Disease and phenotype data at Ensembl

Reporting of Clinical Genome Sequencing Results

High-throughput sequencing and high-performance computing technologies have become powerful tools in clinical genetic diagnosis of hereditary disorders and genetic screening of healthy individuals to provide information for the diagnosis, treatment, and prevention of diseases or impairment and assessment of health. For patients with undiagnosed disorders, including many rare disorders, the whole-genome sequencing (WGS) test may end the diagnostic odyssey, ultimately guiding clinical care for them and their families. A clinical WGS test relies on high-quality genome-sequencing data as well as sophisticated data-interpretation approaches. Results are returned to the ordering physician in a concise report featuring an overall test result and in-depth phenotype-driven interpretation of the known or plausible genetic explanation of test indications. Patients have the option to decide whether the report should include secondary and incidental findings. Protocols and templates for reporting clinical WGS results and supplementary information are described in this article. © 2018 by John Wiley & Sons, Inc.

BgeeDB, an R package for retrieval of curated expression datasets and for gene list expression localization enrichment tests

BgeeDB is a collection of functions to import into R re-annotated, quality-controlled and reprocessed expression data available in the Bgee database. This includes data from thousands of wild-type healthy samples of multiple animal species, generated with different gene expression technologies (RNA-seq, Affymetrix microarrays, expressed sequence tags, and in situ hybridizations). BgeeDB facilitates downstream analyses, such as gene expression analyses with other Bioconductor packages. Moreover, BgeeDB includes a new gene set enrichment test for preferred localization of expression of genes in anatomical structures ("TopAnat"). Along with the classical Gene Ontology enrichment test, this test provides a complementary way to interpret gene lists. Availability: http://www.bioconductor.org/packages/BgeeDB/.

Deciphering the complexities of human diseases and disorders by coupling induced-pluripotent stem cells and systems genetics

The recent discovery that adult mouse and human somatic cells can be 'reprogrammed' to a state of pluripotency by ectopic expression of only a few transcription factors has already made a major impact on the biomedical community. For the first time, it is possible to study diseases on an individual patient basis, which may eventually lead to the realization of personalized medicine. The utility of induced-pluripotent stem cells (iPSCs) for modeling human diseases has greatly benefitted from established human embryonic stem cell (ESC) differentiation and tissue engineering protocols developed to generate many different cell and tissue types. The limited access to preimplantation genetic tested embryos and the difficulty in gene targeting human ESCs have restricted the use of human ESCs in modeling human disease. Afforded by iPSC technology is the ability to study disease pathogenesis as it unfolds during tissue morphogenesis. The complexities of molecular signaling and interplay with protein transduction during disease progression necessitate a systems approach to studying human diseases, whereby data can be statistically integrated by sorting out the signal to noise issues that arise from global biological changes associated with disease versus experimental noise. Using a systems approach, biomarkers can be identified that define the initiation or progression of disease and likewise can serve as putative therapeutic targets.