The reuse of public datasets in the life sciences: potential risks and rewards

Best practices for data management and sharing in experimental biomedical research

Effective data management is crucial for scientific integrity and reproducibility, a cornerstone of scientific progress. Well-organized and well-documented data enable validation and building on results. Data management encompasses activities including organization, documentation, storage, sharing, and preservation. Robust data management establishes credibility, fostering trust within the scientific community and benefiting researchers' careers. In experimental biomedicine, comprehensive data management is vital due to the typically intricate protocols, extensive metadata, and large datasets. Low-throughput experiments, in particular, require careful management to address variations and errors in protocols and raw data quality. Transparent and accountable research practices rely on accurate documentation of procedures, data collection, and analysis methods. Proper data management ensures long-term preservation and accessibility of valuable datasets. Well-managed data can be revisited, contributing to cumulative knowledge and potential new discoveries. Publicly funded research has an added responsibility for transparency, resource allocation, and avoiding redundancy. Meeting funding agency expectations increasingly requires rigorous methodologies, adherence to standards, comprehensive documentation, and widespread sharing of data, code, and other auxiliary resources. This review provides critical insights into raw and processed data, metadata, high-throughput versus low-throughput datasets, a common language for documentation, experimental and reporting guidelines, efficient data management systems, sharing practices, and relevant repositories. We systematically present available resources and optimal practices for wide use by experimental biomedical researchers.

PM2.5, component cause of severe metabolically abnormal obesity: An in silico, observational and analytical study

Obesity is currently one of the most alarming pathological conditions due to the progressive increase in its prevalence. In the last decade, it has been associated with fine particulate matter suspended in the air (PM2.5). The purpose of this study was to explore the mechanistic interaction of PM2.5 with a high-fat diet (HFD) through the differential regulation of transcriptional signatures, aiming to identify the association of these particles with metabolically abnormal obesity. The research design was observational, using bioinformatic methods and an explanatory approach based on Rothman's causal model. We propose three new transcriptional signatures in murine adipose tissue. The sum of transcriptional differences between the group exposed to an HFD and PM2.5, compared to the control group, were 0.851, 0.265, and -0.047 (p > 0.05). The HFD group increased body mass by 20% with two positive biomarkers of metabolic impact. The group exposed to PM2.5 maintained a similar weight to the control group but exhibited three positive biomarkers. Enriched biological pathways (p < 0.05) included PPAR signaling, small molecule transport, adipogenesis genes, cytokine-cytokine receptor interaction, and HIF-1 signaling. Transcriptional regulation predictions revealed CpG islands and common transcription factors. We propose three new transcriptional signatures: FAT-PM2.5-CEJUS, FAT-PM2.5-UP, and FAT-PM2.5-DN, whose transcriptional regulation profile in adipocytes was statistically similar by dietary intake and HFD and exposure to PM2.5 in mice; suggesting a mechanistic interaction between both factors. However, HFD-exposed murines developed moderate metabolically abnormal obesity, and PM2.5-exposed murines developed severe abnormal metabolism without obesity. Therefore, in Rothman's terms, it is concluded that HFD is a sufficient cause of the development of obesity, and PM2.5 is a component cause of severe abnormal metabolism of obesity. These signatures would be integrated into a systemic biological process that would induce transcriptional regulation in trans, activating obesogenic biological pathways, restricting lipid mobilization pathways, decreasing adaptive thermogenesis and angiogenesis, and altering vascular tone thus inducing a severe metabolically abnormal obesity.

Principles, policies, and practices: Thoughts on their integration over the rise of the developmental psychopathology perspective and into the future

Developmental psychopathology has, since the late 20th century, offered an influential integrative framework for conceptualizing psychological health, distress, and dysfunction across the lifespan. Leaders in the field have periodically generated predictions about its future and have proposed ways to increase the macroparadigm's impact. In this paper, we examine, using articles sampled from each decade of the journal Development and Psychopathology's existence as a rough guide, the degree to which the themes that earlier predictions have emphasized have come to fruition and the ways in which the field might further capitalize on the strengths of this approach to advance knowledge and practice in psychology. We focus in particular on two key themes first, we explore the degree to which researchers have capitalized on the framework's capacity for principled flexibility to generate novel work that integrates neurobiological and/or social-contextual factors measured at multiple levels and offer ideas for moving this kind of work forward. Second, we discuss how extensively articles have emphasized implications for intervention or prevention and how the field might amplify the voice of developmental psychopathology in applied settings.

