Variable loss of functional activities of androgen receptor mutants in patients with androgen insensitivity syndrome

Androgen receptor (AR) mutations in androgen insensitivity syndrome (AIS) are associated with a variety of clinical phenotypes. The aim of the present study was to compare the molecular properties and potential pathogenic nature of 8 novel and 3 recurrent AR variants with a broad variety of functional assays. Eleven AR variants (p.Cys177Gly, p.Arg609Met, p.Asp691del, p.Leu701Phe, p.Leu723Phe, p.Ser741Tyr, p.Ala766Ser, p.Arg775Leu, p.Phe814Cys, p.Lys913X, p.Ile915Thr) were analyzed for hormone binding, transcriptional activation, cofactor binding, translocation to the nucleus, nuclear dynamics, and structural conformation. Ligand-binding domain variants with low to intermediate transcriptional activation displayed aberrant Kd values for hormone binding and decreased nuclear translocation. Transcriptional activation data, FxxFF-like peptide binding and DNA binding correlated well for all variants, except for p.Arg609Met, p.Leu723Phe and p.Arg775Leu, which displayed a relatively higher peptide binding activity. Variants p.Cys177Gly, p.Asp691del, p.Ala766Ser, p.Phe814Cys, and p.Ile915Thr had intermediate or wild type values in all assays and showed a predominantly nuclear localization in living cells. All transcriptionally inactive variants (p.Arg609Met, p.Leu701Phe, p.Ser741Tyr, p.Arg775Leu, p.Lys913X) were unable to bind to DNA and were associated with complete AIS. Three variants (p.Asp691del, p.Arg775Leu, p.Ile915Thr) still displayed significant functional activities in in vitro assays, although the clinical phenotype was associated with complete AIS. The data show that molecular phenotyping based on 5 different functional assays matched in most (70%) but not all cases. Copyrigh

The FAIR Guiding Principles for scientific data management and stewardship

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community