory propagation, and adverse conditions may have driven transcriptomic drift. At the physiological level, we catalog the range of strain-dependent responses related to photosynthesis and high light (HL) acclimation. Specifically, (i) all strains develop NPQ upon HL exposure, but to various degrees, (ii) they show a substantial variation in ST capacity, and (iii) they regulate the composition of the photosynthetic apparatus differently. We find that NPQ levels do not correlate with LHCSR3 expression, suggesting an additional layer of NPQ regulation. STs are constantly activated and independent of growth light intensities. Overall, our findings highlight significant strain-to-strain differences in virtually all photosynthetic parameters, emphasizing the importance of careful strain selection in future research endeavors.

59 BASIC BIOLOGICAL SCIENCES↗

Microsensor and transcriptomic signatures of oxygen depletion in biofilms associated with chronic wounds: Biofilms and oxygen

Polymicrobial biofilms have been implicated in delayed wound healing, although the mechanisms by which biofilms impair wound healing are poorly understood. Many species of bacteria produce exotoxins and exoenzymes that may inhibit healing. In addition, oxygen consumption by biofilms may impede wound healing. In this study, we used oxygen microsensors to measure oxygen transects through in vitro-cultured biofilms, biofilms formed in vivo in a diabetic (db/db) mouse model, and ex vivo human chronic wound specimens. The results show that oxygen levels within both euthanized and live mouse wounds had steep gradients that reached minima ranging from 19 to 61% oxygen partial pressure, compared to atmospheric oxygen levels. The oxygen gradients in the mouse wounds were similar to those observed for clinical isolates cultured in vitro and for human ex vivo scabs. No oxygen gradients were observed for heat-killed scabs, suggesting that active metabolism by the viable bacteria contributed to the reduced oxygen partial pressure of the wounds. To characterize the metabolic activities of the bacteria in the mouse wounds, we performed transcriptomics analyses of Pseudomonas aeruginosa biofilms associated with the db/db mice wounds using Affymetrix microarrays. The results demonstrated that the bacteria expressed genes for metabolic activities associated with cell growth. Interestingly, the transcriptome results indicated that the bacteria within the wounds also experienced oxygen-limitation stress. Among the bacterial genes that were expressed in vivo were genes associated with the Anr-mediated hypoxia-stress response. Other bacterial stress response genes highly expressed in vivo were genes associated with stationary-phase growth, osmotic stress, and RpoH-mediated heat shock stress. Overall, the results support the hypothesis that the metabolic activities of bacteria in biofilms act as oxygen sinks in chronic wounds and that the depletion of oxygen contributes to the detrimental impact of biofilms on wound healing.

bacterial biofilms↗

Transcriptomic Data Sets for Zymomonas mobilis 2032 during Fermentation of Ammonia Fiber Expansion (AFEX)-Pretreated Corn Stover and Switchgrass Hydrolysates

The transcriptomes of Zymomonas mobilis 2032 were captured during the fermentation of ammonia fiber expansion (AFEX)-pretreated corn stover and switchgrass hydrolysates containing different concentrations of glucose and xylose. RNA samples were collected when Z. mobilis was fermenting glucose or xylose. Here, we present transcriptome sequencing (RNA-Seq) data obtained during separate phases of glucose or xylose consumption.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring phage–host interactions in Burkholderia cepacia complex bacterium to reveal host factors and phage resistance genes using CRISPRi functional genomics and transcriptomics

Complex interactions of bacteriophages with their bacterial hosts determine phage host range and infectivity. While phage defense systems and host factors have been identified in model bacteria, they remain challenging to predict in non-model bacteria. In this paper, we integrate functional genomics and transcriptomics to investigate phage–host interactions, revealing active phage resistance and host factor genes in Burkholderia cenocepacia K56-2. Burkholderia cepacia complex species are commonly found in soil and are opportunistic pathogens in immunocompromised patients. We studied infection of B. cenocepacia K56-2 with Bcep176, a temperate phage isolated from Burkholderia multivorans. A genome-wide dCas9 knockdown library targeting B. cenocepacia K56-2 was constructed, and a pooled infection experiment identified 63 novel genes or operons coding for candidate host factors or phage resistance genes. The activities of a subset of candidate host factor and resistance genes were validated via single-gene knockdowns. Transcriptomics of B. cenocepacia K56-2 during Bcep176 infection revealed that expression of genes coding for host factor and resistance candidates identified in this screen was significantly altered during infection by 4 h post-infection. Identifying which bacterial genes are involved in phage infection is important to understand the ecological niches of B. cenocepacia and its phages, and for designing phage therapies.

