RESUMEN
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.
RESUMEN
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.
RESUMEN
Human retinal progenitor cells (hRPCs), isolated from fetal retina, require extracellular matrix proteins such as fibronectin or laminin for successful attachment and self-renewal in vitro. Here we have shown that a novel synthetic vitronectin-mimicking surface supports self-renewal and multipotency of hRPCs in a chemically defined culture system. The morphology, adhesion, and proliferation of hRPC were equivalent on a novel vitronectin-mimicking surface (Synthemax) compared to a fibronectin-coated surface. When evaluated using real-time polymerase chain reaction, Western blotting, and flow cytometry, both surfaces maintained self-renewal of hRPCs, as shown by similar expression levels of Sox2, Nestin, cMyc, Klf4, and Pax6, with no change in integrin beta1 and integrin alpha5 expression. We suggest that the use of synthetic, xeno-free surfaces such as Synthemax will be useful for basic research studies, as well as development of translational strategies aimed at using stem cell transplantation to treat disease.