WorldFAIR Project (D10.1) Agriculture-related pollinator data standards use cases report

Although pollination is an essential ecosystem service that sustains life on Earth, data on this vital process is largely scattered or unavailable, limiting our understanding of the current state of pollinators and hindering effective actions for their conservation and sustainable management. In addition to the well-known challenges of biodiversity data management, such as taxonomic accuracy, the recording of biotic interactions like pollination presents further difficulties in proper representation and sharing. Currently, the widely-used standard for representing biodiversity data, Darwin Core, lacks properties that allow for adequately handling biotic interaction data, and there is a need for FAIR vocabularies for properly representing plant-pollinator interactions. Given the importance of mobilising plant-pollinator interaction data also for food production and security, the Research Data Alliance Improving Global Agricultural Data Community of Practice has brought together partners from representative groups to address the challenges of advancing interoperability and mobilising plant-pollinator data for reuse. This report presents an overview of projects, good practices, tools, and examples for creating, managing and sharing data related to plant-pollinator interactions, along with a work plan for conducting pilots in the next phase of the project. We present the main existing data indexing systems and aggregators for plant-pollinator interaction data, as well as citizen science and community-based sourcing initiatives. We also describe current challenges for taxonomic knowledge and present two data models and one semantic tool that will be explored in the next phase. In preparation for the next phase, which will provide best practices and FAIR-aligned guidelines for documenting and sharing plant-pollinator interactions based on pilot efforts with data, this Case Study comprehensively examined the methods and platforms used to create and share such data. By understanding the nature of data from various sources and authors, the alignment of the retrieved datasets with the FAIR principles was also taken into consideration. We discovered that a large amount of data on plant-pollinator interaction is made available as supplementary files of research articles in a diversity of formats and that there are opportunities for improving current practices for data mobilisation in this domain. The diversity of approaches and the absence of appropriate data vocabularies causes confusion, information loss, and the need for complex data interpretation and transformation. Our explorations and analyses provided valuable insights for structuring the next phase of the project, including the selection of the pilot use cases and the development of a ‘FAIR best practices’ guide for sharing plant-pollinator interaction data. This work primarily focuses on enhancing the interoperability of data on plant-pollinator interactions, envisioning its connection with the effort WorldFAIR is undertaking to develop a Cross-Domain Interoperability Framework. Visit WorldFAIR online at http://worldfair-project.eu. WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393

Similarities in drinking behavior of twin's friends: moderation of heritability of alcohol use

Previous research has indicated that friends' drinking may influence alcohol use in adolescents and young adults. We explored whether similarities in the drinking behavior of friends of twins influence the genetic architecture of alcohol use in adolescence and young adulthood. Survey data from The Netherlands Twin Register were available for 1,526 twin pairs aged 16-25 years. We categorized the twin pairs as concordant (both report similar alcohol use in their friends) or discordant for the alcohol use of their friends. Genetic moderator models were tested by carrying out multi-group analyzes in Mplus. Findings showed a significant moderation effect. Genetic factors were more and common environment less important in the explanation of variation in alcohol use in twins discordant for alcohol use of friends than in twins concordant for alcohol use of friend

Stable isotope tagging of epitopes: a highly selective strategy for the identification of major histocompatibility complex class I-associated peptides induced upon viral infection.

Identification of peptides presented in major histocompatibility complex (MHC) class I molecules after viral infection is of strategic importance for vaccine development. Until recently, mass spectrometric identification of virus-induced peptides was based on comparative analysis of peptide pools isolated from uninfected and virus-infected cells. Here we report on a powerful strategy aiming at the rapid, unambiguous identification of naturally processed MHC class I-associated peptides, which are induced by viral infection. The methodology, stable isotope tagging of epitopes (SITE), is based on metabolic labeling of endogenously synthesized proteins during infection. This is accomplished by culturing virus-infected cells with stable isotope-labeled amino acids that are expected to be anchor residues (i.e. residues of the peptide that have amino acid side chains that bind into pockets lining the peptide-binding groove of the MHC class I molecule) for the human leukocyte antigen allele of interest. Subsequently these cells are mixed with an equal number of non-infected cells, which are cultured in normal medium. Finally peptides are acid-eluted from immunoprecipitated MHC molecules and subjected to two-dimensional nanoscale LC-MS analysis. Virus-induced peptides are identified through computer-assisted detection of characteristic, binomially distributed ratios of labeled and unlabeled molecules. Using this approach we identified novel measles virus and respiratory syncytial virus epitopes as well as infection-induced self-peptides in several cell types, showing that SITE is a unique and versatile method for unequivocal identification of disease-related MHC class I epitopes

