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At least 145 records · Page 8

Translational Line of Sight: a multi-omics longitudinal study of the murine retinal response to spaceflight hazard analogs

The space environment includes unique hazards like radiation and microgravity which adversely affect physiology and behavior of humans and rodent models. To better characterize the retinal response to spaceflight, we assessed a multi-omics NASA GeneLab dataset where 6-month-old female mice were gamma irradiated and/or hindlimb unloaded for 21 days followed by whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of retina samples collected at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles revealing a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation differences was seen across different conditions at the same time point (e.g., between radiation exposure and hindlimb unloaded at 7 days). Biological processes related to nucleotide metabolism were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. Interestingly, Notch3 and Lrg1 showed differential patterns in the NASA Twins Study in-flight samples and in response to stressors in the murine retina in the current study. A total of 23 genes were both differentially methylated and expressed, including genes involved in retinal disease or cataract development (Crybb3, Fgfr1, Pitpnm3, Sipa1l3, Sox9) and inflammatory response (B4galt6, Ppm1a, Sphk1). To our knowledge, the current multi-omics analysis is the first multi-omics study to interrogate the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination. The results provide an insight into the retinal response to individual spaceflight hazard analogs and their interplay at different post-exposure stages and contributes towards a mechanistic understanding of spaceflight-induced vision impairment using ground-based models.

Prachi Kothiyal

MULTI-OMICS ANALYSIS OF THE IMPACT OF CHRONIC LOW-DOSE RADIATION AND HINDLIMB SUSPENSION ON MURINE BRAIN AND RETINA

The space environment includes hazards like radiation and microgravity which can adversely affect biological systems. We assessed multi-omics multi-tissue NASA GeneLab datasets where 6-month-old female mice were gamma irradiated (IR) and/or hindlimb unloaded (HLU) for 21 days. Whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of brain and retina samples collected at 4 months post-exposure was performed to better characterize the retinal and neurological responses to spaceflight. We compared epigenomic and transcriptomic profiles within each exposure group for both tissue types to identify correlation (Pearson’s correlation test; p-value < 0.05) between gene expression and DNA methylation levels that may be related to transcriptional regulation. We then obtained genes with methylation-expression correlation that also showed differences in mean expression or dispersion between exposed and control groups (adjusted p-value < 0.25; relaxed to denote ‘hypothesis’) in the brain (37 genes in HLU, 4 in IR, and 156 in HLU+IR) or retina (92 genes in HLU, 1 in IR, and 55 in HLU+IR). Enriched Gene Ontology (GO) terms for these genes are listed in Table 1 for HLU and HLU+IR for both tissue types. No enriched terms and only a few genes were detected with IR-only exposure in the brain (Chmp1a, Limd1, Rab40b, Ubc) and retina (retinoblastoma binding protein Rbbp7). Cellular components related to synapse were enriched in both tissue types. Previous analysis of differentially expressed genes in the retina after 1 month of HLU+IR showed enrichment in the somatodendritic compartment of the neuron, which was also observed in the brain 4 months post-exposure. Interestingly, genes related to ubiquitination showed correlation between methylation and expression and were differentially expressed or dispersed in different exposure groups indicating that this pathway may play an important role in multi-stressor response (Figure 1). The current multi-omics and multi-tissue analysis interrogates the epigenomic and transcriptomic impacts of radiation and hindlimb unloading, in isolation and in combination, on the retina and the brain. The results provide insight into the adaptive response to individual spaceflight hazard analogs and their interplay, as well as hypotheses to be further tested for understanding spaceflight-induced neurological and vision effects.

