"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

Galaxy Training: A powerful framework for teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments.

Adenosine monophosphate deaminase modulates BIN2 activity through hydrogen peroxide-induced oligomerization.

The Arabidopsis thaliana GSK3-like kinase, BRASSINOSTEROID-INSENSITIVE2 (BIN2) is a key negative regulator of brassinosteroid (BR) signaling and a hub for crosstalk with other signaling pathways. However, the mechanisms controlling BIN2 activity are not well understood. Here we performed a forward genetic screen for resistance to the plant-specific GSK3 inhibitor bikinin and discovered that a mutation in the ADENOSINE MONOPHOSPHATE DEAMINASE (AMPD)/EMBRYONIC FACTOR1 (FAC1) gene reduces the sensitivity of Arabidopsis seedlings to both bikinin and BRs. Further analyses revealed that AMPD modulates BIN2 activity by regulating its oligomerization in a hydrogen peroxide (H2O2)-dependent manner. Exogenous H2O2 induced the formation of BIN2 oligomers with a decreased kinase activity and an increased sensitivity to bikinin. By contrast, AMPD activity inhibition reduced the cytosolic reactive oxygen species (ROS) levels and the amount of BIN2 oligomers, correlating with the decreased sensitivity of Arabidopsis plants to bikinin and BRs. Furthermore, we showed that BIN2 phosphorylates AMPD to possibly alter its function. Our results uncover the existence of an H2O2 homeostasis-mediated regulation loop between AMPD and BIN2 that fine-tunes the BIN2 kinase activity to control plant growth and development.

Expanding the Galaxy's reference data.

Summary: Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. In addition, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenie's remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS (CernVM File System) repository from GalaxyProject.org, with mirrors across the USA, Canada, Europe and Australia, enabling easy use outside of Galaxy. Availability and implementation: The ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 22.01, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license. Access to existing data is also available through CVMFS, with instructions at https://galaxyproject.org/admin/reference-data-repo/. No new data were generated or analyzed in support of this research.

ELIXIR biovalidator for semantic validation of life science metadata.

SUMMARY: To advance biomedical research, increasingly large amounts of complex data need to be discovered and integrated. This requires syntactic and semantic validation to ensure shared understanding of relevant entities. This article describes the ELIXIR biovalidator, which extends the syntactic validation of the widely used AJV library with ontology-based validation of JSON documents. AVAILABILITY AND IMPLEMENTATION: Source code: https://github.com/elixir-europe/biovalidator, Release: v1.9.1, License: Apache License 2.0, Deployed at: https://www.ebi.ac.uk/biosamples/schema/validator/validate. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Self-incompatibility requires GPI anchor remodeling by the poppy PGAP1 ortholog HLD1.

Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are tethered to the outer leaflet of the plasma membrane where they function as key regulators of a plethora of biological processes in eukaryotes. Self-incompatibility (SI) plays a pivotal role regulating fertilization in higher plants through recognition and rejection of "self" pollen. Here, we used Arabidopsis thaliana lines that were engineered to be self-incompatible by expression of Papaver rhoeas SI determinants for an SI suppressor screen. We identify HLD1/AtPGAP1, an ortholog of the human GPI-inositol deacylase PGAP1, as a critical component required for the SI response. Besides a delay in flowering time, no developmental defects were observed in HLD1/AtPGAP1 knockout plants, but SI was completely abolished. We demonstrate that HLD1/AtPGAP1 functions as a GPI-inositol deacylase and that this GPI-remodeling activity is essential for SI. Using GFP-SKU5 as a representative GPI-AP, we show that the HLD1/AtPGAP1 mutation does not affect GPI-AP production and targeting but affects their cleavage and release from membranes in vivo. Our data not only implicate GPI-APs in SI, providing new directions to investigate SI mechanisms, but also identify a key functional role for GPI-AP remodeling by inositol deacylation in planta.

PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants.

PLAZA is a platform for comparative, evolutionary, and functional plant genomics. It makes a broad set of genomes, data types and analysis tools available to researchers through a user-friendly website, an API, and bulk downloads. In this latest release of the PLAZA platform, we are integrating a record number of 134 high-quality plant genomes, split up over two instances: PLAZA Dicots 5.0 and PLAZA Monocots 5.0. This number of genomes corresponds with a massive expansion in the number of available species when compared to PLAZA 4.0, which offered access to 71 species, a 89% overall increase. The PLAZA 5.0 release contains information for 5 882 730 genes, and offers pre-computed gene families and phylogenetic trees for 5 274 684 protein-coding genes. This latest release also comes with a set of new and updated features: a new BED import functionality for the workbench, improved interactive visualizations for functional enrichments and genome-wide mapping of gene sets, and a fully redesigned and extended API. Taken together, this new version offers extended support for plant biologists working on different families within the green plant lineage and provides an efficient and versatile toolbox for plant genomics. All PLAZA releases are accessible from the portal website: https://bioinformatics.psb.ugent.be/plaza/.