Bacterial Pathogenesis↗

Metabolomic and transcriptomic remodeling of bone marrow myeloid cells in response to maternal obesity

Maternal obesity puts the offspring at high risk of developing obesity and cardiometabolic diseases in adulthood. Here, we utilized a mouse model of maternal high-fat diet (HFD)-induced obesity that recapitulates metabolic perturbations seen in humans. We show increased adiposity in the offspring of HFD-fed mothers (Off-HFD) when compared with the offspring of regular diet-fed mothers (Off-RD). We have previously reported significant immune perturbations in the bone marrow of newly weaned Off-HFD. Here, we hypothesized that lipid metabolism is altered in the bone marrow of Off-HFD versus Off-RD. To test this hypothesis, we investigated the lipidomic profile of bone marrow cells collected from 3-week-old Off-RD and Off-HFD. Diacylglycerols (DAGs), triacylglycerols (TAGs), sphingolipids, and phospholipids were remarkably different between the groups, independent of fetal sex. Levels of cholesteryl esters were significantly decreased in Off-HFD, suggesting reduced delivery of cholesterol. These were accompanied by age-dependent progression of mitochondrial dysfunction in bone marrow cells. We subsequently isolated CD11b+ myeloid cells from 3-wk-old mice and conducted metabolomic, lipidomic, and transcriptomic analyses. The lipidomic profiles of myeloid cells were similar to those of bone marrow cells and included increases in DAGs and decreased TAGs. Transcriptomics revealed altered expression of genes related to immune pathways, including macrophage alternative activation, B-cell receptors, and transforming growth factor-β signaling. All told, this study revealed lipidomic, metabolomic, and gene expression abnormalities in bone marrow cells broadly, and in bone marrow myeloid cells particularly, in the newly weaned offspring of mothers with obesity, which might at least partially explain the progression of metabolic and cardiovascular diseases in their adulthood.

RNA sequencing↗

divergence in basal transcriptomes of "Wild Type" Chlamydomonas reinhardtii strains

This is a study to compare the basal transcriptomes of several widely used laboratory strains of the Chlorophyte alga, Chlamydomonas reinhardtii. Given that there is a high degree of genetic diversity among the closely-related laboratory strains, we wished to examine how much variation there is at the transcriptome level. A panel of WT strains (CC-124, CC-125, CC-1009, CC-1690, CC-1691), all believed to be descended from a single zygospore isolated in 1945, were chosen based on their representing the oldest lineages among the standard laboratory strains. Additionally, CC-4532, which was the source for the current (v6) reference assembly, and CC-4533, which is the initial parental strain of the CLiP library collection of mutant strains, were also included in this study based on their significance to the Chlamydomonas community. All strains were grown in liquid cultures under identical, mixotrophic conditions (light + acetate) to mid-log phase before collecting mRNA for RNA-Seq analysis. Overall design: Pre-cultures of each strain (CC-124, CC-125, CC-1009, CC-1690, CC-1691, CC-4532, and CC-4533) were used to innoculate flasks of Tris-Acetate-Phosphate (TAP) media supplemented with Kropat's trace metals at a concentration of 1.5 x 10^4 cells/mL. Flasks were placed on a shaking platform at 180 RPM under 50-70 µmol x m^-2 x s^-1 of light. Cultures were grown until they reached ~2-3 x 10^6 cells/mL, about three days, before total RNA was collected and subjected RNA-Seq analysis.

Source record↗

Unique aspects of fiber degradation by the ruminal ethanologen Ruminococcus albus 7 revealed by physiological and transcriptomic analysis

Bacteria in the genus Ruminococcus are ubiquitous members of the mammalian gastrointestinal tract. In particular, they are important in ruminants where they digest a wide range of plant cell wall polysaccharides. For example, Ruminococcus albus 7 is a primary cellulose degrader that produces acetate usable by its bovine host. Moreover, it is one of the few organisms that ferments cellulose to form ethanol at mesophilic temperatures in vitro . The mechanism of cellulose degradation by R. albus 7 is not well-defined and is thought to involve pilin-like proteins, unique carbohydrate-binding domains, a glycocalyx, and cellulosomes. We used a combination of comparative genomics, fermentation analyses, and transcriptomics to further clarify the cellulolytic and fermentative potential of R. albus 7 . A comparison of the R. albus 7 genome sequence against the genome sequences of related bacteria that either encode or do not encode cellulosomes revealed that R. albus 7 does not encode for most canonical cellulosomal components. Fermentation analysis of R. albus 7 revealed the ability to produce ethanol and acetate on a wide range of fibrous substrates in vitro . Global transcriptomic analysis of R. albus 7 grown at identical dilution rates on cellulose and cellobiose in a chemostat showed that this bacterium, when growing on cellulose, utilizes a carbohydrate-degrading strategy that involves increased transcription of the rare carbohydrate-binding module (CBM) family 37 domain and the tryptophan biosynthetic operon. Our data suggest that R. albus 7 does not use canonical cellulosomal components to degrade cellulose, but rather up-regulates the expression of CBM37-containing enzymes and tryptophan biosynthesis. This study contributes to a revised model of carbohydrate degradation by this key member of the rumen ecosystem.

