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Plants have been recognized as key components of bioregenerative life support systems for space exploration, and many experiments have been carried out to evaluate their adaptability to spaceflight. Unfortunately, few of these experiments have involved monocot plants, which constitute most of the crops used on Earth as sources of food, feed, and fiber. To better understand the ability of monocot plants to adapt to spaceflight, we germinated and grew Brachypodium distachyon seedlings of the Bd21, Bd21-3, and Gaz8 accessions in a customized growth unit on the International Space Station, along with 1-g ground controls. At the end of a 4-day growth period, seedling organ’s growth and morphologies were quantified, and root and shoot transcriptomic profiles were investigated using RNA-seq. The roots of all three accessions grew more slowly and displayed longer root hairs under microgravity conditions relative to ground control. On the other hand, the shoots of Bd21-3 and Gaz-8 grew at similar rates between conditions, whereas those of Bd21 grew more slowly under microgravity. The three Brachypodium accessions displayed dramatically different transcriptomic responses to microgravity relative to ground controls, with the largest numbers of differentially expressed genes (DEGs) found in Gaz8 (4527), followed by Bd21 (1353) and Bd21-3 (570). Only 47 and six DEGs were shared between accessions for shoots and roots, respectively, including DEGs encoding wall-associated proteins and photosynthesis-related DEGs. Furthermore, DEGs associated with the “Oxidative Stress Response” GO group were up-regulated in the shoots and down-regulated in the roots of Bd21 and Gaz8, indicating that Brachypodium roots and shoots deploy distinct biological strategies to adapt to the microgravity environment. A comparative analysis of the Brachypodium oxidative-stress response DEGs with the Arabidopsis ROS wheel suggests a connection between retrograde signaling, light response, and decreased expression of photosynthesis-related genes in microgravity-exposed shoots. In Gaz8, DEGs were also found to preferentially associate with the “Plant Hormonal Signaling” and “MAP Kinase Signaling” KEGG pathways. Overall, these data indicate that Brachypodium distachyon seedlings exposed to the microgravity environment of ISS display accession- and organ-specific responses that involve oxidative stress response, wall remodeling, photosynthesis inhibition, expression regulation, ribosome biogenesis, and post-translational modifications. The general characteristics of these responses are similar to those displayed by microgravity-exposed Arabidopsis thaliana seedlings. However, organ- and accession-specific components of the response dramatically differ both within and between species. These results suggest a need to directly evaluate candidate-crop responses to microgravity to better understand their specific adaptability to this novel environment and develop cultivation strategies allowing them to strive during spaceflight. 

Clinostats are instruments that continuously rotate biological specimens along an axis, thereby averaging their orientation relative to gravity over time. Our previous experiments indicated that low-speed clinorotation may itself trigger directional root tip curvature. In this project, we have investigated the root curvature response to low-speed clinorotation using Arabidopsis thaliana and Brachypodium distachyon seedlings as models. We show that low-speed clinorotation triggers root tip curvature in which direction is dictated by gravitropism during the first half-turn of clinorotation. We also show that the angle of root tip curvature is modulated by the speed of clinorotation. Arabidopsis mutations affecting gravity susception (pgm) or gravity signal transduction (arg1, toc132) are shown to affect the root tip curvature response to low-speed clinorotation. Furthermore, low-speed vertical clinorotation triggers relocalization of the PIN3 auxin efflux facilitator to the lateral membrane of Arabidopsis root cap statocytes, and creates a lateral gradient of auxin across the root tip. Together, these observations support a role for gravitropism in modulating root curvature responses to clinorotation. Interestingly, distinct Brachypodium distachyon accessions display different abilities to develop root tip curvature responses to low-speed vertical clinorotation, suggesting the possibility of using genome-wide association studies to further investigate this process. 

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication we describe enhancements made to our data processing pipeline and to our website to adapt to an ever-increasing information content. The number of sequences in UniProtKB has risen to over 227 million and we are working towards including a reference proteome for each taxonomic group. We continue to extract detailed annotations from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations provided by automated systems using a variety of machine-learning techniques. In addition, the scientific community continues their contributions of publications and annotations to UniProt entries of their interest. Finally, we describe our new website (https://www.uniprot.org/), designed to enhance our users’ experience and make our data easily accessible to the research community. This interface includes access to AlphaFold structures for more than 85% of all entries as well as improved visualisations for subcellular localisation of proteins.

 

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

 

Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/. 

Abstract The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.