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Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts., (© The Author(s) 2024. Published by Oxford University Press.)

The Solve-RD project objectives include solving undiagnosed rare diseases (RD) through collaborative research on shared genome-phenome datasets. The RD-Connect Genome-Phenome Analysis Platform (GPAP), for data collation and analysis, and the European Genome-Phenome Archive (EGA), for file storage, are two key components of the Solve-RD infrastructure. Clinical researchers can identify candidate genetic variants within the RD-Connect GPAP and, thanks to the developments presented here as part of joint ELIXIR activities, are able to remotely visualize the corresponding alignments stored at the EGA. The Global Alliance for Genomics and Health (GA4GH) htsget streaming application programming interface (API) is used to retrieve alignment slices, which are rendered by an integrated genome viewer (IGV) instance embedded in the GPAP. As a result, it is no longer necessary for over 11,000 datasets to download large alignment files to visualize them locally. This work highlights the advantages, from both the user and infrastructure perspectives, of implementing interoperability standards for establishing federated genomics data networks., Competing Interests: The authors declare that they have no conflict of interest., (© 2023 The Authors.)

The European Genome-phenome Archive (EGA - https://ega-archive.org/) is a resource for long term secure archiving of all types of potentially identifiable genetic, phenotypic, and clinical data resulting from biomedical research projects. Its mission is to foster hosted data reuse, enable reproducibility, and accelerate biomedical and translational research in line with the FAIR principles. Launched in 2008, the EGA has grown quickly, currently archiving over 4,500 studies from nearly one thousand institutions. The EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA, therefore, the submitter keeps control on who has access to the data and under which conditions. Given the size and value of data hosted, the EGA is constantly improving its value chain, that is, how the EGA can contribute to enhancing the value of human health data by facilitating its submission, discovery, access, and distribution, as well as leading the design and implementation of standards and methods necessary to deliver the value chain. The EGA has become a key GA4GH Driver Project, leading multiple development efforts and implementing new standards and tools, and has been appointed as an ELIXIR Core Data Resource., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide., Competing Interests: M.N.C. is an employee of Foundation Medicine and equity holder of Roche. A.A.P. is a venture partner at GV and an employee of alphabet corporation. He has received funding from MSFT, Verily, IBM, Intel, Bayer, and Novartis. The views expressed by L.L.R. are the author’s own and do not necessarily represent those of her organization., (© 2021 The Author(s).)

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

In hypoxic stress conditions, glycolysis enzymes assemble into singular cytoplasmic granules called glycolytic (G) bodies. G body formation in yeast correlates with increased glucose consumption and cell survival. However, the physical properties and organizing principles that define G body formation are unclear. We demonstrate that glycolysis enzymes are non-canonical RNA binding proteins, sharing many common mRNA substrates that are also integral constituents of G bodies. Targeting nonspecific endoribonucleases to G bodies reveals that RNA nucleates G body formation and maintains its structural integrity. Consistent with a phase separation mechanism of biogenesis, recruitment of glycolysis enzymes to G bodies relies on multivalent homotypic and heterotypic interactions. Furthermore, G bodies fuse in vivo and are largely insensitive to 1,6-hexanediol, consistent with a hydrogel-like composition. Taken together, our results elucidate the biophysical nature of G bodies and demonstrate that RNA nucleates phase separation of the glycolysis machinery in response to hypoxic stress., Competing Interests: GF, TH, MF, JM, AG, NR, JY, SM, JK No competing interests declared, (© 2020, Fuller et al.)

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org., (Copyright © 2018. Published by Elsevier Inc.)

A novel antisense transcript was identified in the human telomerase reverse transcriptase ( hTERT ) promoter region, suggesting that the hTERT promoter is bidirectional. This transcript, named hTERT antisense promoter-associated ( hTAPAS ) RNA, is a 1.6 kb long non-coding RNA. hTAPAS transcription is initiated 167 nucleotides upstream of the hTERT transcription start site and is present in both the nucleus and the cytoplasm. Surprisingly, we observed that a large fraction of the hTERT polyadenylated RNA is localized in the nucleus, suggesting this might be an additional means of regulating the cellular abundance of hTERT protein. Both hTAPAS and hTERT are expressed in immortalized B-cells and human embryonic stem cells but are not detected in normal somatic cells. hTAPAS expression inversely correlates with hTERT expression in different types of cancer samples. Moreover, hTAPAS expression is not promoted by an hTERT promoter mutation (-124 C>T). Antisense-oligonucleotide mediated knockdown of hTAPAS results in an increase in hTERT expression. Conversely, ectopic overexpression of hTAPAS down regulates hTERT expression, suggesting a negative role in hTERT gene regulation. These observations provide insights into hTAPAS as a novel player that negatively regulates hTERT expression and may be involved in telomere length homeostasis., Competing Interests: The authors declare no conflict of interest.

