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At least 901 records · Page 50

mTOR regulates aerobic glycolysis through NEAT1 and nuclear paraspeckle-mediated mechanism in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a major form of liver cancer and a leading cause of cancer-related death worldwide. New insights into HCC pathobiology and mechanism of drug actions are urgently needed to improve patient outcomes. HCC undergoes metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the ‘Warburg Effect’ that supports rapid cancer cell growth, survival, and invasion. mTOR is known to promote Warburg Effect, but the underlying mechanism(s) remains poorly defined. The aim of this study is to understand the mechanism(s) and significance of mTOR regulation of aerobic glycolysis in HCC. We profiled mTORC1-dependent long non-coding RNAs (lncRNAs) by RNA-seq of HCC cells treated with rapamycin. Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were used to explore the transcriptional regulation of NEAT1 by mTORC1. [U- 13 C]-glucose labeling and metabolomic analysis, extracellular acidification Rate (ECAR) by Seahorse XF Analyzer, and glucose uptake assay were used to investigate the role of mTOR-NEAT1-NONO signaling in the regulation of aerobic glycolysis. RNA immunoprecipitation (RIP) and NONO-binding motif scanning were performed to identify the regulatory mechanism of pre-mRNA splicing by mTOR-NEAT1. Myristoylated AKT1 (mAKT1)/NRASV 12 -driven HCC model developed by hydrodynamic transfection (HDT) was employed to explore the significance of mTOR-NEAT1 signaling in HCC tumorigenesis and mTOR-targeted therapy. mTOR regulates lncRNA transcriptome in HCC and that NEAT1 is a major mTOR transcriptional target. Interestingly, although both NEAT1_1 and NEAT1_2 are down-regulated in HCC, only NEAT1_2 is significantly correlated with poor overall survival of HCC patients. NEAT1_2 is the organizer of nuclear paraspeckles that sequester the RNA-binding proteins NONO and SFPQ. We show that upon oncogenic activation, mTORC1 suppresses NEAT1_2 expression and paraspeckle biogenesis, liberating NONO/SFPQ, which in turn, binds to U5 within the spliceosome, stimulating mRNA splicing and expression of key glycolytic enzymes. This series of actions lead to enhanced glucose transport, aerobic glycolytic flux, lactate production, and HCC growth both in vitro and in vivo. Furthermore, the paraspeckle-mediated mechanism is important for the anticancer action of US FDA-approved drugs rapamycin/temsirolimus. These findings reveal a molecular mechanism by which mTOR promotes the ‘Warburg Effect’, which is important for the metabolism and development of HCC, and anticancer response of mTOR-targeted therapy.

59 BASIC BIOLOGICAL SCIENCES↗

De novo transcriptome assembly databases for the central nervous system of the medicinal leech

The study of non-model organisms stands to benefit greatly from genetic and genomic data. For a better understanding of the molecular mechanisms driving neuronal development, and to characterize the entire leech Hirudo medicinalis central nervous system (CNS) transcriptome we combined Trinity for de-novo assembly and Illumina HiSeq2000 for RNA-Seq. We present a set of 73,493 de-novo assembled transcripts for the leech, reconstructed from RNA collected, at a single ganglion resolution, from the CNS. This set of transcripts greatly enriches the available data for the leech. Here, we share two databases, such that each dataset allows a different type of search for candidate homologues. The first is the raw set of assembled transcripts. This set allows a sequence-based search. A comprehensive analysis of which revealed 22,604 contigs with high e-values, aligned versus the Swiss-Prot database. This analysis enabled the production of the second database, which includes correlated sequences to annotated transcript names, with the confidence of BLAST best hit.

59 BASIC BIOLOGICAL SCIENCES↗

Eucalyptus grandis MYB‐Like and RAN‐Like Zinc Finger Proteins Display Dual Roles in Regulating Plant Immunity and Symbiosis Pathways

