Determining the functional attributes of pancreatic transcription factors is essential to understand how the pancreas is specified distinct from other endodermal organs, such as liver, stomach and duodenum, and to direct the differentiation of other cell types into pancreas. Previously, we demonstrated that Pdx1-VP16 was sufficient to convert liver to pancreas. In this paper, we characterize the functional ability of another pancreatic transcription factor, Ptf1a, in promoting ectopic pancreatic fates at early stages throughout the endoderm and later during organogenesis. Using the transthyretin promoter to drive expression in the early liver region/bud of transgenic Xenopus tadpoles, we find that Ptf1a-VP16 is able to convert liver to pancreas. Overexpression of the unmodified Ptf1a on the other hand has no effect in liver but is able to convert stomach and duodenum to pancreas. When overexpressed at earlier embryonic stages throughout the endoderm, Ptf1a activity is similarly limited, whereas Ptf1a-VP16 has increased activity. Interestingly, in all instances we find that Ptf1a-VP16 is only capable of promoting acinar cell fates, whereas Ptf1a promotes both acinar and endocrine fates. Lastly, we demonstrate that, similar to mouse and zebrafish, Xenopus Ptf1a is essential for the initial specification of both endocrine and exocrine cells during normal pancreas development.

Data sharing is becoming more of a requirement as technologies mature and as global research and communications diversify. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access specialized datasets. In many cases, the realities of data acquisition present a significant burden, therefore gaining access to public datasets allows for more robust analyses and broadly enriched data exploration. To answer this demand, the Montreal Neurological Institute has announced its commitment to Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016a,b). As such, the LORIS and CBRAIN (Das et al., 2016) platforms have been tasked with the technical challenges specific to the institutional-level implementation of open data sharing, including: Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for rapid data processing and sharing of software tools.Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.Long term storage (and web access) of data, reducing loss of institutional data assets.Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards.Implementing the vision of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing for the global research community. Our goal is to utilize the years of experience in multi-site collaborative research infrastructure to implement the technical requirements to achieve this level of public data sharing in a practical yet robust manner, in support of accelerating scientific discovery.

Open science can significantly influence the development and translational process of precision medicine in Canada. Precision medicine presents a unique opportunity to improve disease prevention and healthcare, as well as to reduce health-related expenditures. However, the development of precision medicine also brings about economic challenges, such as costly development, high failure rates, and reduced market size in comparison with the traditional blockbuster drug development model. Open science, characterized by principles of open data sharing, fast dissemination of knowledge, cumulative research, and cooperation, presents a unique opportunity to address these economic challenges while also promoting the public good. The Centre of Genomics and Policy at McGill University organized a stakeholders’ workshop in Montreal in March 2018. The workshop entitled “Could Open be the Yellow Brick Road to Precision Medicine?” provided a forum for stakeholders to share experiences and identify common objectives, challenges, and needs to be addressed to promote open science initiatives in precision medicine. The rich presentations and exchanges that took place during the meeting resulted in this consensus paper containing key considerations for open science precision medicine in Canada. Stakeholders would benefit from addressing these considerations as to promote a more coherent and dynamic open science ecosystem for precision medicine.