09 BIOMASS FUELS↗

Niche-DE: niche-differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions

Existing methods for analysis of spatial transcriptomic data focus on delineating the global gene expression variations of cell types across the tissue, rather than local gene expression changes driven by cell-cell interactions. We propose a new statistical procedure called niche-differential expression (niche-DE) analysis that identifies cell-type-specific niche-associated genes, which are differentially expressed within a specific cell type in the context of specific spatial niches. We further develop niche-LR, a method to reveal ligand-receptor signaling mechanisms that underlie niche-differential gene expression patterns. Niche-DE and niche-LR are applicable to low-resolution spot-based spatial transcriptomics data and data that is single-cell or subcellular in resolution.

59 BASIC BIOLOGICAL SCIENCES↗

Assembled genomic and tissue-specific transcriptomic data resources for two genetically distinct lines of Cowpea (Vigna unguiculata (L.) Walp)

Cowpea (Vigna unguiculata (L.) Walp) is an important legume crop for food security in areas of low-input and smallholder farming throughout Africa and Asia. Genetic improvements are required to increase yield and resilience to biotic and abiotic stress and to enhance cowpea crop performance. An integrated cowpea genomic and gene expression data resource has the potential to greatly accelerate breeding and the delivery of novel genetic traits for cowpea. Extensive genomic resources for cowpea have been absent from the public domain; however, a recent early release reference genome for IT97K-499-35 (Vigna unguiculata v1.0, NSF, UCR, USAID, DOE-JGI, http://phytozome.jgi.doe.gov/) has now been established in a collaboration between the Joint Genome Institute (JGI) and University California (UC) Riverside. Here we release supporting genomic and transcriptomic data for IT97K-499-35 and a second transformable cowpea variety, IT86D-1010. The transcriptome resource includes six tissue-specific datasets for each variety, with particular emphasis on reproductive tissues that extend and support the V. unguiculata v1.0 reference. Annotations have been included in our resource to allow direct mapping to the v1.0 cowpea reference. Access to this resource provided here is supported by raw and assembled data downloads.

Spriggs, Andrew↗

Inference of Causal Networks from Time-Varying Transcriptome Data via Sparse Coding

Temporal analysis of genome-wide data can provide insights into the underlying mechanism of the biological processes in two ways. First, grouping the temporal data provides a richer, more robust representation of the underlying processes that are co-regulated. The net result is a significant dimensional reduction of the genome-wide array data into a smaller set of vocabularies for bioinformatics analysis. Second, the computed set of time-course vocabularies can be interrogated for a potential causal network that can shed light on the underlying interactions. The method is coupled with an experiment for investigating responses to high doses of ionizing radiation with and without a small priming dose. From a computational perspective, inference of a causal network can rapidly become computationally intractable with the increasing number of variables. Additionally, from a bioinformatics perspective, larger networks always hinder interpretation. Therefore, our method focuses on inferring the simplest network that is computationally tractable and interpretable. The method first reduces the number of temporal variables through consensus clustering to reveal a small set of temporal templates. It then enforces simplicity in the network configuration through the sparsity constraint, which is further regularized by requiring continuity between consecutive time points. We present intermediate results for each computational step, and apply our method to a time-course transcriptome dataset for a cell line receiving a challenge dose of ionizing radiation with and without a prior priming dose. Our analyses indicate that (i) the priming dose increases the diversity of the computed templates (e.g., diversity of transcriptome signatures); thus, increasing the network complexity; (ii) as a result of the priming dose, there are a number of unique templates with delayed and oscillatory profiles; and (iii) radiation-induced stress responses are enriched through pathway and subnetwork studies.

