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Leber congenital amaurosis type 10 is a severe retinal dystrophy caused by mutations in the CEP290 gene 1,2 . We developed EDIT-101, a candidate genome-editing therapeutic, to remove the aberrant splice donor created by the IVS26 mutation in the CEP290 gene and restore normal CEP290 expression. Key to this therapeutic, we identified a pair of Staphylococcus aureus Cas9 guide RNAs that were highly active and specific to the human CEP290 target sequence. In vitro experiments in human cells and retinal explants demonstrated the molecular mechanism of action and nuclease specificity. Subretinal delivery of EDIT-101 in humanized CEP290 mice showed rapid and sustained CEP290 gene editing. A comparable surrogate non-human primate (NHP) vector also achieved productive editing of the NHP CEP290 gene at levels that met the target therapeutic threshold, and demonstrated the ability of CRISPR/Cas9 to edit somatic primate cells in vivo. These results support further development of EDIT-101 for LCA10 and additional CRISPR-based medicines for other inherited retinal disorders.

Unlabelled: We present Bioinformatics Autodiscovery of Training Materials (BATMat), an open-source, Google-based, targeted, automatic search tool for training materials related to bioinformatics. BATMat helps gain access with one click to filtered and portable information containing links to existing materials (when present). It also offers functionality to sort results according to source site or title., Availability: http://imbatmat.com, Contact: piar301@gmail.com., (© The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.