Prachi Kothiyal

A Multi-omics Longitudinal Study of the Murine Retinal Response to Chronic Low-dose Irradiation and/or Simulated Microgravity

The space environment includes unique hazards like radiation and microgravity which adversely affect physiology and behavior of humans and rodent models. To better characterize the retinal response to spaceflight, we assessed a multi-omics NASA GeneLab dataset where 6-month-old female mice were gamma irradiated and/or hindlimb unloaded for 21 days followed by whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of retina samples collected at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles revealing a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation differences was seen across different conditions at the same time point (e.g., between radiation exposure and hindlimb unloaded at 7 days). Biological processes related to nucleotide metabolism were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. Interestingly, Notch3 and Lrg1 showed differential patterns in the NASA Twins Study in-flight samples and in response to stressors in the murine retina in the current study. A total of 23 genes were both differentially methylated and expressed, including genes involved in retinal disease or cataract development (Crybb3, Fgfr1, Pitpnm3, Sipa1l3, Sox9) and inflammatory response (B4galt6, Ppm1a, Sphk1). To our knowledge, the current multi-omics analysis is the first multi-omics study to interrogate the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination. The results provide an insight into the retinal response to individual spaceflight hazard analogs and their interplay at different post-exposure stages and contributes towards a mechanistic understanding of spaceflight-induced vision impairment using ground-based models.

Prachi Kothiyal

Nutrient Limitation Predisposes A Cultivate of Burkholderia Contaminans From the ISS Water Processor Assembly to Biofilm Formation Under Simulated Microgravity.

The International Space Station (ISS) Water Processor Assembly (WPA) experiences intermittent dormancy between water recycling events thus promoting biofilm formation within the system. In this work we aimed to gain a deeper understanding of the impact of nutrient limitation on bacterial growth and biofilm formation under microgravity in support of biofilm mitigation efforts in exploration water recovery systems. A representative species of bacteria that is commonly cultured from the ISS WPA was cultured in an WPA influent water ersatz formulation tailored for microbiology studies. Burkholderia contaminans was cultured under a simulated microgravity (SµG) treatment in a vertically rotating high-aspect rotating vessel (HARV), with a rotating control (R) in the horizontal plane at the determined optimal rpm of 15 along with a stationary (S) control. At different time points, the bacterial culture and ersatz were harvested for bacterial counts, transcriptomic and nutrient content analyses. Under the test conditions, the culture under SµG treatment consumed the essential nutrients faster than the R and S control cultures in the early stage of growth, thus approaching a nutrient limited growth condition earlier than the controls. The rapid uptake and subsequent depletion of essential nutrients was further illustrated in the transcriptomic response of the SµG culture when compared to the transcriptomic response of the R and S control conditions. The observed starvation response may serve as one element to explain a moderate enhancement of biofilm formation in the SµG treatment. One implication of this investigation is that biofilm mitigation in the ISS environment could be supported by ensuring a steady flow of water as a vehicle for essential nutrients within the WPA to avoid complete consumption which occurs in times of no flow lending to undesired biofilm formation.

Angie Diaz

Cardiovascular Responses to Simulated Spaceflight: Molecular Signatures and Surrogate Outputs to Measure CVD Risk