Glycolysis is upregulated under conditions such as hypoxia and high energy demand to promote cell proliferation, although the mechanism remains poorly understood. We find that hypoxia in Saccharomyces cerevisiae induces concentration of glycolytic enzymes, including the Pfk2p subunit of the rate-limiting phosphofructokinase, into a single, non-membrane-bound granule termed the "glycolytic body" or "G body." A yeast kinome screen identifies the yeast ortholog of AMP-activated protein kinase, Snf1p, as necessary for G-body formation. Many G-body components identified by proteomics are required for G-body integrity. Cells incapable of forming G bodies in hypoxia display abnormal cell division and produce inviable daughter cells. Conversely, cells with G bodies show increased glucose consumption and decreased levels of glycolytic intermediates. Importantly, G bodies form in human hepatocarcinoma cells in hypoxia. Together, our results suggest that G body formation is a conserved, adaptive response to increase glycolytic output during hypoxia or tumorigenesis., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

The RNA binding protein, LARP1, has been proposed to function downstream of mTORC1 to regulate the translation of 5'TOP mRNAs such as those encoding ribosome proteins (RP). However, the roles of LARP1 in the translation of 5'TOP mRNAs are controversial and its regulatory roles in mTORC1-mediated translation remain unclear. Here we show that LARP1 is a direct substrate of mTORC1 and Akt/S6K1. Deep sequencing of LARP1-bound mRNAs reveal that non-phosphorylated LARP1 interacts with both 5' and 3'UTRs of RP mRNAs and inhibits their translation. Importantly, phosphorylation of LARP1 by mTORC1 and Akt/S6K1 dissociates it from 5'UTRs and relieves its inhibitory activity on RP mRNA translation. Concomitantly, phosphorylated LARP1 scaffolds mTORC1 on the 3'UTRs of translationally-competent RP mRNAs to facilitate mTORC1-dependent induction of translation initiation. Thus, in response to cellular mTOR activity, LARP1 serves as a phosphorylation-sensitive molecular switch for turning off or on RP mRNA translation and subsequent ribosome biogenesis.

Germline-expressed endogenous small interfering RNAs (endo-siRNAs) transmit multigenerational epigenetic information to ensure fertility in subsequent generations. In Caenorhabditis elegans, nuclear RNAi ensures robust inheritance of endo-siRNAs and deposition of repressive H3K9me3 marks at target loci. How target silencing is maintained in subsequent generations is poorly understood. We discovered that morc-1 is essential for transgenerational fertility and acts as an effector of endo-siRNAs. Unexpectedly, morc-1 is dispensable for siRNA inheritance but is required for target silencing and maintenance of siRNA-dependent chromatin organization. A forward genetic screen identified mutations in met-1, which encodes an H3K36 methyltransferase, as potent suppressors of morc-1(-) and nuclear RNAi mutant phenotypes. Further analysis of nuclear RNAi and morc-1(-) mutants revealed a progressive, met-1-dependent enrichment of H3K36me3, suggesting that robust fertility requires repression of MET-1 activity at nuclear RNAi targets. Without MORC-1 and nuclear RNAi, MET-1-mediated encroachment of euchromatin leads to detrimental decondensation of germline chromatin and germline mortality., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Protein-RNA interactions are integral components of posttranscriptional gene regulatory processes including mRNA processing and assembly of cellular architectures. Dysregulation of RNA-binding protein (RBP) expression or disruptions in RBP-RNA interactions underlie a variety of human pathologies and genetic diseases including cancer and neurodegenerative diseases (reviewed in (Cooper et al., Cell 136(4):777-793, 2009; Darnell, Cancer Res Treat 42(3):125-129, 2010; Lukong et al., Trends Genet 24 (8):416-425, 2008)). Recent studies have uncovered only a small proportion of the extensive RBP-RNA interactome in any organism (Baltz et al., Mol Cell 46(5):674-690, 2012; Castello et al., Cell 149(6):1393-1406, 2012; Freeberg et al., Genome Biol 14(2):R13, 2013; Hogan et al., PLoS Biol 6(10):e255, 2008; Mitchell et al., Nat Struct Mol Biol 20(1):127-133, 2013; Tsvetanova et al. PLoS One 5(9): pii: e12671, 2010; Schueler et al., Genome Biol 15(1):R15, 2014; Silverman et al., Genome Biol 15(1):R3, 2014). To expand our understanding of how RBP-RNA interactions govern RNA-related processes, we developed gPAR-CLIP-seq (global photoactivatable-ribonucleoside-enhanced cross-linking and precipitation followed by deep sequencing) for capturing and sequencing all regions of the Saccharomyces cerevisiae transcriptome bound by RBPs (Freeberg et al., Genome Biol 14(2):R13, 2013). This chapter describes a pipeline for bioinformatic analysis of gPAR-CLIP-seq data. The first half of this pipeline can be implemented by running locally installed programs or by running the programs using the Galaxy platform (Blankenberg et al., Curr Protoc Mol Biol. Chapter 19:Unit 19 10 11-21, 2010; Giardine et al., Genome Res 15 (10):1451-1455, 2005; Goecks et al., Genome Biol 11(8):R86, 2010). The second half of this pipeline can be implemented by user-generated code in any language using the pseudocode provided as a template.