59 BASIC BIOLOGICAL SCIENCES↗

Use of a Capture-Based Pathogen Transcript Enrichment Strategy for RNA-Seq Analysis of the Francisella Tularensis LVS Transcriptome during Infection of Murine Macrophages

Francisella tularensis is a zoonotic intracellular pathogen that is capable of causing potentially fatal human infections. Like all successful bacterial pathogens, F. tularensis rapidly responds to changes in its environment during infection of host cells, and upon encountering different microenvironments within those cells. This ability to appropriately respond to the challenges of infection requires rapid and global shifts in gene expression patterns. In this study, we use a novel pathogen transcript enrichment strategy and whole transcriptome sequencing (RNA-Seq) to perform a detailed characterization of the rapid and global shifts in F. tularensis LVS gene expression during infection of murine macrophages. We performed differential gene expression analysis on all bacterial genes at two key stages of infection: phagosomal escape, and cytosolic replication. By comparing the F. tularensis transcriptome at these two stages of infection to that of the bacteria grown in culture, we were able to identify sets of genes that are differentially expressed over the course of infection. This analysis revealed the temporally dynamic expression of a number of known and putative transcriptional regulators and virulence factors, providing insight into their role during infection. In addition, we identified several F. tularensis genes that are significantly up-regulated during infection but had not been previously identified as virulence factors. These unknown genes may make attractive therapeutic or vaccine targets.

59 BASIC BIOLOGICAL SCIENCES↗

Parallel measurement of transcriptomes and proteomes from same single cells using nanodroplet splitting

Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. While tools for co-profiling single-cell genomes, transcriptomes, and epigenomes are available, accessing proteomes in parallel is more challenging. We developed nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single cells using RNA sequencing and mass spectrometry-based proteomics, respectively. nanoSPLITS can precisely quantify over 5000 genes, 2000 proteins, and 140 phosphopeptides per single cell and identify candidate cell markers from these modalities. By exploring Cdk1-mediated cell cycle arrest, we demonstrate how nanoSPLITS single-cell multiomics can provide comprehensive cellular characterization with insights into covarying protein/gene clusters, unique phosphorylation events, and mitotic pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Effective Mechanisms for Improving Seed Oil Production in Pennycress (Thlaspi arvense L.) Highlighted by Integration of Comparative Metabolomics and Transcriptomics

Pennycress is a potentially lucrative biofuel crop due to its high content of long-chain unsaturated fatty acids, and because it uses non-conventional pathways to achieve efficient oil production. However, metabolic engineering is required to improve pennycress oilseed content and make it an economically viable source of aviation fuel. Research is warranted to determine if further upregulation of these non-conventional pathways could improve oil production within the species even more, which would indicate these processes serve as promising metabolic engineering targets and could provide the improvement necessary for economic feasibility of this crop. To test this hypothesis, we performed a comparative biomass, metabolomic, and transcriptomic analyses between a high oil accession (HO) and low oil accession (LO) of pennycress to assess potential factors required to optimize oil content. An evident reduction in glycolysis intermediates, improved oxidative pentose phosphate pathway activity, malate accumulation in the tricarboxylic acid cycle, and an anaplerotic pathway upregulation were noted in the HO genotype. Additionally, higher levels of threonine aldolase transcripts imply a pyruvate bypass mechanism for acetyl-CoA production. Nucleotide sugar and ascorbate accumulation also were evident in HO, suggesting differential fate of associated carbon between the two genotypes. An altered transcriptome related to lipid droplet (LD) biosynthesis and stability suggests a contribution to a more tightly-packed LD arrangement in HO cotyledons. In addition to the importance of central carbon metabolism augmentation, alternative routes of carbon entry into fatty acid synthesis and modification, as well as transcriptionally modified changes in LD regulation, are key aspects of metabolism and storage associated with economically favorable phenotypes of the species.

59 BASIC BIOLOGICAL SCIENCES↗

Rhythmic Mechanisms Governing CAM Photosynthesis in Kalanchoe fedtschenkoi : High-Resolution Temporal Transcriptomics

Crassulacean acid metabolism (CAM) is a specialized photosynthetic pathway that enhances water-use efficiency by temporally separating nocturnal CO 2 uptake from daytime decarboxylation and carbon fixation. To uncover the regulatory mechanisms coordinating these temporal dynamics, we generated high-resolution, 48 h time-course transcriptomes for the CAM model Kalanchoe fedtschenkoi under both 12 h/12 h light/dark (LD) cycles and continuous light (LL). A rhythmicity analysis revealed that diel light cues are the dominant driver of transcript oscillations: 16,810 genes (54.3% of annotated genes) exhibited rhythmic expression only under LD, whereas just 399 genes (1.3%) remained rhythmic under LL. A smaller set of 3009 genes (9.7%) oscillated in both conditions, indicating that the intrinsic circadian clock sustains rhythmicity for a limited subset of the transcriptome. A gene co-expression network analysis revealed extensive integration between circadian clock components, core CAM pathway enzymes, and stomatal regulators, defining regulatory modules that coordinate metabolic and physiological timing. Notably, key hub genes associated with post-translational and post-transcriptional regulation, including the E3 ubiquitin ligase HUB2 and several pentatricopeptide repeat (PPR) proteins, act as central nodes in CAM-associated networks. This discovery implicates epigenetic and organellar regulation as previously unrecognized critical tiers of control in CAM. Together, our results support a regulatory model in which CAM rhythmicity is governed by both external light/dark cues and the endogenous circadian clock through multi-level control spanning transcriptional and protein-level regulation. To support community exploration, we also provide an interactive eFP (electronic Fluorescent Pictograph) browser for visualizing time-resolved gene expression profiles.