During extended space missions beyond low Earth orbit, astronauts will encounter prolonged periods of weightlessness and low dose space radiation. Previous studies have shown that exposure to small doses of high LET radiation (< 50 cGy) can lead to both short-term and long-term alterations in heart function, structure and underlying molecular mechanisms. In this study, we aim to identify the molecular signature associated with the cardiovascular response to simulated galactic cosmic radiation (5-ion GCR) alone or in combination with simulated weightlessness at time intervals relevant to mission length and recovery. Additionally, we aim to determine whether sex impacts cardiovascular responses to these spaceflight factors. Our overarching goal is to enhance our understanding of the cardiovascular risks associated with extended space missions and the clinical endpoints they suggest. We hypothesize that exposure to simulated space radiation leads to enduring alterations in the transcriptome, redox signaling and cytokine environment of cardiovascular tissue, some which have known links with reduced cardiovascular performance, aging, and increased risk of cardiovascular disease (CVD). Furthermore, we posit that simulated space radiation exposure in combination with simulated microgravity exacerbates cardiovascular deficits compared to single factor exposure. Female and male C57BL/6J mice, aged 23-24 weeks, were exposed to a single dose of 5, 15, or 50 cGy of 5-ion GCR, or sham-treated (0 cGy). Euthanasia was performed at 14 days and ~4 months post-irradiation. Hearts, aorta and blood plasma were collected shortly thereafter. RNA-sequencing of left ventricles at ~4 months post-GCR exposure revealed sex differences in the heart transcriptome with a few genes showing radiation-dependent changes in expression levels. Notably, some of the differentially expressed genes in 15 and 50 cGy GCR groups are known to play roles in the development of CVD. Analysis of protein levels of a subset of inflammatory cytokines in the heart indicated sex differences but no differences between sham and 50 cGy groups. Results also showed correlations among differentially expressed genes and a subset of inflammatory cytokines, with some correlations altered by GCR exposure. These findings suggest that GCR exposure can modify protein and gene networks linked to inflammation and CVD progression. In the aorta, telomere lengths were comparable across treatment groups sexes. Mitochondrial copy number is a biomarker for mitochondrial function with decreased copy numbers associated with cardiometabolic disease traits. Mitochondrial copy numbers of aorta also showed no sex nor dose differences. In a second study, mice underwent one week of simulated microgravity by hindlimb unloading (HU) and then exposed to a single dose of 15 cGy of 5-ion GCR. HU was conducted for an additional two weeks following GCR exposure. Single factor exposure groups (HU or GCR only) also were included in the study. Euthanasia was then performed and the same tissues were collected. Protein levels of select inflammatory cytokines in the heart showed sex-dependent differences in expression. In the aorta, telomere lengths and mitochondrial copy number also showed sex differences. In summary, our results indicate differences between sexes in biomarkers related to cardiovascular health. Exposure to 5-ion GCR or HU, alone or in combination, did not result in changes in most of the cardiovascular biomarkers that were examined. However, in the heart, simulated space radiation at doses of 15 and 50 cGy led to long-term alterations in the expression levels of a small group of genes known to be associated with the progression of CVD. The long-term transcriptomic changes resulting from exposure to simulated space radiation should be carefully investigated to mitigate adverse cardiovascular events during and after deep space missions. Our results also highlight the importance of sex-specific strategies in monitoring and maintaining cardiovascular health during and after deep space missions.

cardiovascular

Data for Sugar Accumulation Enhancement in Sorghum Stem is Associated with Reduced Reproductive Sink Strength and Increased Phloem Unloading Activity

Sweet sorghum has emerged as a promising source of bioenergy mainly due to its high biomass and high soluble sugar yield in stems. Studies have shown that loss-of-function Dry locus alleles have been selected during sweet sorghum domestication, and decapitation can further boost sugar accumulation in sweet sorghum, indicating that the potential for improving sugar yields is yet to be fully realized. To maximize sugar accumulation, it is essential to gain a better understanding of the mechanism underlying the massive accumulation of soluble sugars in sweet sorghum stems in addition to the Dry locus. We performed a transcriptomic analysis upon decapitation of near-isogenic lines for mutant (d, juicy stems, and green leaf midrib) and functional (D, dry stems and white leaf midrib) alleles at the Dry locus. Our analysis revealed that decapitation suppressed photosynthesis in leaves, but accelerated starch metabolic processes in stems. SbbHLH093 negatively correlates with sugar levels supported by genotypes (DD vs. dd), treatments (control vs. decapitation), and developmental stages post anthesis (3d vs.10d). D locus gene SbNAC074A and other programmed cell death-related genes were down regulated by decapitation, while sugar transporter-encoding gene SbSWEET1A was induced. Both SbSWEET1A and Invertase 5 were detected in phloem companion cells by RNA in situ assay. Loss of the SbbHLH093 homolog, AtbHLH093, in Arabidopsis led to a sugar accumulation increase. This study provides new insights into sugar accumulation enhancement in bioenergy crops, which can be potentially achieved by reducing reproductive sink strength and enhancing phloem unloading.