Variability in drought gene expression datasets highlight the need for community standardization

Physiologically relevant drought stress is difficult to apply consistently, and the heterogeneity in experimental design, growth conditions, and sampling schemes make it challenging to compare water deficit studies in plants. Here, we re-analyzed hundreds of drought gene expression experiments across diverse model and crop species and quantified the variability across studies. We found that drought studies are surprisingly uncomparable, even when accounting for differences in genotype, environment, drought severity, and method of drying. Many studies, including most Arabidopsis work, lack high-quality phenotypic and physiological datasets to accompany gene expression, making it impossible to assess the severity or in some cases the occurrence of water deficit stress events. From these datasets, we developed supervised learning classifiers that can accurately predict if RNA-seq samples have experienced a physiologically relevant drought stress, and suggest this can be used as a quality control for future studies. Together, our analyses highlight the need for more community standardization, and the importance of paired physiology data to quantify stress severity for reproducibility and future data analyses.

The knowledge and reuse practices of researchers utilising government health information assets, Victoria, Australia, 2008-2020

BACKGROUND

Using government health datasets for secondary purposes is widespread; however, little is known on researchers' knowledge and reuse practices within Australia.

OBJECTIVES

To explore researchers' knowledge and experience of governance processes, and their data reuse practices, when using Victorian government health datasets for research between 2008-2020.

METHOD

A cross-sectional quantitative survey was conducted with authors who utilised selected Victorian, Australia, government health datasets for peer-reviewed research published between 2008-2020. Information was collected on researchers': data reuse practices; knowledge of government health information assets; perceptions of data trustworthiness for reuse; and demographic characteristics.

RESULTS

When researchers used government health datasets, 45% linked their data, 45% found the data access process easy and 27% found it difficult. Government-curated datasets were significantly more difficult to access compared to other-agency curated datasets (p = 0.009). Many respondents received their data in less than six months (58%), in aggregated or de-identified form (76%). Most reported performing their own data validation checks (70%). To assist in data reuse, almost 71% of researchers utilised (or created) contextual documentation, 69% a data dictionary, and 62% limitations documentation. Almost 20% of respondents were not aware if data quality information existed for the dataset they had accessed. Researchers reported data was managed by custodians with rigorous confidentiality/privacy processes (94%) and good data quality processes (76%), yet half lacked knowledge of what these processes entailed. Many respondents (78%) were unaware if dataset owners had obtained consent from the dataset subjects for research applications of the data.

CONCLUSION

Confidentiality/privacy processes and quality control activities undertaken by data custodians were well-regarded. Many respondents included data linkage to additional government datasets in their research. Ease of data access was variable. Some documentation types were well provided and used, but improvement is required for the provision of data quality statements and limitations documentation. Provision of information on participants' informed consent in a dataset is required.

Data literacy in genome research

With an ever increasing amount of research data available, it becomes constantly more important to possess data literacy skills to benefit from this valuable resource. An integrative course was developed to teach students the fundamentals of data literacy through an engaging genome sequencing project. Each cohort of students performed planning of the experiment, DNA extraction, nanopore sequencing, genome sequence assembly, prediction of genes in the assembled sequence, and assignment of functional annotation terms to predicted genes. Students learned how to communicate science through writing a protocol in the form of a scientific paper, providing comments during a peer-review process, and presenting their findings as part of an international symposium. Many students enjoyed the opportunity to own a project and to work towards a meaningful objective.

The suitability of government health information assets for secondary use in research: A fit-for-purpose analysis

BACKGROUND

Governments have responsibility for ensuring the quality and fitness-for-purpose of personal health data provided to them. While these health information assets are used widely for research, this secondary usage has received minimal research attention.

OBJECTIVE

This study aimed to investigate the secondary uses, in research, of population health and administrative datasets (information assets) of the Department of Health (DoH), Victoria, Australia. The objectives were to (i) identify research based on these datasets published between 2008 and 2020; (ii) describe the data quality studies published between 2008 and 2020 for each dataset and (iii) evaluate "fitness-for-purpose" of the published research.

METHOD

Using a modified scoping review, research publications from 2008 to 2020 based on information assets related to health service provision and containing person-level data were reviewed. Publications were summarised by data quality and purpose-categories based on a taxonomy of data use. Fitness-for-purpose was evaluated by comparing the publicly stated purpose(s) for which each information asset was collected, with the purpose(s) assigned to the published research.

RESULTS

Of the >1000 information assets, 28 were utilised in 756 publications: 54% were utilised for general research purposes, 14% for patient safety, 10% for quality of care and 39% included data quality-related publications. Almost 85% of publications used information assets that were fit-for-purpose.

CONCLUSION

The DoH information assets were used widely for secondary purposes, with the majority identified as fit-for-purpose. We recommend that data custodians, including governments, provide information on data quality and transparency on data use of their health information assets.

Maximizing the utility of public data

The human genome project galvanized the scientific community around an ambitious goal. Upon completion, the project delivered several discoveries, and a new era of research commenced. More importantly, novel technologies and analysis methods materialized during the project period. The cost reduction allowed many more labs to generate high-throughput datasets. The project also served as a model for other extensive collaborations that generated large datasets. These datasets were made public and continue to accumulate in repositories. As a result, the scientific community should consider how these data can be utilized effectively for the purposes of research and the public good. A dataset can be re-analyzed, curated, or integrated with other forms of data to enhance its utility. We highlight three important areas to achieve this goal in this brief perspective. We also emphasize the critical requirements for these strategies to be successful. We draw on our own experience and others in using publicly available datasets to support, develop, and extend our research interest. Finally, we underline the beneficiaries and discuss some risks involved in data reuse.

Introduction of the Korea BioData Station (K-BDS) for sharing biological data

A wave of new technologies has created opportunities for the cost-effective generation of high-throughput profiles of biological systems, foreshadowing a "data-driven science" era. The large variety of data available from biological research is also a rich resource that can be used for innovative endeavors. However, we are facing considerable challenges in big data deposition, integration, and translation due to the complexity of biological data and its production at unprecedented exponential rates. To address these problems, in 2020, the Korean government officially announced a national strategy to collect and manage the biological data produced through national R&D fund allocations and provide the collected data to researchers. To this end, the Korea Bioinformation Center (KOBIC) developed a new biological data repository, the Korea BioData Station (K-BDS), for sharing data from individual researchers and research programs to create a data-driven biological study environment. The K-BDS is dedicated to providing free open access to a suite of featured data resources in support of worldwide activities in both academia and industry.

Excel-SBOL Converter: Creating SBOL from Excel Templates and Vice Versa

Standards support synthetic biology research by enabling the exchange of component information. However, using formal representations, such as the Synthetic Biology Open Language (SBOL), typically requires either a thorough understanding of these standards or a suite of tools developed in concurrence with the ontologies. Since these tools may be a barrier for use by many practitioners, the Excel-SBOL Converter was developed to facilitate the use of SBOL and integration into existing workflows. The converter consists of two Python libraries: one that converts Excel templates to SBOL and another that converts SBOL to an Excel workbook. Both libraries can be used either directly or via a SynBioHub plugin.

Exploring the Potential of Metatranscriptomics to Describe Microbial Communities and Their Effects in Molluscs

Metatranscriptomics has emerged as a very useful technology for the study of microbiomes from RNA-seq reads. This method provides additional information compared to the sequencing of ribosomal genes because the gene expression can also be analysed. In this work, we used the metatranscriptomic approach to study the whole microbiome of mussels, including bacteria, viruses, fungi, and protozoans, by mapping the RNA-seq reads to custom assembly databases (including the genomes of microorganisms publicly available). This strategy allowed us not only to describe the diversity of microorganisms but also to relate the host transcriptome and microbiome, finding the genes more affected by the pathogen load. Although some bacteria abundant in the metatranscriptomic analysis were undetectable by 16S rRNA sequencing, a common core of the taxa was detected by both methodologies (62% of the metatranscriptomic detections were also identified by 16S rRNA sequencing, the Oceanospirillales, Flavobacteriales and Vibrionales orders being the most relevant). However, the differences in the microbiome composition were observed among different tissues of Mytilus galloprovincialis, with the fungal kingdom being especially diverse, or among molluscan species. These results confirm the potential of a meta-analysis of transcriptome data to obtain new information on the molluscs' microbiome.