Plant roots live in constant contact with diverse microbes in the soil. Plant fitness, therefore, relies on signaling pathways that mount an effective immune response against pathogens while fostering mutualistic symbioses. Plant pathways, and specifically immune genes that may act as "switches," discriminating between pathogenic or mutualistic fungi, remain largely unknown. Using Eucalyptus grandis as a model system, we investigate alterations to the root transcriptomic landscape during pre-symbiosis with either the pathogen Armillaria luteobubalina or the mutualistic fungus Pisolithus microcarpus. Comparative analyses identified three strongly counter-regulated genes that may act as immune switches to accommodate or to repress fungal colonization. We characterized two of these, a MYB-like and RAN-like zinc finger protein, using a transgenic approach and demonstrated that they have bifunctional roles in the regulation of cell death and a hypersensitive-like response, depending on the lifestyle of the associated fungus. Using co-expression network analysis, we identified hypothetical pathways correlated to these genes. We functionally validated these predictions using plants with transgenic roots with increased or decreased transcription of these genes, thereby showing the power of co-expression networks as an a priori approach to identify key immune response pathways in plants. Overall, our results demonstrate that prior to physical contact with microbes, MYB-like and RAN-like zinc finger proteins are key regulators of plant immune signaling that respond to fungal signals and enable or repress symbiotic establishment.

mycorrhizal fungi↗

Plant iTRAQ-based proteomics

We present a simple one-­pot extraction protocol, which rapidly isolates hydrophyllic metabolites, lipids, and proteins from the same pulverized plant sample. Also detailed is a global plant proteomics sample preparation method utilizing iTRAQ multiplexing reagents that enables deep proteome coverage due to the use of HPLC fractionation of the peptides prior to mass spectrometric analysis. We have successfully used this protocol on several different plant tissues (e.g., roots, stems, leaves) from different plants (e.g., sorghum, poplar, Arabidopsis, soybean), and have been able to successfully detect and quantify thousands of proteins. Multiplexing strategies such as iTRAQ and the bioinformatics strategy outlined here, ultimately provide insight into which proteins are significantly changed in abundance between two or more groups (e.g., control, perturbation). Our bioinformatics strategy yields z-­score values, which normalize the expression data into a format that can easily be cross-­compared with other expression data (i.e., metabolomics, transcriptomics) obtained from different analytical methods and instrumentation.

60 APPLIED LIFE SCIENCES↗

GeneLab for High Schools: Data Mining for the Next Generation

Modern biological sciences have become increasingly based on molecular biology and high-throughput molecular techniques, such as genomics, transcriptomics, and proteomics. NASA Scientists and the NASA Space Biology Program have aimed to examine the fundamental building blocks of life (RNA, DNA and protein) in order to understand the response of living organisms to space and aid in fundamental research discoveries on Earth. In an effort to enable NASA funded science to be available to everyone, NASA has collected the data from omics studies and curated them in a data system called GeneLab. Whilst most college-level interns, academics and other scientists have had some interaction with omics data sets and analysis tools, high school students often have not. Therefore, the Space Biology Program is implementing a new Summer Program for high-school students that aims to inspire the next generation of scientists to learn about and get involved in space research using GeneLabs Data System. The program consists of three main components core learning modules, focused on developing students knowledge on the Space Biology Program and Space Biology research, Genelab and the data system, and previous research conducted on model organisms in space; networking and team work, enabling students to interact with guest lecturers from local universities and their fellow peers, and also enabling them to visit local universities and genomics centers around the Bay area; and finally an independent learning project, whereby students will be required to form small groups, analyze a dataset on the Genelab platform, generate a hypothesis and develop a research plan to test their hypothesis. This program will not only help inspire high-school students to become involved in space-based research but will also help them develop key critical thinking and bioinformatics skills required for most college degrees and furthermore, will enable them to establish networks with their peers and connections with university Professors that may help them achieve their educational goals.

genelab↗

DNA Damage Response to Low and High-LET in a Large Cohort of Mice and Humans and Latest Advancement in NASA Space Omics

