GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It automatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. VarElect's capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. © 2016 by John Wiley & Sons, Inc.

An increasing number of eukaryotic genes are being found to have naturally occurring antisense transcripts. Here we study the extent of antisense transcription in the human genome by analyzing the public databases of expressed sequences using a set of computational tools designed to identify sense-antisense transcriptional units on opposite DNA strands of the same genomic locus. The resulting data set of 2,667 sense-antisense pairs was evaluated by microarrays containing strand-specific oligonucleotide probes derived from the region of overlap. Verification of specific cases by northern blot analysis with strand-specific riboprobes proved transcription from both DNA strands. We conclude that > or =60% of this data set, or approximately 1,600 predicted sense-antisense transcriptional units, are transcribed from both DNA strands. This indicates that the occurrence of antisense transcription, usually regarded as infrequent, is a very common phenomenon in the human genome. Therefore, antisense modulation of gene expression in human cells may be a common regulatory mechanism.

The GeneCards® database of human genes was launched in 1997 and has expanded since then to encompass gene-centric, disease-centric, and pathway-centric entities and relationships within the GeneCards Suite, effectively navigating the universe of human biological data—genes, proteins, cells, regulatory elements, biological pathways, and diseases—and the connections among them. The knowledgebase amalgamates information from >150 selected sources related to genes, proteins, ncRNAs, regulatory elements, chemical compounds, drugs, splice variants, SNPs, signaling molecules, differentiation protocols, biological pathways, stem cells, genetic tests, clinical trials, diseases, publications, and more and empowers the suite’s Next Generation Sequencing (NGS), gene set, shared descriptors, and batch query analysis tools.

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BackgroundNext generation sequencing (NGS) provides a key technology for deciphering the genetic underpinnings of human diseases. Typical NGS analyses of a patient depict tens of thousands non-reference coding variants, but only one or very few are expected to be significant for the relevant disorder. In a filtering stage, one employs family segregation, rarity in the population, predicted protein impact and evolutionary conservation as a means for shortening the variation list. However, narrowing down further towards culprit disease genes usually entails laborious seeking of gene-phenotype relationships, consulting numerous separate databases. Thus, a major challenge is to transition from the few hundred shortlisted genes to the most viable disease-causing candidates.ResultsWe describe a novel tool, VarElect (http://ve.genecards.org), a comprehensive phenotype-dependent variant/gene prioritizer, based on the widely-used GeneCards, which helps rapidly identify causal mutations with extensive evidence. The GeneCards suite offers an effective and speedy alternative, whereby >120 gene-centric automatically-mined data sources are jointly available for the task. VarElect cashes on this wealth of information, as well as on GeneCards’ powerful free-text Boolean search and scoring capabilities, proficiently matching variant-containing genes to submitted disease/symptom keywords. The tool also leverages the rich disease and pathway information of MalaCards, the human disease database, and PathCards, the unified pathway (SuperPaths) database, both within the GeneCards Suite. The VarElect algorithm infers direct as well as indirect links between genes and phenotypes, the latter benefitting from GeneCards’ diverse gene-to-gene data links in GenesLikeMe. Finally, our tool offers an extensive gene-phenotype evidence portrayal (“MiniCards”) and hyperlinks to the parent databases.ConclusionsWe demonstrate that VarElect compares favorably with several often-used NGS phenotyping tools, thus providing a robust facility for ranking genes, pointing out their likelihood to be related to a patient’s disease. VarElect’s capacity to automatically process numerous NGS cases, either in stand-alone format or in VCF-analyzer mode (TGex and VarAnnot), is indispensable for emerging clinical projects that involve thousands of whole exome/genome NGS analyses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2722-2) contains supplementary material, which is available to authorized users.

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RNA localization is a regulatory mechanism that is conserved from bacteria to mammals. Yet, little is known about the mechanism and the logic that govern the distribution of RNA transcripts within the cell. Here, we present a novel organ culture system, which enables the isolation of RNA specifically from NGF dependent re-growing peripheral axons of mouse embryo, sensory neurons. In combination with massive parallel sequencing technology, we determine the subcellular localization of most transcripts in the transcriptome. We found that the axon is enriched in mRNAs that encode secreted proteins, transcription factors, and the translation machinery. In contrast, the axon was largely depleted from mRNAs encoding transmembrane proteins, a particularly interesting finding, since many of these gene products are specifically expressed in the tip of the axon at the protein level. Comparison of the mitochondrial mRNAs encoded in the nucleus with those encoded in the mitochondria, uncovered completely different localization pattern, with the latter much enriched in the axon fraction. This discovery is intriguing since the protein products encoded by the nuclear and mitochondrial genome form large co-complexes. Finally, focusing on alternative splice variants that are specific to axonal fractions, we find short sequence motifs that are enriched in the axonal transcriptome. Together our findings shed light on the extensive role of RNA localization and its characteristics.

Epileptic encephalopathies are genetically heterogeneous severe disorders in which epileptic activity contributes to neurological deterioration. We studied two unrelated children presenting with a distinctive early-onset epileptic encephalopathy characterized by refractory epilepsy and absent developmental milestones, as well as thick and short corpus callosum and persistent cavum septum pellucidum on brain MRI. Using whole-exome sequencing, we identified biallelic mutations in seizure threshold 2 (SZT2) in both affected children. The causative mutations include a homozygous nonsense mutation and a nonsense mutation together with an exonic splice-site mutation in a compound-heterozygous state. The latter mutation leads to exon skipping and premature termination of translation, as shown by RT-PCR in blood RNA of the affected boy. Thus, all three mutations are predicted to result in nonsense-mediated mRNA decay and/or premature protein truncation and thereby loss of SZT2 function. Although the molecular role of the peroxisomal protein SZT2 in neuronal excitability and brain development remains to be defined, Szt2 has been shown to influence seizure threshold and epileptogenesis in mice, consistent with our findings in humans. We conclude that mutations in SZT2 cause a severe type of autosomal-recessive infantile encephalopathy with intractable seizures and distinct neuroradiological anomalies.