A SARS-CoV-2 sequence submission tool for the European Nucleotide Archive.

SUMMARY: Many aspects of the global response to the COVID-19 pandemic are enabled by the fast and open publication of SARS-CoV-2 genetic sequence data. The European Nucleotide Archive (ENA) is the European recommended open repository for genetic sequences. In this work, we present a tool for submitting raw sequencing reads of SARS-CoV-2 to ENA. The tool features a single-step submission process, a graphical user interface, tabular-formatted metadata and the possibility to remove human reads prior to submission. A Galaxy wrap of the tool allows users with little or no bioinformatics knowledge to do bulk sequencing read submissions. The tool is also packed in a Docker container to ease deployment. AVAILABILITY AND IMPLEMENTATION: CLI ENA upload tool is available at github.com/usegalaxy-eu/ena-upload-cli (DOI 10.5281/zenodo.4537621); Galaxy ENA upload tool at toolshed.g2.bx.psu.edu/view/iuc/ena_upload/382518f24d6d and github.com/galaxyproject/tools-iuc/tree/master/tools/ena_upload (development); and ENA upload Galaxy container at github.com/ELIXIR-Belgium/ena-upload-container (DOI 10.5281/zenodo.4730785).

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring.

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org .

The Arabidopsis condensin CAP-D subunits arrange interphase chromatin.

Condensins are best known for their role in shaping chromosomes. Other functions such as organizing interphase chromatin and transcriptional control have been reported in yeasts and animals, but little is known about their function in plants. To elucidate the specific composition of condensin complexes and the expression of CAP-D2 (condensin I) and CAP-D3 (condensin II), we performed biochemical analyses in Arabidopsis. The role of CAP-D3 in interphase chromatin organization and function was evaluated using cytogenetic and transcriptome analysis in cap-d3 T-DNA insertion mutants. CAP-D2 and CAP-D3 are highly expressed in mitotically active tissues. In silico and pull-down experiments indicate that both CAP-D proteins interact with the other condensin I and II subunits. In cap-d3 mutants, an association of heterochromatic sequences occurs, but the nuclear size and the general histone and DNA methylation patterns remain unchanged. Also, CAP-D3 influences the expression of genes affecting the response to water, chemicals, and stress. The expression and composition of the condensin complexes in Arabidopsis are similar to those in other higher eukaryotes. We propose a model for the CAP-D3 function during interphase in which CAP-D3 localizes in euchromatin loops to stiffen them and consequently separates centromeric regions and 45S rDNA repeats.

No more business as usual: Agile and effective responses to emerging pathogen threats require open data and open analytics.

The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies and requires unimpeded access to data, analysis tools, and computational infrastructure. Here, we show that community efforts in developing open analytical software tools over the past 10 years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all SARS-CoV-2 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.

Reactivity of Gypsum-Based Materials Subjected to Thermal Load: Investigation of Reaction Mechanisms.

The thermal stability of gypsum-based materials, and in this context, especially their long-term behavior, is the background of our current research activities. A comprehensive investigation program was compiled in which detailed examinations of various model materials exposed to thermal loads were carried out. The understanding of the partly not entirely consistent state of knowledge shall be sharpened especially by in situ observations of the thermally induced conversion reaction of gypsum into hemihydrate. The temporal course of the reaction was investigated non-destructively by in situ investigations in a high-resolution X-ray computed tomography setup, and the experiment was accompanied by detailed characterizations of the microstructure and composition. In this contribution, selected results of experiments with a high-purity natural gypsum rock as the model substance are presented. Studying the influence of temperature on the reaction showed that, even under supposedly dry conditions, the reaction could take place at much lower temperatures than usually reported in the literature. It was demonstrated that the transformation of gypsum into hemihydrate could take place at a temperature of already 50 °C. The results indicated that even under "classical" heating conditions in a conventional oven, the dissolution and crystallization processes in water films on the mineral surfaces could be suggested to be a driving force for the reaction. A corresponding reaction model, which took these aspects into account, was proposed in this work.

Enabling reusability of plant phenomic datasets with MIAPPE 1.1.

Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.