Transcriptomics

Carbon source-induced changes in the transcriptional landscape of Novacetimonas hansenii

Novacetimonas hansenii is a model organism for bacterial cellulose (BC) production, a biopolymer with broad industrial applications. To better understand its carbon source-dependent metabolism, we conducted the first time-resolved transcriptomic analysis of N. hansenii ATCC 23769 grown on five carbon sources (glucose, fructose, mannitol, galactose, and sucrose) across five time points (24–120h). Glucose, fructose, and mannitol supported growth and efficient BC production, whereas galactose and sucrose resulted in poor yields, likely due to limited transport and enzymatic capacity. Solid-state NMR revealed that cellulose crystallinity and polymorphism were carbon source-dependent, with reduced bcsD expression correlating with lower crystallinity. Transcriptomic profiling showed distinct metabolic responses. Cultures containing glucose and mannitol activated core metabolic pathways, fructose induced a delayed adaptive shift, and galactose and sucrose triggered stress-related gene expression. These results highlight the metabolic plasticity of N. hansenii and offer insights for enhancing BC production through carbon source optomization.

Bacterial cellulose

A network-enabled pipeline for gene discovery and validation in non-model plant species

Identifying key regulators of important genes in non-model crop species is challenging due to limited multi-omics resources. To address this, we introduce the network-enabled gene discovery pipeline NEEDLE, a user-friendly tool that systematically generates coexpression gene network modules, measures gene connectivity, and establishes network hierarchy to pinpoint key transcriptional regulators from dynamic transcriptome datasets. After validating its accuracy with two independent datasets, we applied NEEDLE to identify transcription factors (TFs) regulating the expression of cellulose synthase-like F6 ( CSLF6 ), a crucial cell wall biosynthetic gene, in Brachypodium and sorghum. Our analyses uncover regulators of CSLF6 and also shed light on the evolutionary conservation or divergence of gene regulatory elements among grass species. These results highlight NEEDLE’s capability to provide biologically relevant TF predictions and demonstrate its value for non-model plant species with dynamic transcriptome datasets.

59 BASIC BIOLOGICAL SCIENCES

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics

Integrative analysis of CAM photosynthesis reveals its impact on primary metabolism in Yucca

Crassulacean Acid Metabolism (CAM) is an adaptation that temporally separates carbon uptake at night from photosynthesis during the day. CAM has evolved repeatedly across vascular plants, as its emergence may depend on simple regulatory changes to deeply conserved metabolic pathways. Modern CAM research relies heavily on interpretation of transcriptomic data, though regulation occurs at multiple levels following transcription. Additionally, while most research to date has focused on a handful of genes and metabolites in the core CAM pathway, the co-option of conserved regulatory and functional genes is bound to have wide-ranging effects on other aspects of primary metabolism. In this study, we integrate transcriptomic, proteomic, and metabolomic data to compare primary metabolism between the CAM species Yucca aloifolia and closely related C 3 species, Y. filamentosa. We observe minimal correlation between protein abundance and mRNA expression, suggesting significant post-transcriptional regulation in CAM species. We also find evidence of shifts in gene expression and metabolite accumulation outside of the central CAM pathway, suggesting that the shift to CAM has cascading effects across primary metabolism, especially nitrogen metabolism. Our findings provide insights into the metabolic shifts associated with CAM evolution, and highlight the complexity of its regulation at multiple biological levels.