09 BIOMASS FUELS↗

The stem cell-type transcriptome of bioenergy sorghum reveals the spatial regulation of secondary cell wall networks

Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type.

cell specificity↗

Space Biofilms - Phenotypic and Transcriptomic Behaviour of Pseudomonas Aeruginosa Biofilms on Board the International Space Station

Bacterial biofilms in space can have a positive or negative impact on the success of a mission. For example, in some instances, biofilms can improve plant growth, facilitate synthesis/recovery of metals from regolith, or bioremediate wastewater. On the other hand, biofilms can deteriorate or cause malfunctions of spaceflight hardware. Biofilms have been found on the wastewater tank of the Environmental Control and Life Support System (ECLSS), which poses a risk to the system. Even more alarming, some biofilms cause infections that may threaten astronauts’ health, like urinary tract infections that if left unclear could cause permanent damage to the kidneys. Given that biofilms can contribute to or hinder the efforts of space exploration, it is necessary to understand the effects of microgravity on biofilm behaviour. The Space Biofilms experiment intends to contribute to such understanding by analysing the morphology and transcriptomic profiles of Pseudomonas aeruginosa PA14 biofilms grown in spaceflight compared to matched ground controls. P. aeruginosa biofilms were grown onboard the International Space Station for 1, 2, or 3 days at 37°C over six surface materials: Stainless Steel 316 (SS316), passivated SS316, and a novel Lubricant Impregnated Surface (LIS) were grown in rich media supplemented with potassium nitrate (LBK) to simulate wastewater. While cellulose membrane, catheter grade silicone, and silicone with special nanotopography (DLIP) were grown in modified Artificial Urine Media supplemented with glucose and high phosphate (mAUMg-hi Pi) to simulate urine. Asynchronous ground controls replicated spaceflight procedures. Morphology analysis revealed that flight samples had a significant decrease in mass, thickness and surface area coverage in LBK. Additionally, biofilm surface coverage on LIS was only 11% of the equivalent samples on SS316 (p<0.001). Associated preliminary transcriptomic data will also be addressed.

Pamela Flores↗

Transcriptomic Changes in Seedlings from Seeds Exposed to Simulated Space Radiation

Outside the protection of Earth’s magnetic field, living organisms are constantly exposed to space radiation that consists of energetic protons and other heavier charged particles. With the goal of manned Mars exploration, the production of fresh crop during long duration space missions can be beneficial for meeting astronauts’ nutritional and psychological needs. In our study, we not only evaluated plant/fruit morphometrics and edible fresh mass, but also analyzed transcriptomic changes in seedlings from seeds of three plant species (Arabidopsis, mizuna, and tomato) exposed to simulated Galactic Cosmic Rays(GCR) and solar particle events(SPE). The radiation experiments were performed in the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). 10-day Arabidopsis seedlings were exposed acutely (~240 cGy/hr) to simulated GCR scenarios of combined ions including protons, helium, oxygen, titanium, and/or iron ions at 40 or 80 cGy. Seeds of Arabidopsis, mizuna, and tomato were exposed to 40 or 80 cGy simulated GCR (dry seeds) or SPE (imbibed seeds) at lower dose rates(20-26 cGy/hr). Seedlings from control and irradiated seeds were then collected in RNAlater at similar growth stages with true leaves emerged. Total RNA was isolated and analyzed via Illumina whole transcriptome sequencing technology. Plant species-specific bioinformatics revealed transcriptional biomarkers and signaling pathways induced by simulated space radiation that were found to be dose, dose-rate, and species dependent. DNA damage response, stress signaling, and metabolic pathways are among the most significant changes. These data highlight some critical insights on the mechanisms of how plants respond and adapt to the space radiation environment and provide a molecular basis for crop selection and refinement in deep space exploration.

Anirudha Dixit↗