Meta-analysis of the space flight and microgravity response of the Arabidopsis plant transcriptome

15 p.-8 fig.-2 tab.Spaceflight presents a multifaceted environment for plants, combining the effects on growth of many stressors and factors including altered gravity, the influence of experiment hardware, and increased radiation exposure. To help understand the plant response to this complex suite of factors this study compared transcriptomic analysis of 15 Arabidopsis thaliana spaceflight experiments deposited in the National Aeronautics and Space Administration’s GeneLab data repository. These data were reanalyzed for genes showing significant differential expression in spaceflight versus ground controls using a single common computational pipeline for either the microarray or the RNA-seq datasets. Such a standardized approach to analysis should greatly increase the robustness of comparisons made between datasets. This analysis was coupled with extensive cross-referencing to a curated matrix of metadata associated with these experiments. Our study reveals that factors such as analysis type (i.e., microarray versus RNA-seq) or environmental and hardware conditions have important confounding effects on comparisons seeking to define plant reactions to spaceflight. The metadata matrix allows selection of studies with high similarity scores, i.e., that share multiple elements of experimental design, such as plant age or flight hardware. Comparisons between these studies then helps reduce the complexity in drawing conclusions arising from comparisons made between experiments with very different designs.This work was coordinated through the GeneLab Plant Analysis Working Group and was supported by NASA grants 80NSSC19K0126, 80NSSC18K0132 and 80NSSC21K0577 to S.G. and R.B., through NASA 80NSSC19K1481 to S.W., NNX15AG55G to C.W., and NNX15AG56G to L.D. and N.L., from the Spanish Agencia Estatal de Investigación grant RTI2018-099309-B-I00 and ESA 1340112 4000131202/20/NL/PG/pt to R.H. Contributions from P.J. and P.G. were partially supported by funds from the Oregon State University, NSF awards 1127112 and 1340112 and the United States Department of Agriculture, Agriculture Research Service. The Qlik software used in this work is provided under a free-to-use educational license from Qlik Technologies Inc. GeneLab datasets were obtained from https://genelab-data.ndc.nasa.gov/genelab/projects/, maintained by NASA GeneLab, NASA Ames Research Center, Moffett Field, CA 94035.Peer reviewe

Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development

The Materials Research Platform: Defining the Requirements from User Stories

A recent meeting focused on accelerated materials design and discovery examined user requirements for a general, collaborative, integrative, and on-demand materials research platform

NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab

Approaches for Investigating Phase Transformations at the Atomic Scale

Multiple characterization (e.g., TEM/STEM, 3DAP, x-ray/neutron diffraction) techniques, and modeling and simulation tools (e.g., first principles calculations, Monte Carlo methods, cluster expansions, Molecular Dynamics) are used to investigate phase transformations at the atomic scale. The complementary nature of these experimental techniques, as well as the combination of experimental techniques with modeling and simulation can provide powerful synergies for these investigations. This symposium will give emphasis to studies where multiple techniques and/or computational materials science tools have been coupled for the study of phase transformations at the atomic scale.Peer Reviewe

NASA GeneLab RNA-Seq Consensus Pipeline: Standardized Processing of Short-Read RNA-Seq Data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab

Discovery of a Superconducting Cu-Bi Intermetallic Compound by High-Pressure Synthesis

A new intermetallic compound, the first to be structurally identified in the Cu-Bi binary system, is reported. This compound is accessed by high-pressure reaction of the elements. Its detailed characterization, physical property measurements, and abinitio calculations are described. The commensurate crystal structure of Cu11Bi7 is a unique variation of the NiAs structure type. Temperature-dependent electrical resistivity and heat capacity measurements reveal a bulk superconducting transition at T-c=1.36K. Density functional theory calculations further demonstrate that Cu11Bi7 can be stabilized (relative to decomposition into the elements) at high pressure and temperature. These results highlight the ability of high-pressure syntheses to allow for inroads into heretofore-undiscovered intermetallic systems for which no thermodynamically stable binaries are known

Quaternary Chalcogenide Semiconductors with 2D Structures: Rb₂ZnBi₂Se₅ and Cs₆Cd₂Bi₈Te₁₇

Two new layered compounds Rb₂ZnBi₂Se₅ and Cs₆Cd₂Bi₈Te₁₇ are described. Rb₂ZnBi₂Se₅ crystallizes in the orthorhombic space group <i>Pnma</i>, with lattice parameters of <i>a</i> = 15.6509(17) Å, <i>b</i> = 4.218(8) Å, and <i>c</i> = 18.653(3) Å. Cs₆Cd₂Bi₈Te₁₇ crystallizes in the monoclinic <i>C</i>2/<i>m</i> space group, with <i>a</i> = 28.646(6) Å, <i>b</i> = 4.4634(9) Å, <i>c</i> = 21.164(4) Å, and β = 107.65(3)°. The two structures are different and composed of anionic layers which are formed by inter connecting of BiQ₆ octahedra (Q = Se or Te) and MQ₄ (M = Zn or Cd) tetrahedra. The space between the layers hosts alkali metal as counter cations. The rubidium atoms of Rb₂ZnBi₂Se₅ structure can be exchanged with other cations (Cd²⁺, Pb²⁺ and Zn²⁺) in aqueous solutions forming new phases. Rb₂ZnBi₂Se₅ is an <i>n</i>-type semiconductor and exhibits an indirect band gap energy of 1.0 eV. Rb₂ZnBi₂Se₅ is a congruently melting compound (mp ∼644 °C). The thermal conductivity of this semiconductor is very low with 0.38 W·m^–1·K^–1 at 873 K. Density functional theory (DFT) calculations suggest that the low lattice thermal conductivity of Rb₂ZnBi₂Se₅ is attributed to heavy Bi atom induced slow phonon velocities and large Gruneisen parameters especially in the <i>a</i> and <i>c</i> directions. The thermoelectric properties of Rb₂ZnBi₂Se₅ were characterized with the highest ZT value of ∼0.25 at 839 K