Data preservation practices for enhancing agricultural research data usage among agricultural researchers in Tanzania

The objective of this study was to investigate the role of research data preservation for enhanced data usage among agricultural researchers in Tanzania. Specifically, the study aimed to examine the data preservation methods used by agriculture researchers, find out how long agriculture researchers preserve their agriculture research data, and determine factors that influence agriculture researchers on their choice of data preservation methods for use. The study employed a cross-sectional research design. The study employed both qualitative and quantitative approaches. A survey was conducted to collect data in 11 research institutions. A simple random sampling technique was used to select 204 respondents from the study area while purposive sampling techniques were used to select 11 agriculture research institutions including 10 Tanzanian Agricultural Research Institution (TARI) centers, and Sokoine University of Agriculture (SUA). Also, 12 respondents were selected purposively for an in-depth interview as key informants. The study adopted Data Curation Centre (DCC) Lifecycle Model to explain data preservation process. Findings indicated that a majority of more than 90% of researchers preferred to preserve their data using different storage devices such as field notebooks, computers, and institutional libraries. Moreover, findings indicated that about 74% of agricultural researchers preferred to preserve their data for more than 6 years after the end of the project. Findings also indicated factors that influence researchers in the choice of data preservation methods to be easy to reach, cost-effective storage devices, support to use the devices, adequate infrastructure for data preservation, and reliable power supply. It can be concluded that there is yet a great role of research data preservation in enhancing data usage among researchers in Tanzania. It is recommended that the government should establish an agricultural research data bank to guarantee permanent availability of data at all times when needed.

New Insights into the Identity of the DFNA58 Gene

Hearing loss is the most common sensory deficit, affecting 466 million people worldwide. The vast and diverse genes involved reflect the complexity of auditory physiology, which requires the use of animal models in order to gain a fuller understanding. Among the loci with a yet-to-be validated gene is the DFNA58, in which ~200 Kb genomic duplication, including three protein-coding genes (PLEK, CNRIP1, and PPP3R1's exon1), was found to segregate with autosomal dominant hearing loss. Through whole genome sequencing, the duplication was found to be in tandem and inserted in an intergenic region, without the disruption of the topological domains. Reanalysis of transcriptomes data studies (zebrafish and mouse), and RT-qPCR analysis of adult zebrafish target organs, in order to access their orthologues expression, highlighted promising results with Cnrip1a, corroborated by zebrafish in situ hybridization and immunofluorescence. Mouse data also suggested Cnrip1 as the best candidate for a relevant role in auditory physiology, and its importance in hearing seems to have remained conserved but the cell type exerting its function might have changed, from hair cells to spiral ganglion neurons.

Transcriptomic meta-analysis reveals unannotated long non-coding RNAs related to the immune response in sheep

Long non-coding RNAs (lncRNAs) are involved in several biological processes, including the immune system response to pathogens and vaccines. The annotation and functional characterization of lncRNAs is more advanced in humans than in livestock species. Here, we take advantage of the increasing number of high-throughput functional experiments deposited in public databases in order to uniformly analyse, profile unannotated lncRNAs and integrate 422 ovine RNA-seq samples from the ovine immune system. We identified 12302 unannotated lncRNA genes with support from independent CAGE-seq and histone modification ChIP-seq assays. Unannotated lncRNAs showed low expression levels and sequence conservation across other mammal species. There were differences in expression levels depending on the genomic location-based lncRNA classification. Differential expression analyses between unstimulated and samples stimulated with pathogen infection or vaccination resulted in hundreds of lncRNAs with changed expression. Gene co-expression analyses revealed immune gene-enriched clusters associated with immune system activation and related to interferon signalling, antiviral response or endoplasmic reticulum stress. Besides, differential co-expression networks were constructed in order to find condition-specific relationships between coding genes and lncRNAs. Overall, using a diverse set of immune system samples and bioinformatic approaches we identify several ovine lncRNAs associated with the response to an external stimulus. These findings help in the improvement of the ovine lncRNA catalogue and provide sheep-specific evidence for the implication in the general immune response for several lncRNAs.