This presentation will first focus on a thorough evaluation of the DNA damage response to both low and high-LET in a cohort of 76 mice primary skin fibroblast derived from 15 different strains or in human blood mononuclear cells derived from 550 healthy donors. In both the human and mice work, we have hypothesized that DNA repair capacity can be used as a marker to evaluate and differentiate individual radiation sensitivity. More specifically, this work is based on the concept that the combined time-dose dependence of radiation-induced foci (RIF) of p53-binding protein 1 (53BP1) following low-LET exposure contains sufficient information to infer sensitivity to any other LET. This work is one of the most extensive studies on the kinetics and possible genetic underpinnings of radiation-induced DNA damage and repair. Results on humans are still preliminary as we are still in the process of collecting and isolating primary blood mononuclear cells from 500 to 800 healthy subjects of European descent, 18-75 years of age, 50/50 male/female distribution. We have analyzed 53BP1+ RIF formation as well as oxidative stress and cell death in primary cells from 192 subjects in response to the same HZE particles as used in mice: 600 MeV/n Fe, 350 MeV/n Ar and 350 MeV/n Si, 1.1 and 3 particles/100m2, 4 and 24 hours after irradiation. The second part of the talk will focus on describing GeneLab: The NASA Systems Biology Platform for Space Omics Repository, Analysis and Visualization. NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). Started as a repository designed to archive precious omics from space experiments, GeneLab has expanded its scope to maximize the intelligibility of the raw data (e.g. RNAseq, microarray, WGBS, metagenome), particularly for users with limited bioinformatics knowledge. As such GeneLab is now providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome), to help users explore important questions: Which genes or proteins are expressed differently in space for various living organisms? What are the consequences arising from these changes? What specifics DNA mutations or epigenetic changes happen in space? What species or genetic features lead to better adaption to such a unique environment? In this presentation, we will report on the current and future objectives for GeneLab, and review recent published studies relating molecular changes observed in various animal models and tissue with microgravity, radiation, circadian rhythm, hydration and carbon dioxide conditions.

DNA repair kinetics↗

Temporal multi-omic analysis uncovers sex-biased molecular programs underlying skeletal muscle adaptation to endurance training

Background. Exercise training is known to benefit health and reduce disease risk. While adaptations in skeletal muscles are fundamental to many of the health benefits of exercise training, the common and sex-specific molecular regulators that mediate these adaptations remain to be fully elucidated. Methods. To this end, we leveraged skeletal muscle multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), where 6 month-old male and female rats endurance trained for 1, 2, 4, or 8 weeks. Our objective was to identify shared and sex-specific multi-omic molecular responses to endurance training in skeletal muscle, and relate them to phenotypic adaptations. Results. We identified largely sexually-conserved transcriptomic and proteomic enrichments in the gastrocnemius, which correlated with skeletal muscle responses from a published exercise study in humans. We uncovered sex-consistent post-translational modifications, including decreased oxidation of MYH2 and deacetylation of the ß-oxidation enzyme HADHA. Pathway enrichment analyses revealed sex-specific remodeling across the acetylome, redox proteome, and phosphoproteome; females decreased mitochondrial protein oxidation and increased mitochondrial cristae proteins, indicative of enhanced redox buffering and mitochondrial efficiency. Despite observed decreases in the oxidation of key mitochondrial proteins, females displayed increases in the oxidation of proteins involved in glucose catabolism relative to males after 8 weeks of training, suggestive of sex-biased subcellular reactive oxygen species generation. Conclusions. This work shows a large portion of the adaptive response to endurance training in skeletal muscle is shared between females and males, while there are distinct and nuanced sex-specific adaptations that are evident, particularly at the level of post-translational regulation.

Many, Gina M.↗

Profiling neuron-autonomous lncRNA changes upon ischemia/reperfusion injury

Highlights: • Tnxa-ps1 is up regulated after OGD/R. • Tnxa-ps1 knockdown promoted neuronal survival after OGD/R. • Tnxa-ps1 up-regulation is associated with the four mRNA changes after OGD/R. Extensive changes of neuronal transcriptome occur post ischemic stroke and during the following reperfusion. Although numerous studies focused on transcriptome changes of mRNAs associated with ischemic stroke, little is known about whether and how long non-coding RNAs (lncRNAs), which play critical roles in cellular homeostasis, are involved in this process. In this study, we performed high throughput screening to analyze expression changes of lncRNAs in primarily cultured hippocampal neurons under an oxygen-glucose deprivation/reperfusion (OGD/R) condition at 0 h, 6 h, 12 h, and 18 h, respectively. Knock down of one validated lncRNAs (Tnxa-ps1) promoted neuronal survival by inhibiting apoptosis. Coding non-coding co-expression network analysis revealed that the expression of Tnxa-ps1 was highly correlated with changes of a particular group of genes, many of which are associated with neural protection. Finally, we showed that down-regulation of Tnxa-ps1 reversed the expression changes of four mRNAs post OGD/R, revealing a regulatory effect between Tnxa-ps1 and selected genes. Together, our data revealed possible participation of lncRNAs in the pathophysiology of OGD/R and thereby provided new insights into the studies of potential therapeutic targets for ischemic stroke.

60 APPLIED LIFE SCIENCES↗

Comparative Transcriptomics Identifies Novel Genes and Pathways Involved in Post-Traumatic Osteoarthritis Development and Progression

Anterior cruciate ligament (ACL) injuries often result in post-traumatic osteoarthritis (PTOA). To better understand the molecular mechanisms behind PTOA development following ACL injury, we profiled ACL injury-induced transcriptional changes in knee joints of three mouse strains with varying susceptibility to OA: STR/ort (highly susceptible), C57BL/6J (moderately susceptible) and super-healer MRL/MpJ (not susceptible). Right knee joints of the mice were injured using a non-invasive tibial compression injury model and global gene expression was quantified before and at 1-day, 1-week, and 2-weeks post-injury using RNA-seq. Following injury, injured and uninjured joints of STR/ort and injured C57BL/6J joints displayed significant cartilage degeneration while MRL/MpJ had little cartilage damage. Gene expression analysis suggested that prolonged inflammation and elevated catabolic activity in STR/ort injured joints, compared to the other two strains may be responsible for the severe PTOA phenotype observed in this strain. MRL/MpJ had the lowest expression values for several inflammatory cytokines and catabolic enzymes activated in response to ACL injury. Furthermore, we identified several genes highly expressed in MRL/MpJ compared to the other two strains including B4galnt2 and Tpsab1 which may contribute to enhanced healing in the MRL/MpJ. Overall, this study has increased our knowledge of early molecular changes associated with PTOA development.

59 BASIC BIOLOGICAL SCIENCES↗

Tripogon loliiformis tolerates rapid desiccation after metabolic and transcriptional priming during initial drying

Abstract Crop plants and undomesticated resilient species employ different strategies to regulate their energy resources and growth. Most crop species are sensitive to stress and prioritise rapid growth to maximise yield or biomass production. In contrast, resilient plants grow slowly, are small, and allocate their resources for survival in challenging environments. One small group of plants, termed resurrection plants, survive desiccation of their vegetative tissue and regain full metabolic activity upon watering. However, the precise molecular mechanisms underlying this extreme tolerance remain unknown. In this study, we employed a transcriptomics and metabolomics approach, to investigate the mechanisms of desiccation tolerance in Tripogon loliiformis , a modified desiccation-tolerant plant, that survives gradual but not rapid drying. We show that T. loliiformis can survive rapid desiccation if it is gradually dried to 60% relative water content (RWC). Furthermore, the gene expression data showed that T. loliiformis is genetically predisposed for desiccation in the hydrated state, as evidenced by the accumulation of MYB, NAC, bZIP, WRKY transcription factors along with the phytohormones, abscisic acid, salicylic acid, amino acids (e.g., proline) and TCA cycle sugars during initial drying. Through network analysis of co-expressed genes, we observed differential responses to desiccation between T. loliiformis shoots and roots. Dehydrating shoots displayed global transcriptional changes across broad functional categories, although no enrichment was observed during drying. In contrast, dehydrating roots showed distinct network changes with the most significant differences occurring at 40% RWC. The cumulative effects of the early stress responses may indicate the minimum requirements of desiccation tolerance and enable T. loliiformis to survive rapid drying. These findings potentially hold promise for identifying biotechnological solutions aimed at developing drought-tolerant crops without growth and yield penalties.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization and Transcription of Arsenic Respiration and Resistance Genes During In Situ Uranium Bioremediation

The possibility of arsenic release and the potential role of Geobacter in arsenic biogeochemistry during in situ uranium bioremediation was investigated because increased availability of organic matter has been associated with substantial releases of arsenic in other subsurface environments. In a field experiment conducted at the Rifle, CO study site, groundwater arsenic concentrations increased when acetate was added. The number of transcripts from arrA, which codes for the alpha subunit of dissimilatory As(V) reductase, and acr3, which codes for the arsenic pump protein Acr3, were determined with quantitative RT-PCR. Most of the arrA (> 60%) and acr3-1 (> 90%) sequences that were recovered were most similar to Geobacter species, while the majority of acr3-2 (>50%) sequences were most closely related to Rhodoferax ferrireducens. Analysis of transcript abundance demonstrated that transcription of acr3-1 by the subsurface Geobacter community was correlated with arsenic concentrations in the groundwater. In contrast, Geobacter arrA transcript numbers lagged behind the major arsenic release and remained high even after arsenic concentrations declined. This suggested that factors other than As(V) availability regulated transcription of arrA in situ even though the presence of As(V) increased transcription of arrA in cultures of G. lovleyi, which was capable of As(V) reduction. These results demonstrate that subsurface Geobacter species can tightly regulate their physiological response to changes in groundwater arsenic concentrations. The transcriptomic approach developed here should be useful for the study of a diversity of other environments in which Geobacter species are considered to have an important influence on arsenic biogeochemistry.