MicroRNAs (miRNAs) play essential, conserved roles in diverse developmental processes through association with the miRNA-induced silencing complex (miRISC). Whereas fundamental insights into the mechanistic framework of miRNA biogenesis and target gene silencing have been established, posttranslational modifications that affect miRISC function are less well understood. Here we report that the conserved serine/threonine kinase, casein kinase II (CK2), promotes miRISC function in Caenorhabditis elegans. CK2 inactivation results in developmental defects that phenocopy loss of miRISC cofactors and enhances the loss of miRNA function in diverse cellular contexts. Whereas CK2 is dispensable for miRNA biogenesis and the stability of miRISC cofactors, it is required for efficient miRISC target mRNA binding and silencing. Importantly, we identify the conserved DEAD-box RNA helicase, CGH-1/DDX6, as a key CK2 substrate within miRISC and demonstrate phosphorylation of a conserved N-terminal serine is required for CGH-1 function in the miRNA pathway.

Background: Autophagy as a conserved lysosomal/vacuolar degradation and recycling pathway is important in normal development and physiology, and defects in this process are linked to many kinds of disease. Because too much or too little autophagy can be detrimental, the process must be tightly regulated both temporally and in magnitude. Two parameters that affect this regulation are the size and the number of autophagosomes; however, although we know that the amount of Atg8 affects the size of autophagosomes, the mechanism for regulating their number has not been elucidated. The transcriptional induction and repression of the autophagy-related (ATG) genes is one crucial aspect of autophagy regulation, but the transcriptional regulators that modulate autophagy are not well characterized., Results: We detected increased expression levels of ATG genes, and elevated autophagy activity, in cells lacking the transcriptional regulator Pho23. Using transmission electron microscopy, we found that PHO23 null mutant cells contain significantly more autophagosomes than the wild-type. By RNA sequencing transcriptome profiling, we identified ATG9 as one of the key targets of Pho23, and our studies with strains expressing modulated levels of Atg9 show that the amount of this protein directly correlates with the frequency of autophagosome formation and the level of autophagy activity., Conclusions: Our results identified Pho23 as a master transcriptional repressor for autophagy that regulates the frequency of autophagosome formation through its negative regulation of ATG9., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Background: Protein-RNA interactions are integral components of nearly every aspect of biology, including regulation of gene expression, assembly of cellular architectures, and pathogenesis of human diseases. However, studies in the past few decades have only uncovered a small fraction of the vast landscape of the protein-RNA interactome in any organism, and even less is known about the dynamics of protein-RNA interactions under changing developmental and environmental conditions., Results: Here, we describe the gPAR-CLIP (global photoactivatable-ribonucleoside-enhanced crosslinking and immunopurification) approach for capturing regions of the untranslated, polyadenylated transcriptome bound by RNA-binding proteins (RBPs) in budding yeast. We report over 13,000 RBP crosslinking sites in untranslated regions (UTRs) covering 72% of protein-coding transcripts encoded in the genome, confirming 3' UTRs as major sites for RBP interaction. Comparative genomic analyses reveal that RBP crosslinking sites are highly conserved, and RNA folding predictions indicate that secondary structural elements are constrained by protein binding and may serve as generalizable modes of RNA recognition. Finally, 38% of 3' UTR crosslinking sites show changes in RBP occupancy upon glucose or nitrogen deprivation, with major impacts on metabolic pathways as well as mitochondrial and ribosomal gene expression., Conclusions: Our study offers an unprecedented view of the pervasiveness and dynamics of protein-RNA interactions in vivo.

Piwi-interacting RNAs (piRNAs) fulfill a critical, conserved role in defending the genome against foreign genetic elements. In many organisms, piRNAs appear to be derived from processing of a long, polycistronic RNA precursor. Here, we establish that each Caenorhabditis elegans piRNA represents a tiny, autonomous transcriptional unit. Remarkably, the minimal C. elegans piRNA cassette requires only a 21 nucleotide (nt) piRNA sequence and an ∼50 nt upstream motif with limited genomic context for expression. Combining computational analyses with a novel, in vivo transgenic system, we demonstrate that this upstream motif is necessary for independent expression of a germline-enriched, Piwi-dependent piRNA. We further show that a single nucleotide position within this motif directs differential germline enrichment. Accordingly, over 70% of C. elegans piRNAs are selectively expressed in male or female germline, and comparison of the genes they target suggests that these two populations have evolved independently. Together, our results indicate that C. elegans piRNA upstream motifs act as independent promoters to specify which sequences are expressed as piRNAs, how abundantly they are expressed, and in what germline. As the genome encodes well over 15,000 unique piRNA sequences, our study reveals that the number of transcriptional units encoding piRNAs rivals the number of mRNA coding genes in the C. elegans genome., Competing Interests: The authors have declared that no competing interests exist.

Caenorhabditis elegans piRNAs promote genome surveillance by triggering siRNA-mediated silencing of nonself DNA in competition with licensing programs that support endogenous gene expression.