59 BASIC BIOLOGICAL SCIENCES

Evidence for autotrophic growth of purple sulfur bacteria using pyrite as electron and sulfur source

ABSTRACT Purple sulfur bacteria (PSB) are capable of anoxygenic photosynthesis via oxidizing reduced sulfur compounds and are considered key drivers of the sulfur cycle in a range of anoxic environments. In this study, we show that Allochromatium vinosum (a PSB species) is capable of autotrophic growth using pyrite as the electron and sulfur source. Comparative growth profile, substrate characterization, and transcriptomic sequencing data provided valuable insight into the molecular mechanisms underlying the bacterial utilization of pyrite and autotrophic growth. Specifically, the pyrite-supported cell cultures (“py”’) demonstrated robust but much slower growth rates and distinct patterns from their sodium sulfide-amended positive controls. Up to ~200-fold upregulation of genes encoding various c - and b -type cytochromes was observed in “py,” pointing to the high relevance of these molecules in scavenging and relaying electrons from pyrite to cytoplasmic metabolisms. Conversely, extensive downregulation of genes related to LH and RC complex components indicates that the electron source may have direct control over the bacterial cells’ photosynthetic activity. In terms of sulfur metabolism, genes encoding periplasmic or membrane-bound proteins (e.g., FccAB and SoxYZ) were largely upregulated, whereas those encoding cytoplasmic proteins (e.g., Dsr and Apr groups) are extensively suppressed. Other notable differentially expressed genes are related to flagella/fimbriae/pilin(+), metal efflux(+), ferrienterochelin(−), and [NiFe] hydrogenases(+). Characterization of the biologically reacted pyrite indicates the presence of polymeric sulfur. These results have, for the first time, put the interplay of PSB and transition metal sulfide chemistry under the spotlight, with the potential to advance multiple fields, including metal and sulfur biogeochemistry, bacterial extracellular electron transfer, and artificial photosynthesis. IMPORTANCE Microbial utilization of solid-phase substrates constitutes a critical area of focus in environmental microbiology, offering valuable insights into microbial metabolic processes and adaptability. Recent advancements in this field have profoundly deepened our knowledge of microbial physiology pertinent to these scenarios and spurred innovations in biosynthesis and energy production. Furthermore, research into interactions between microbes and solid-phase substrates has directly linked microbial activities to the surrounding mineralogical environments, thereby enhancing our understanding of the relevant biogeochemical cycles. Our study represents a significant step forward in this field by demonstrating, for the first time, the autotrophic growth of purple sulfur bacteria using insoluble pyrite (FeS2) as both the electron and sulfur source. The presented comparative growth profiles, substrate characterizations, and transcriptomic sequencing data shed light on the relationships between electron donor types, photosynthetic reaction center activities, and potential extracellular electron transfer in these organisms capable of anoxygenic photosynthesis. Furthermore, the findings of our study may provide new insights into early-Earth biogeochemical evolutions, offering valuable constraints for understanding the environmental conditions and microbial processes that shaped our planet’s history.

59 BASIC BIOLOGICAL SCIENCES

Cell Population–resolved Multiomics Atlas of the Developing Lung

The lung is a vital organ that undergoes extensive morphological and functional changes during postnatal development. To disambiguate how different cell populations contribute to organ development, we performed proteomic and transcriptomic analyses of four sorted cell populations from the lung of human subjects aged 0 to 8 years-old with a focus on early life. The cell populations analyzed included epithelial, endothelial, mesenchymal, and immune cells. Our results revealed distinct molecular signatures for each of the sorted cell populations that enable the description of molecular shifts occurring in these populations during post-natal development. Here, we confirmed that the proteome of the different cell populations was distinct regardless of age and identified functions specific to each population. We identified a series of cell population protein markers, including those located at the cell surface, that show differential expression and distribution on RNA in situ hybridization and immunofluorescence imaging. We validated the spatial distribution of AT1 and endothelial cell surface markers. Temporal analyses of the proteome of each of the four populations revealed processes modulated during postnatal development and disambiguating results obtained on whole tissue proteome. Finally, the proteome was compared to a transcriptomics survey performed on the same lung samples to evaluate processes under post-transcriptional control.

59 BASIC BIOLOGICAL SCIENCES

Discovering Innovations in Stress Tolerance through Comparative Gene Regulatory Network Analysis and Cell-Type Specific Expression Maps (Final Technical Report with Cover Page)

Through this grant, we developed a comparative framework to elucidate the mechanisms behind variations in environmental stress responses among a diverse group of species within the Brassicaceae family. Our focus was on the differences in physiological and transcriptomic responses to abscisic acid (ABA), a hormone associated with water stress. We examined the differential growth responses of four Brassicaceae species, finding that most exhibited reduced root growth correlated with smaller meristem size. In contrast, Schrenkiella parvula showed accelerated growth due to increased root cell elongation. We employed RNA sequencing to analyze the transcriptional responses to ABA across these species, and innovative bioinformatics techniques were used to pinpoint biological pathways with significant divergence. Additionally, we utilized DAP-seq to map the gene regulatory networks associated with ABAresponsive transcription factors, revealing that variations in the regulation of growth hormone biosynthesis play a critical role in the distinct ABA effects on root growth among the species. This research sets a new standard for comparative physiology by integrating comparative genomics and transcriptomics to uncover pathway divergences.

59 BASIC BIOLOGICAL SCIENCES

GeneLab for High Schools – Bioinformatic Training For Students And Educators

Modern biological sciences are increasingly based on high-throughput molecular techniques, including genomics, transcriptomics, and proteomics. NASA’s GeneLab program has collected extensive data from ‘omics’ studies, curated them into an accessible platform and provided data analysis/visualization tools to facilitate the generation of new hypotheses and research directions. GeneLab for High Schools (GL4HS), launched in 2017, has endeavored to utilize this database and provide tools for students to understand and analyze omics datasets whilst also learning about spaceflight research. The GL4HS program ran in person at Ames from 2017-2019 and has run virtually since 2020. Each year fifteen high school students are trained to analyze and interpret GeneLab transcriptomic data. Additionally, in the last several years we have expanded our “teacher training program” to include 10 teachers total in an effort to enable this program to be utilized in classrooms across the USA. Teachers also join the NASA GeneLab Education Working Group (EWG) enabling support as they implement custom GL4HS modules into their classrooms. The GL4HS program consists of three main components – (1) core learning modules, (2) networking and teamwork, and (3) an independent learning project. Students are also taught critical networking and science communication skills facilitating their ability to ‘sell their science’ in innovative and creative ways. This program has enabled students to learn about biology in space and to have a glimpse into the world of research for the first time. Many of the students in this program shared that the course was transformative to their perception about biological sciences and how it linked to other areas of STEM. The ultimate and long-term goal of GL4HS is to expand the program to multiple locations thereby facilitating the reach of NASA Space Biology beyond NASA-centric regions.

GeneLab

Single cell RNA sequencing reveals shifts in cell maturity and function of endogenous and infiltrating cell types in response to acute intervertebral disc injury

Intervertebral disc (IVD) degeneration contributes to disabling back pain. Degeneration can be initiated by injury and progressively leads to an irreversible loss of cells and function. IVD function restoration through cell replacement therapies have had limited success due to knowledge gaps in the critical cell populations important for repair. Here, in this study, we used single cell RNA sequencing to identify the transcriptional changes of IVD resident and infiltrating cell populations from Control and Injured coccygeal IVDs extracted from 12-week-old female C57BL/6J mice 7 days post injury. Clustering, gene ontology, and pseudotime trajectory analyses determined transcriptomic divergences with injury, flow cytometry identified they types of infiltrating immune cells, and immunofluorescence was utilized to define mesenchymal stem cell (MSC) localization. We identified 11 distinct clusters that included IVD, immune, vascular cells, and MSCs. Differential gene expression analysis determined that Outer Annulus Fibrosus, Neutrophils, Saa2-High MSCs, Macrophages, and Krt18 + Nucleus Pulposus (NP) cells were the major drivers of transcriptomic differences between Control and Injured cells. Gene ontology revealed that the most upregulated biological pathways were angiogenesis and T cell-related while wound healing and ECM regulation were downregulated. Pseudotime trajectory analyses revealed that IVD injury directed cells towards increased differentiation in all clusters, except for Krt18 + NP cells which remained in a less mature cell state. Saa2-High and Grem1-High MSCs populations shifted towards more differentiated IVD cells profiles with injury and localized distinctly within the IVD. This study revealed novel MSC populations with the potential to be leveraged for future IVD repair studies.