Seven steps to enhance Open Science practices in animal science

The Open Science movement aims at ensuring accessibility, reproducibility, and transparency of research. The adoption of Open Science practices in animal science, however, is still at an early stage. To move ahead as a field, we here provide seven practical steps to embrace Open Science in animal science. We hope that this paper contributes to the shift in research practices of animal scientists towards open, reproducible, and transparent science, enabling the field to gain additional public trust and deal with future challenges to guarantee reliable research. Although the paper targets primarily animal science researchers, the steps discussed here are also applicable to other research domains.

Recommendations for the formatting of Variant Call Format (VCF) files to make plant genotyping data FAIR

In this opinion article, we discuss the formatting of files from (plant) genotyping studies, in particular the formatting of metadata in Variant Call Format (VCF) files. The flexibility of the VCF format specification facilitates its use as a generic interchange format across domains but can lead to inconsistency between files in the presentation of metadata. To enable fully autonomous machine actionable data flow, generic elements need to be further specified. We strongly support the merits of the FAIR principles and see the need to facilitate them also through technical implementation specifications. They form a basis for the proposed VCF extensions here. We have learned from the existing application of VCF that the definition of relevant metadata using controlled standards, vocabulary and the consistent use of cross-references via resolvable identifiers (machine-readable) are particularly necessary and propose their encoding. VCF is an established standard for the exchange and publication of genotyping data. Other data formats are also used to capture variant data (for example, the HapMap and the gVCF formats), but none currently have the reach of VCF. For the sake of simplicity, we will only discuss VCF and our recommendations for its use, but these recommendations could also be applied to gVCF. However, the part of the VCF standard relating to metadata (as opposed to the actual variant calls) defines a syntactic format but no vocabulary, unique identifier or recommended content. In practice, often only sparse descriptive metadata is included. When descriptive metadata is provided, proprietary metadata fields are frequently added that have not been agreed upon within the community which may limit long-term and comprehensive interoperability. To address this, we propose recommendations for supplying and encoding metadata, focusing on use cases from plant sciences. We expect there to be overlap, but also divergence, with the needs of other domains.

Considerations for an integrated population health databank in Africa: lessons from global best practices

Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa.

Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing.

Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing.  We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access.

Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

The Changes in the p53 Protein across the Animal Kingdom Point to Its Involvement in Longevity

Recently, the quest for the mythical fountain of youth has produced extensive research programs that aim to extend the healthy lifespan of humans. Despite advances in our understanding of the aging process, the surprisingly extended lifespan and cancer resistance of some animal species remain unexplained. The p53 protein plays a crucial role in tumor suppression, tissue homeostasis, and aging. Long-lived, cancer-free African elephants have 20 copies of the TP53 gene, including 19 retrogenes (38 alleles), which are partially active, whereas humans possess only one copy of TP53 and have an estimated cancer mortality rate of 11–25%. The mechanism through which p53 contributes to the resolution of the Peto’s paradox in Animalia remains vague. Thus, in this work, we took advantage of the available datasets and inspected the p53 amino acid sequence of phylogenetically related organisms that show variations in their lifespans. We discovered new correlations between specific amino acid deviations in p53 and the lifespans across different animal species. We found that species with extended lifespans have certain characteristic amino acid substitutions in the p53 DNA-binding domain that alter its function, as depicted from the Phenotypic Annotation of p53 Mutations, using the PROVEAN tool or SWISS-MODEL workflow. In addition, the loop 2 region of the human p53 DNA-binding domain was identified as the longest region that was associated with longevity. The 3D model revealed variations in the loop 2 structure in long-lived species when compared with human p53. Our findings show a direct association between specific amino acid residues in p53 protein, changes in p53 functionality, and the extended animal lifespan, and further highlight the importance of p53 protein in aging.