arsenic resistance↗

Hepatic leukemia factor promotes resistance to cell death: Implications for therapeutics and chronotherapy

Physiological variation related to circadian rhythms and aberrant gene expression patterns are believed to modulate therapeutic efficacy, but the precise molecular determinants remain unclear. Here we examine the regulation of cell death by hepatic leukemia factor (HLF), which is an output regulator of circadian rhythms and is aberrantly expressed in human cancers, using an ectopic expression strategy in JB6 mouse epidermal cells and human keratinocytes. Ectopic HLF expression inhibited cell death in both JB6 cells and human keratinocytes, as induced by serum-starvation, tumor necrosis factor alpha and ionizing radiation. Microarray analysis indicates that HLF regulates a complex multi-gene transcriptional program encompassing upregulation of anti-apoptotic genes, downregulation of pro-apoptotic genes, and many additional changes that are consistent with an anti-death program. Collectively, our results demonstrate that ectopic expression of HLF, an established transcription factor that cycles with circadian rhythms, can recapitulate many features associated with circadian-dependent physiological variation. - Highlights: ► Circadian-dependent physiological variation impacts therapeutic efficacy. ► Hepatic leukemia factor inhibits cell death and is a candidate circadian factor. ► Hepatic leukemia factor anti-death program is conserved in murine and human cells. ► Transcriptomics indicates the anti-death program results from a systems response.

60 APPLIED LIFE SCIENCES↗

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

59 BASIC BIOLOGICAL SCIENCES↗

Data from: Generation of transcript assemblies and identification of single nucleotide polymorphisms from seven lowland and upland cultivars of switchgrass

Switchgrass (Panicum virgatum) is a North American perennial prairie species that has been used as a rangeland and forage crop and has recently been targeted as a potential biofuel feedstock species. Switchgrass, which occurs as tetraploid and octoploid forms, is classified into lowland or upland ecotypes that differ in growth phenotypes and adaptation to distinct habitats. Using RNA-sequencing reads derived from crown, young shoot and leaf tissues, we generated sequence data from seven switchgrass cultivars, three lowland and four upland, to enable comparative analyses between switchgrass cultivars and to identify single nucleotide polymorphisms (SNPs) for use in breeding and genetic analysis. We also generated individual transcript assemblies for each of the cultivars. Transcript data indicate that subgenomes of octoploid switchgrass are not substantially different from subgenomes of tetraploids as expected for an autopolyploid origin of switchgrass octoploids. Using RNA-sequencing reads aligned to the switchgrass Release 0 AP13 reference genome, we identified 1,305,976 high-confidence SNPs. Of these SNPs, 438,464 were unique to lowland cultivars, but only 12,002 were found in all lowlands. Conversely, 723,678 SNPs were unique to upland cultivars with only 34,665 observed in all uplands. Comparison of our high-confidence transcriptome-derived SNPs with SNPs previously identified in a genotyping-by-sequencing study of an association panel revealed limited overlap between the two methods, highlighting the utility of transcriptome-based SNP discovery in augmenting genome diversity polymorphism datasets. The transcript and SNP data described here provide a useful resource for switchgrass gene annotation and marker-based analyses of the switchgrass genome.

09 BIOMASS FUELS↗

3′ RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism

The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

3’ RNA-seq↗

GeneLab: Overview of Challenges and Opportunities

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data, and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 200 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetery data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 100 scientists from NASA and academia. These pipelines are now being used by a group of bioinformatics interns to provide standard basic analysis of the data for incorporation into GLDS.

Galazka, Jonathan M.↗

GeneLab: Open Science for Life in Space

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data, and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 200 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetery data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 100 scientists from NASA and academia. These pipelines are now being used by a group of bioinformatics interns to provide standard basic analysis of the data for incorporation into GLDS.

Galazka, Jonathan M.↗