JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release.

BACKGROUND Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient’s clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children’s Hospital Foundation and others.)

BackgroundDramatic improvements in DNA-sequencing technologies and computational analyses have led to wide use of whole exome sequencing (WES) to identify the genetic basis of Mendelian disorders. More than 180 novel rare-disease-causing genes with Mendelian inheritance patterns have been discovered through sequencing the exomes of just a few unrelated individuals or family members. As rare/novel genetic variants continue to be uncovered, there is a major challenge in distinguishing true pathogenic variants from rare benign mutations.MethodsWe used publicly available exome cohorts, together with the dbSNP database, to derive a list of genes (n = 100) that most frequently exhibit rare (<1%) non-synonymous/splice-site variants in general populations. We termed these genes FLAGS for FrequentLy mutAted GeneS and analyzed their properties.ResultsAnalysis of FLAGS revealed that these genes have significantly longer protein coding sequences, a greater number of paralogs and display less evolutionarily selective pressure than expected. FLAGS are more frequently reported in PubMed clinical literature and more frequently associated with diseased phenotypes compared to the set of human protein-coding genes. We demonstrated an overlap between FLAGS and the rare-disease causing genes recently discovered through WES studies (n = 10) and the need for replication studies and rigorous statistical and biological analyses when associating FLAGS to rare disease. Finally, we showed how FLAGS are applied in disease-causing variant prioritization approach on exome data from a family affected by an unknown rare genetic disorder.ConclusionsWe showed that some genes are frequently affected by rare, likely functional variants in general population, and are frequently observed in WES studies analyzing diverse rare phenotypes. We found that the rate at which genes accumulate rare mutations is beneficial information for prioritizing candidates. We provided a ranking system based on the mutation accumulation rates for prioritizing exome-captured human genes, and propose that clinical reports associating any disease/phenotype to FLAGS be evaluated with extra caution.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-014-0064-y) contains supplementary material, which is available to authorized users.

Over the last decades, a growing spectrum of monogenic disorders of human magnesium homeostasis has been clinically characterized, and genetic studies in affected individuals have identified important molecular components of cellular and epithelial magnesium transport. Here, we describe three infants who are from non-consanguineous families and who presented with a disease phenotype consisting of generalized seizures in infancy, severe hypomagnesemia, and renal magnesium wasting. Seizures persisted despite magnesium supplementation and were associated with significant intellectual disability. Whole-exome sequencing and conventional Sanger sequencing identified heterozygous de novo mutations in the catalytic Na þ , K þ-ATPase a1 subunit (ATP1A1). Functional characterization of mutant Na þ , K þ-ATPase a1 subunits in heterologous expression systems revealed not only a loss of Na þ , K þ-ATPase function but also abnormal cation permeabilities, which led to membrane depolarization and possibly aggravated the effect of the loss of physiological pump activity. These findings underline the indispensable role of the a1 isoform of the Na þ , K þ-ATPase for renal-tubular magnesium handling and cellular ion homeostasis, as well as maintenance of physiologic neuronal activity.

Although inborn errors of metabolism do not represent the most common cause of seizures, their early identification is of utmost importance, since many will require therapeutic measures beyond that of common anti-epileptic drugs, either in order to control seizures, or to decrease the risk of neurodegeneration. We translate the currently-known literature on metabolic etiologies of epilepsy (268 inborn errors of metabolism belonging to 21 categories, with 74 treatable errors), into a 2-tiered diagnostic algorithm, with the first-tier comprising accessible, affordable, and less invasive screening tests in urine and blood, with the potential to identify the majority of treatable conditions, while the second-tier tests are ordered based on individual clinical signs and symptoms. This resource aims to support the pediatrician, neurologist, biochemical, and clinical geneticists in early identification of treatable inborn errors of metabolism in a child with seizures, allowing for timely initiation of targeted therapy with the potential to improve outcomes.

Purpose: Recognizing individuals with inherited diseases can be difficult because signs and symptoms often overlap those of common medical conditions. Focusing on inborn errors of metabolism (IEMs), we present a method that brings the knowledge of highly specialized experts to professionals involved in early diagnoses. We introduce IEMbase, an online expert-curated IEM knowledge base combined with a prototype diagnosis support (mini-expert) system.Methods: Disease-characterizing profiles of specific biochemical markers and clinical symptoms were extracted from an expert-compiled IEM database. A mini-expert system algorithm was developed using cosine similarity and semantic similarity. The system was evaluated using 190 retrospective cases with established diagnoses, collected from 15 different metabolic centers.Results: IEMbase provides 530 well-defined IEM profiles and matches a user-provided phenotypic profile to a list of candidate diagnoses/genes. The mini-expert system matched 62% of the retrospective cases to the exact diagnosis and 86% of the cases to a correct diagnosis within the top five candidates. The use of biochemical features in IEM annotations resulted in 41% more exact phenotype matches than clinical features alone. Conclusion:IEMbase offers a central IEM knowledge repository for many genetic diagnostic centers and clinical communities seeking support in the diagnosis of IEMs.

Distal hereditary motor neuropathies represent a group of rare genetic disorders characterized by progressive distal motor weakness without sensory loss. Their genetic heterogeneity is high and thus eligible for diagnostic whole exome sequencing. The authors report successful application of whole exome sequencing in diagnosing a second consanguineous family with distal hereditary motor neuropathy due to a homozygous c.151+1G>T variant in SIGMAR1. This variant was recently proposed as causal for the same condition in a consanguineous Chinese family. Compared to this family, the Afghan ethnic origin of our patient is distinct, yet the features are identical, validating the SIGMAR1 deficiency phenotype: progressive muscle wasting/weakness in lower and upper limbs without sensory loss. Rapid disease progression during adolescent growth is similar and may be due to SIGMAR1’s role in regulating axon elongation and tau phosphorylation. Finally, the authors conclude that SIGMAR1 deficiency should be added to the differential diagnosis of distal hereditary motor neuropathies.

Early identification and treatment of inherited metabolic diseases (IMDs) are essential to prevent and minimize intellectual disability (ID) and epilepsy. The oldest form of treatment, nutritional modulation, has proved beneficial for many IMDs. These conditions represent a promising model for P4 medicine — predictive, preventive, personalized, and participatory — specifically through the interpretation of individual genetic, pathophysiological, and clinical characteristics. More than 1000 IMDs have been described, and for these different nutritional modulation strategies are applied, varying from substrate reduction, supplementation of vitamins for catalyzation of enzymatic reactions or supplementation of amino acids or other nutrients, to substitution for deficient or inactivated products. This review provides an overview of all IMDs presenting with epilepsy and/or ID amenable to nutritional modulation; these are 85 in number, belonging to 27 categories. Therapeutic strategies include protein-restricted diet, ketogenic diet, fat-restricted diet, lactose-restricted diet; supplementation of amino acids, carbohydrates, or others; and supplementation of vitamins or cofactors as well as a sick-day protocol. Nutritional therapies are generally safe, affordable, and accessible, but compliance is an issue. Three different types of response exist: (1) a positive effect on seizure control and/or psychomotor development; (2) efficacy in prevention of decompensation but ongoing damage occurs; and (3) insufficient insights or evidence to establish the treatment as effective. For the latter category, we describe pyridoxine-dependent epilepsy as a case vignette for P4 medicine, discuss the benefits and challenges of nutritional modulation in IMDs, and outline novel approaches and solutions.