Predictors of problem drinking in adolescence and young adulthood. A longitudinal twin-family study

We examined drinking behavior of parents, siblings, and friends of twins as predictors of adolescent and young adult problem drinking over a period of 2 and a period of 7 years. Data of 12 to 30-year-old twins and their family members from the Netherlands Twin Register were analyzed. Problem drinking in twins was assessed in 1995 and 2000 and was defined based on the CAGE and amount of drinking. Data on alcohol use of parents, siblings and friends were collected in 1993. Multinomial logistic regression analyses were used to examine the short-term (1993-1995; n = 2,994) and the long-term longitudinal predictors (1993-2000; n = 1,796) of problem drinking. Age, sex and own alcohol use in 1993 explained 25% of the variance in adolescent and young adult problem drinking. Moreover, adolescents and young adults with fathers who drank frequently and with a large numbers of drinking friends, were at the highest risk for problem drinking 2 years later. Over a period of 7 years the number of drinking friends was no longer a risk factor, but few times a week or daily alcohol use of fathers remained a risk factor for later problem drinking. Drinking behavior of mother and siblings did not substantially predict problem drinking. Sex and age did not moderate these effect

Ten (mostly) simple rules to future-proof trait data in ecological and evolutionary sciences

Abstract Traits have become a crucial part of ecological and evolutionary sciences, helping researchers understand the function of an organism's morphology, physiology, growth and life history, with effects on fitness, behaviour, interactions with the environment and ecosystem processes. However, measuring, compiling and analysing trait data comes with data‐scientific challenges. We offer 10 (mostly) simple rules, with some detailed extensions, as a guide in making critical decisions that consider the entire life cycle of trait data. This article is particularly motivated by its last rule, that is, to propagate good practice. It has the intention of bringing awareness of how data on the traits of organisms can be collected and managed for reuse by the research community. Trait observations are relevant to a broad interdisciplinary community of field biologists, synthesis ecologists, evolutionary biologists, computer scientists and database managers. We hope these basic guidelines can be useful as a starter for active communication in disseminating such integrative knowledge and in how to make trait data future‐proof. We invite the scientific community to participate in this effort at http://opentraits.org/best‐practices.html

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

Liberating host–virus knowledge from biological dark data

Connecting basic data about bats and other potential hosts of SARS-CoV-2 with their ecological context is crucial to the understanding of the emergence and spread of the virus. However, when lockdowns in many countries started in March, 2020, the world's bat experts were locked out of their research laboratories, which in turn impeded access to large volumes of offline ecological and taxonomic data. Pandemic lockdowns have brought to attention the long-standing problem of so-called biological dark data: data that are published, but disconnected from digital knowledge resources and thus unavailable for high-throughput analysis. Knowledge of host-to-virus ecological interactions will be biased until this challenge is addressed. In this Viewpoint, we outline two viable solutions: first, in the short term, to interconnect published data about host organisms, viruses, and other pathogens; and second, to shift the publishing framework beyond unstructured text (the so-called PDF prison) to labelled networks of digital knowledge. As the indexing system for biodiversity data, biological taxonomy is foundational to both solutions. Building digitally connected knowledge graphs of host–pathogen interactions will establish the agility needed to quickly identify reservoir hosts of novel zoonoses, allow for more robust predictions of emergence, and thereby strengthen human and planetary health systems.info:eu-repo/semantics/publishedVersio

The Interaction Between Pubertal Timing and Peer Popularity for Boys and Girls: An Integration of Biological and Interpersonal Perspectives on Adolescent Depression

Abstract The transition to adolescence marks a time of sharply increased vulnerability to the development of depression, particularly among girls. Past research has examined isolated risk factors from individual theoretical models (e.g., biological, interpersonal, and cognitive) of depression, but few have examined integrative models. This study investigated the conjoint effects of early pubertal timing and popularity in the longitudinal prediction of depressive symptoms. A total of 319 girls and 294 boys (ages 11-14) provided information on their pubertal status, depressive symptoms, and the social status (i.e., popularity) of their peers. Adolescents completed a second measure of depressive symptoms 11 months after the initial time point. Findings supported an integrated biological-interpersonal model in explaining the development of depressive symptoms during adolescence. Early pubertal development was associated with increase in depressive symptoms only when accompanied by low levels of popularity. High levels of popularity buffered the association between early pubertal development and later depressive symptoms. Unexpectedly, these results were significant both for girls and boys. Results are discussed in terms of dynamic systems theories

Open Science Principles for Accelerating Trait-Based Science Across the Tree of Life

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges