FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the FAIRness of NASAs GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems

NASA's GeneLab Phase II: Federated Search and Data Discovery

GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics

NASA's GeneLab: An Integrated Omics Data Commons and Workbench

GeneLab (http://genelab.nasa.gov) is a NASA initiative designed to accelerate open science biomedical research in support of the human exploration of space and the improvement of life on earth. The GeneLab Data Systems (GLDS) were developed to help investigators corroborate findings from omics (genomics, transcriptomics, proteomics, and metabolomics) assays and translate them into systems biology knowledge and, eventually, therapeutics, including countermeasures to support life in space. Phase I of the project (completed) emphasized developing key capabilities for submission, curation, storage, search, and retrieval of omics data from biomedical research in and of space environments. The development focus for Phase II (completed) was federated data search and retrieval of these kinds of data from other open-access repositories. The last phase of the project (in work) entails developing an omics analysis tool set, and a portal to visualize processed omics data, emphasizing integration with the data repository and search functions developed during the prior phases. The final product will be an open-access system where users can individually or collaboratively publish, search, integrate, analyze, and visualize omics data

Predicting Cell Death and Mutation Frequency for a Wide Spectrum of LET by Assuming DNA Break Clustering Inside Repair Domains

Cosmic radiation, which is composed of high charged and energy (HZE) particles, is responsible for cell death and mutation, which may be involved in cancer induction. Mutations are consequences of mis-repaired DNA breaks especially double-strand breaks (DSBs) that induce inter- and intra-chromosomal rearrangements (translocations, deletions, inversion). In this study, a computer simulation model is used to investigate the clustering of DSBs in repair domains, previously evidenced by our group in human breast cells [1]. This model is calibrated with experimental data measuring persistent 53BP1 radiation-induced foci (RIF) and is used to explain the high relative biological effectiveness (RBE) of HZE for both cell death and DNA mutation frequencies. We first validate our DSB cluster model using a new track structure model deployed on a simple geometrical configuration for repair domains in the nucleus; then we extend the scope from cell death to mutation induction. This work suggests that mechanism based on DSB repair process can explain several biological effects induced by HZE particles on different type of living cell

NASA's GeneLab: An Integrated Omics Data Commons and Workbench

GeneLab (http://genelab.nasa.gov) is a NASA initiative designed to accelerate "open science" biomedical research in support of the human exploration of space and the improvement of life on earth. The GeneLab Data Systems (GLDS) were developed to help investigators corroborate findings from "omics" (genomics, transcriptomics, proteomics, and metabolomics) assays and translate them into systems biology knowledge and, eventually, therapeutics, including countermeasures to support life in space. Phase I of the project (completed) emphasized developing key capabilities for submission, curation, storage, search, and retrieval of omics data from biomedical research in and of space environments. The development focus for Phase II (completed) was federated data search and retrieval of these kinds of data from other open-access repositories. The last phase of the project (in work) entails developing an omics analysis tool set, and a portal to visualize processed omics data, emphasizing integration with the data repository and search functions developed during the prior phases. The final product will be an open-access system where users can individually or collaboratively publish, search, integrate, analyze, and visualize omics data

Systemic Response to Microgravity: Utilizing GeneLab Datasets to Identify Molecular Targets for Future Hypotheses-Driven Spaceflight Studies

Biological risks associated with microgravity are a major concern for long-term space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. To perform our analysis, we utilized the NASA GeneLab database which is a publicly available repository containing a wide array of omics results from experiments conducted with: i) with different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); ii) a variety of tissues; and 3) assays that measure epigenetic, transcriptional, and protein expression changes. Meta-analysis of the transcriptomic data from 7 different murine and rat data sets, examining tissues such as liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius) revealed for the first time, the existence of potential master regulators coordinating systemic responses to microgravity in rodents. We identified p53, TGF(beta)1 and immune related pathways as the highly prevalent pan-tissue signaling pathways that are affected by microgravity. Some variability in the degree of change in their expression across species, strain and time of flight was also observed. Interestingly, while certain skeletal muscle (gastrocnemius and soleus) exhibited an overall down-regulation of these genes, some other muscle types such as the extensor digitorum longus, tibialis anterior and quadriceps, showed an up-regulated expression, indicative of potential compensatory mechanisms to prevent microgravity-induced atrophy. Key genes isolated by unbiased systems analyses displayed a major overlap between tissue types and flight conditions and established TGF(beta)1 to be the most connected gene across all data sets. Finally, a set of microgravity responsive miRNA signature was identified and based on their predicted functional state and subsequent impact on health, a theoretical health risk score was calculated. The genes and miRNAs identified from our analyses can be targeted for future research involving efficient countermeasure design. Our study thus exemplifies the utility of GeneLab data repository to aid in the process of performing novel hypothesis based spaceflight research aimed at elucidating the global impact of environmental stressors at multiple biological scales

NASA GeneLab Project: Bridging Space Radiation Omics with Ground Studies

Accurate assessment of risk factors for long-term space missions is critical for human space exploration: therefore it is essential to have a detailed understanding of the biological effects on humans living and working in deep space. Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) currently includes datasets from both spaceflight and ground-based studies, a majority of which involve exposure to ionizing radiation. In addition to detailed information for ground-based studies, we are in the process of adding detailed, curated dosimetry information for spaceflight missions. GeneLab is the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. In addition to previously acquired data, the GLDS is continually expanding as Omics related data are generated by the space life sciences community. Here we provide a brief summary of space radiation related data available at GeneLab

Systemic Microgravity Response: Utilizing GeneLab to Develop Hypotheses for Spaceflight Risks

Biological risks associated with microgravity is a major concern for space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. The overall goal of our work is to identify potential master regulators responsible for such responses to microgravity conditions. To do this we utilized the NASA GeneLab database which contains a wide array of omics experiments, including data from: 1) different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); 2) different tissues; and 3) different types of assays that measure epigenetic, transcriptional, and protein expression changes. We have performed meta-analysis identifying potential master regulators involved with systemic responses to microgravity. The analysis used 7 different murine and rat data sets, examining the following tissues: liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius). Using a systems biology approach, we were able to determine that p53 and immune related pathways appear central to pan-tissue microgravity responses. Evidence for a universal response in the form of consistency of change across tissues in regulatory pathways was observed in both STS and ISS experiments with varying durations; while degree of change in expression of these master regulators varied across species and strain, some change in these master regulators was universally observed. Interestingly, certain skeletal muscle (gastrocnemius and soleus) show an overall down-regulation in these genes, while in other types (extensor digitorum longus, tibialis anterior and quadriceps) they are up-regulated, suggesting certain muscle tissues may be compensating for atrophy responses caused by microgravity. Studying these organtissue-specific perturbations in molecular signaling networks, we demonstrate the value of GeneLab in characterizing potential master regulators associated with biological risks for spaceflight