FlyMine is a data warehouse that addresses one of the important challenges of modern biology: how to integrate and make use of the diversity and volume of current biological data. Its main focus is genomic and proteomics data for Drosophila and other insects. It provides web access to integrated data at a number of different levels, from simple browsing to construction of complex queries, which can be executed on either single items or lists. RationaleWith the completion of increasing numbers of genome sequences has come an explosion in the development of both computational and experimental techniques for deciphering the functions of genes, molecules and their interactions. These include theoretical methods for deducing function, such as analysis of protein homologies, structural domain predictions, phylogenetic profiling and analysis of protein domain fusions, as well as experimental techniques, such as microarray-based gene expression and transcription factor binding studies, two-hybrid protein-protein interaction screens, and large-scale RNA interference (RNAi) screens. The result is a huge amount of information and a current challenge is to extract meaningful knowledge and patterns of biological significance that can lead to new experimentally testable hypotheses. Many of these broad datasets, however, are noisy and the data quality can vary significantly. While in some circumstances the data from each of these techniques are useful in their own right, the ability to combine data from different sources facilitates interpretation and potentially allows stronger inferences to be made. Currently, biological data are stored in a wide variety of formats in numerous different places, making their combined analysis difficult: when information from several different databases is required, the assembly of data into a format suitable for querying is a challenge in itself. Sophisticated analysis of diverse data requires that they are available in a form that allows questions to be asked across them and that tools for constructing the questions are available. The development of systems for the integration and combined analysis of diverse data remains a priority in bioinformatics. Avoiding the need to understand and reformat many different data sources is a major benefit for end users of a centralized data access system.A number of studies have illustrated the power of integrating data for cross-validation, functional annotation and generating testable hypotheses (reviewed in [1,2]). These studies have covered a range of data types; some looking at the overlap between two different data sets, for example, protein interaction and expression data [3][4][5][6] Another key component is the use of ontologies that provide a standardized system for naming biological entities and their relationships and this aspect is based on the approach taken by the Chado schema [28]. For example, a large part of the FlyMine data model is based on the Sequence Ontology (a controlled-vocabulary for describing biological sequences) [29...

Summary: InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of ‘widgets’ performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages.Availability: Freely available from http://www.intermine.org under the LGPL license.Contact: g.micklem@gen.cam.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

SignificanceWe report a disease-causing mutation in the β-cell–enriched MAFA transcription factor. Strikingly, the missense p.Ser64Phe MAFA mutation was associated with either of two distinct phenotypes, multiple insulin-producing neuroendocrine tumors of the pancreas—a condition known as insulinomatosis—or diabetes mellitus, recapitulating the physiological properties of MAFA both as an oncogene and as a key islet β-cell transcription factor. The implication of MAFA in these human phenotypes will provide insights into how this transcription factor regulates human β-cell activity as well as into the mechanisms of Maf-induced tumorigenesis.

Neonatal diabetes is caused by single gene mutations reducing pancreatic β cell number or impairing β cell function. Understanding the genetic basis of rare diabetes subtypes highlights fundamental biological processes in β cells. We identified 6 patients from 5 families with homozygous mutations in the YIPF5 gene, which is involved in trafficking between the endoplasmic reticulum (ER) and the Golgi. All patients had neonatal/early-onset diabetes, severe microcephaly, and epilepsy. YIPF5 is expressed during human brain development, in adult brain and pancreatic islets. We used 3 human β cell models ( YIPF5 silencing in EndoC-βH1 cells, YIPF5 knockout and mutation knockin in embryonic stem cells, and patient-derived induced pluripotent stem cells) to investigate the mechanism through which YIPF5 loss of function affects β cells. Loss of YIPF5 function in stem cell–derived islet cells resulted in proinsulin retention in the ER, marked ER stress, and β cell failure. Partial YIPF5 silencing in EndoC-βH1 cells and a patient mutation in stem cells increased the β cell sensitivity to ER stress–induced apoptosis. We report recessive YIPF5 mutations as the genetic cause of a congenital syndrome of microcephaly, epilepsy, and neonatal/early-onset diabetes, highlighting a critical role of YIPF5 in β cells and neurons. We believe this is the first report of mutations disrupting the ER-to-Golgi trafficking, resulting in diabetes.

Physical stress, including high temperatures, may damage the central metabolic nicotinamide nucleotide cofactors [NAD(P)H], generating toxic derivatives [NAD(P)HX]. The highly conserved enzyme NAD(P)HX dehydratase (NAXD) is essential for intracellular repair of NAD(P)HX. Here we present a series of infants and children who suffered episodes of febrile illness-induced neurodegeneration or cardiac failure and early death. Whole-exome or whole-genome sequencing identified recessive NAXD variants in each case. Variants were predicted to be potentially deleterious through in silico analysis. Reverse-transcription PCR confirmed altered splicing in one case. Subject fibroblasts showed highly elevated concentrations of the damaged cofactors S-NADHX, R-NADHX and cyclic NADHX. NADHX accumulation was abrogated by lentiviral transduction of subject cells with wild-type NAXD. Subject fibroblasts and muscle biopsies showed impaired mitochondrial function, higher sensitivity to metabolic stress in media containing galactose and azide, but not glucose, and decreased mitochondrial reactive oxygen species production. Recombinant NAXD protein harbouring two missense variants leading to the amino acid changes p.(Gly63Ser) and p.(Arg608Cys) were thermolabile and showed a decrease in V max and increase in K M for the ATP-dependent NADHX dehydratase activity. This is the first study to identify pathogenic variants in NAXD and to link deficient NADHX repair with mitochondrial dysfunction. The results show that NAXD deficiency can be classified as a metabolite repair disorder in which accumulation of damaged metabolites likely triggers devastating effects in tissues such as the brain and the heart, eventually leading to early childhood death.