Plant-RRBS: DNA Methylome Profiling Adjusted to Plant Genomes, Utilizing Efficient Endonuclease Combinations, for Multi-Sample Studies.

In plants, methylation at cytosines often leads to changes in gene expression and inactivation of transposable elements. Changes in cytosine methylation (epimutations) might produce epialleles with distinct phenotypes. We present a genome-wide cytosine methylation profiling method based on bisulfite conversion and next-generation sequencing, which is applicable for plant species with available reference genomes. This so-called plant-RRBS profiling method reproducibly covers specific genomic regions and enriches for coverage of cytosine positions that are suitable for comparative analyses in multi-sample studies in basic biology and breeding studies. The plant-RRBS workflow consists of genomic DNA digestion with coverage-efficient restriction endonuclease combinations followed by a performant library generation and next-generation sequencing and a straightforward, publically available methylation data processing pipeline. Plant-RRBS has a twofold higher ratio of cytosine coverage per covered genome as compared to whole-genome bisulfite sequencing, covering tens of millions of cytosine positions, and allows detection of differential cytosine methylation, which was evaluated using rice epilines.

From invisibility to readability: Recovering the ink of Herculaneum.

The noninvasive digital restoration of ancient texts written in carbon black ink and hidden inside artifacts has proven elusive, even with advanced imaging techniques like x-ray-based micro-computed tomography (micro-CT). This paper identifies a crucial mistaken assumption: that micro-CT data fails to capture any information representing the presence of carbon ink. Instead, we show new experiments indicating a subtle but detectable signature from carbon ink in micro-CT. We demonstrate a new computational approach that captures, enhances, and makes visible the characteristic signature created by carbon ink in micro-CT. This previously "unseen" evidence of carbon inks, which can now successfully be made visible, is a discovery that can lead directly to the noninvasive digital recovery of the lost texts of Herculaneum.

Multifaceted activity of cytokinin in leaf development shapes its size and structure in Arabidopsis.

The phytohormone cytokinin has been shown to affect many aspects of plant development ranging from the regulation of the shoot apical meristem to leaf senescence. However, some studies have reported contradictory effects of cytokinin on leaf physiology. Therefore cytokinin treatments cause both chlorosis and increased greening and both lead to decrease or increase in cell size. To elucidate this multifaceted role of cytokinin in leaf development, we have employed a system of temporal controls over the cytokinin pool and investigated the consequences of modulated cytokinin levels in the third leaf of Arabidopsis. We show that, at the cell proliferation phase, cytokinin is needed to maintain cell proliferation by blocking the transition to cell expansion and the onset of photosynthesis. Transcriptome profiling revealed regulation by cytokinin of a gene suite previously shown to affect cell proliferation and expansion and thereby a molecular mechanism by which cytokinin modulates a molecular network underlying the cellular responses. During the cell expansion phase, cytokinin stimulates cell expansion and differentiation. Consequently, a cytokinin excess at the cell expansion phase results in an increased leaf and rosette size fueled by higher cell expansion rate, yielding higher shoot biomass. Proteome profiling revealed the stimulation of primary metabolism by cytokinin, in line with an increased sugar content that is expected to increase turgor pressure, representing the driving force of cell expansion. Therefore, the developmental timing of cytokinin content fluctuations, together with a tight control of primary metabolism, is a key factor mediating transitions from cell proliferation to cell expansion in leaves.

PLAZA 4.0: an integrative resource for functional, evolutionary and comparative plant genomics.

PLAZA (https://bioinformatics.psb.ugent.be/plaza) is a plant-oriented online resource for comparative, evolutionary and functional genomics. The PLAZA platform consists of multiple independent instances focusing on different plant clades, while also providing access to a consistent set of reference species. Each PLAZA instance contains structural and functional gene annotations, gene family data and phylogenetic trees and detailed gene colinearity information. A user-friendly web interface makes the necessary tools and visualizations accessible, specific for each data type. Here we present PLAZA 4.0, the latest iteration of the PLAZA framework. This version consists of two new instances (Dicots 4.0 and Monocots 4.0) providing a large increase in newly available species, and offers access to updated and newly implemented tools and visualizations, helping users with the ever-increasing demands for complex and in-depth analyzes. The total number of species across both instances nearly doubles from 37 species in PLAZA 3.0 to 71 species in PLAZA 4.0, with a much broader coverage of crop species (e.g. wheat, palm oil) and species of evolutionary interest (e.g. spruce, Marchantia). The new PLAZA instances can also be accessed by a programming interface through a RESTful web service, thus allowing bioinformaticians to optimally leverage the power of the PLAZA platform.