Cartilage

Prediction of plant complex traits via integration of multi-omics data

The formation of complex traits is the consequence of genotype and activities at multiple molecular levels. However, connecting genotypes and these activities to complex traits remains challenging. Here, we investigate whether integrating genomic, transcriptomic, and methylomic data can improve prediction for six Arabidopsis traits. We find that transcriptome- and methylome-based models have performances comparable to those of genome-based models. However, models built for flowering time using different omics data identify different benchmark genes. Nine additional genes identified as important for flowering time from our models are experimentally validated as regulating flowering. Gene contributions to flowering time prediction are accession-dependent and distinct genes contribute to trait prediction in different genotypes. Models integrating multi-omics data perform best and reveal known and additional gene interactions, extending knowledge about existing regulatory networks underlying flowering time determination. These results demonstrate the feasibility of revealing molecular mechanisms underlying complex traits through multi-omics data integration.

59 BASIC BIOLOGICAL SCIENCES

A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell transcriptomics provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in silico drug interventions. Here we introduce UNAGI, a deep generative neural network tailored to analyse time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modelling and screening. When applied to a dataset from patients with idiopathic pulmonary fibrosis, UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation using proteomics reveals the accuracy of UNAGI’s cellular dynamics analysis, and the use of the fibrotic cocktail-treated human precision-cut lung slices confirms UNAGI’s predictions that nifedipine, an antihypertensive drug, may have anti-fibrotic effects on human tissues. UNAGI’s versatility extends to other diseases, including COVID, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond idiopathic pulmonary fibrosis, amplifying its use in the quest for therapeutic solutions across diverse pathological landscapes.

Neural Network

scRNA seq of an F1 cross of Marek’s disease resistant and susceptible chickens identifies allele specific expression signatures enriched in transcription modulators

Abstract Marek’s disease (MD), a T cell lymphoma disease in chickens, is caused by the Marek’s disease virus (MDV) found ubiquitously in the poultry industry. Genetically resistant Line 6 3 (L6) and susceptible Line 7 2 (L7) chickens have been instrumental to research on avian immune system response to MDV infection. In this study we characterized molecular signatures unique to splenic immune cell types across different genetic backgrounds 6 days after infection. Using three populations, L6, L7, and an F1 cross between L6xL7, we evaluated the immune cell transcriptome of responding cell types using single cell RNA sequencing. Several MDV genes were found expressed mainly in cytotoxic T cells while ICP4 and MEQ MDV genes were expressed across infected cell types. Using the F1 we quantified allele specific expression (ASE) of biallelic SNPs and found biased expression of parental alleles specific to immune cell subtypes. We identified 22 SNPs with ASE in response to MDV infection mapped to gene rich regions surrounding 59 genes of critical importance for chromatin remodeling and transcriptional regulation. Histone deacetylase genes (HDAC1 and HDAC8) had increased expression of L6 alleles, while small nuclear RNA genes (SNORA68 and SNORA72) expressed higher levels of L7 alleles with infection in T cell subsets. SNPs with ASE also mapped genes important for an adequate immune response including GNLY (cytotoxic activity) and PDIA3 (component of MHC class I peptide loading complex), and genes known to promote viral replication (MCM5 and EIF3M). These results show that functional variants associated with susceptibility to MD may have a bigger impact in subsets of immune cell types, and by characterizing the transcriptomes of these subtypes we can unravel molecular signatures specific to MD genomic resistance.

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