Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info. Both are offered free of charge to the research community.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0953-9) contains supplementary material, which is available to authorized users.

X-linked myotubular myopathy (XLMTM) results from MTM1 gene mutations and myotubularin deficiency. Most XLMTM patients develop severe muscle weakness leading to respiratory failure and death, typically within 2 years of age. Our objective was to evaluate the efficacy and safety of systemic gene therapy in the p.N155K canine model of XLMTM by performing a dose escalation study. A recombinant adeno-associated virus serotype 8 (rAAV8) vector expressing canine myotubularin (cMTM1) under the muscle-specific desmin promoter (rAAV8-cMTM1) was administered by simple peripheral venous infusion in XLMTM dogs at 10 weeks of age, when signs of the disease are already present. A comprehensive analysis of survival, limb strength, gait, respiratory function, neurological assessment, histology, vector biodistribution, transgene expression, and immune response was performed over a 9-month study period. Results indicate that systemic gene therapy was well tolerated, prolonged lifespan, and corrected the skeletal musculature throughout the body in a dose-dependent manner, defining an efficacious dose in this large-animal model of the disease. These results support the development of gene therapy clinical trials for XLMTM.

Renal cell carcinoma is a heterogenous cancer composed of an increasing number of unique subtypes each with their own cellular and tumor behavior. The study of hereditary renal cell carcinoma, which composes just 5% of all types of tumor cases, has allowed for the elucidation of subtype-specific tumorigenesis mechanisms that can also be applied to their sporadic counterparts. This review will focus on the major forms of hereditary renal cell carcinoma and the genetic alterations contributing to their tumorigenesis, including von Hippel Lindau syndrome, Hereditary Papillary Renal Cell Carcinoma, Succinate Dehydrogenase-Deficient Renal Cell Carcinoma, Hereditary Leiomyomatosis and Renal Cell Carcinoma, BRCA Associated Protein 1 Tumor Predisposition Syndrome, Tuberous Sclerosis, Birt–Hogg–Dubé Syndrome and Translocation RCC. The mechanisms for tumorigenesis described in this review are beginning to be exploited via the utilization of novel targets to treat renal cell carcinoma in a subtype-specific fashion.

MyGene.info and MyVariant.info provide high-performance data APIs for querying gene and variant annotation information. They demonstrate a new model for organizing biological annotation information by utilizing a cloud-based scalable infrastructure. MyGene.info and MyVariant.info can be accessed at http://mygene.info and http://myvariant.info. Content:The accumulation of biomedical knowledge is growing exponentially. There have been tremendous efforts seeking to structure research findings as annotations on various biological entities (e.g., genes, genetic variants, pathways). However, these annotations are fragmented among many resources that range greatly in terms of size, funding, and visibility (e.g., Ensembl 1 , Uniprot 2 , PROSITE 3 and Reactome 4 ). Tools for knowledge integration enable more efficient analysis of genome-scale data sets and discovery of relationships between biological entities.Bioinformaticians facing data integration problems generally pursue one of two strategies: data warehousing and data federation. Data warehousing involves downloading flat-files from various sources, writing parsers to process the files, and then loading the parsed data in a local database. This strategy has the advantage of very high performance, but also requires significant initial effort to write the parsers and ongoing effort to keep the resource

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