Dvir Dahary

Widespread occurrence of antisense transcription in the human genome

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 ≥60% of this data set, or ∼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.

Is the G72/G30 locus associated with schizophrenia? single nucleotide polymorphisms, haplotypes, and gene expression analysis

BACKGROUND The genes G72/G30 were recently implicated in schizophrenia in both Canadian and Russian populations. We hypothesized that 1) polymorphic changes in this gene region might be associated with schizophrenia in the Ashkenazi Jewish population and that 2) changes in G72/G30 gene expression might be expected in schizophrenic patients compared with control subjects. METHODS Eleven single nucleotide polymorphisms (SNPs) encompassing the G72/G30 genes were typed in the genomic deoxyribonucleic acid (DNA) from 60 schizophrenic patients and 130 matched control subjects of Ashkenazi ethnic origin. Case-control comparisons were based on linkage disequilibrium (LD) and haplotype frequency estimations. Gene expression analysis of G72 and G30 was performed on 88 postmortem dorsolateral prefrontal cortex samples. RESULTS Linkage disequilibrium analysis revealed two main SNP blocks. Haplotype analysis on block II, containing three SNPs external to the genes, demonstrated an association with schizophrenia. Gene expression analysis exhibited correlations between expression levels of the G72 and G30 genes, as well as a tendency toward overexpression of the G72 gene in schizophrenic brain samples of 44 schizophrenic patients compared with 44 control subjects. CONCLUSIONS It is likely that the G72/G30 region is involved in susceptibility to schizophrenia in the Ashkenazi population. The elevation in expression of the G72 gene coincides with the glutamatergic theory of schizophrenia.

Discovery and Validation of Novel Peptide Agonists for G-protein-coupled Receptors

G-protein-coupled receptors (GPCRs) represent an important group of targets for pharmaceutical therapeutics. The completion of the human genome revealed a large number of putative GPCRs. However, the identification of their natural ligands, and especially peptides, suffers from low discovery rates, thus impeding development of therapeutics based on these potential drug targets. We describe the discovery of novel GPCR ligands encrypted in the human proteome. Hundreds of potential peptide ligands were predicted by machine learning algorithms. In vitro screening of selected 33 peptides on a set of 152 GPCRs, including a group of designated orphan receptors, was conducted by intracellular calcium measurements and cAMP assays. The screening revealed eight novel peptides as potential agonists that specifically activated six different receptors in a dose-dependent manner. Most of the peptides showed distinct stimulatory patterns targeted at designated and orphan GPCRs. Further analysis demonstrated a significant in vivo effect for one of the peptides in a mouse inflammation model.

The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses.

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. VarElects 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.

Is there any sense in antisense editing

Several recent studies have hypothesized that sense-antisense RNA-transcript pairs create dsRNA duplexes that undergo extensive A-to-I RNA editing. We studied human and mouse genomic antisense regions and found that the editing level in these areas is negligible. This observation questions the scope of sense-antisense duplexes formation in-vivo, which is the basis for several proposed regulatory mechanisms.

Biallelic SZT2 Mutations Cause Infantile Encephalopathy with Epilepsy and Dysmorphic Corpus Callosum

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.

VarElect: the phenotype-based variation prioritizer of the GeneCards Suite

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.

Hypocretin neuron-specific transcriptome profiling identifies the sleep modulator Kcnh4a

Sleep has been conserved throughout evolution; however, the molecular and neuronal mechanisms of sleep are largely unknown. The hypothalamic hypocretin/orexin (Hcrt) neurons regulate sleep\wake states, feeding, stress, and reward. To elucidate the mechanism that enables these various functions and to identify sleep regulators, we combined fluorescence cell sorting and RNA-seq in hcrt:EGFP zebrafish. Dozens of Hcrt-neuron–specific transcripts were identified and comprehensive high-resolution imaging revealed gene-specific localization in all or subsets of Hcrt neurons. Clusters of Hcrt-neuron–specific genes are predicted to be regulated by shared transcription factors. These findings show that Hcrt neurons are heterogeneous and that integrative molecular mechanisms orchestrate their diverse functions. The voltage-gated potassium channel Kcnh4a, which is expressed in all Hcrt neurons, was silenced by the CRISPR-mediated gene inactivation system. The mutant kcnh4a (kcnh4a-/-) larvae showed reduced sleep time and consolidation, specifically during the night, suggesting that Kcnh4a regulates sleep. DOI: http://dx.doi.org/10.7554/eLife.08638.001

Microcephaly Thin Corpus Callosum Intellectual Disability Syndrome Caused by Mutated TAF2

BACKGROUND The combination of microcephaly, pyramidal signs, abnormal corpus callosum, and intellectual disability presents a diagnostic challenge. We describe an autosomal recessive disorder characterized by microcephaly, pyramidal signs, thin corpus callosum, and intellectual disability. METHODS We previously mapped the locus for this disorder to 8q23.2-q24.12; the candidate region included 22 genes. We performed Sanger sequencing of 10 candidate genes; to ensure other genes in the candidate region do not harbor mutations, we sequenced the exome of one affected individual. RESULTS We identified two homozygous missense changes, p.Thr186Arg and p.Pro416His in TAF2, which encodes a multisubunit cofactor for TFIID-dependent RNA polymerase II-mediated transcription, in all affected individuals. CONCLUSIONS We propose that the disorder is caused by the more conserved mutation p.Thr186Arg, with the second sequence change identified, p.Pro416His, possibly further negatively affecting the function of the protein. However, it is unclear which of the two changes, or maybe both, represents the causative mutation. A single missense mutation in TAF2 in a family with microcephaly and intellectual disability was described in a large-scale study reporting on the identification of 50 novel genes. We suggest that a mutation in TAF2 can cause this syndrome.

Monitoring Collagen Synthesis in Fibroblasts Using Fluorescently Labeled tRNA Pairs

There is a critical need for techniques that directly monitor protein synthesis within cells isolated from normal and diseased tissue. Fibrotic disease, for which there is no drug treatment, is characterized by the overexpression of collagens. Here, we use a bioinformatics approach to identify a pair of glycine and proline isoacceptor tRNAs as being specific for the decoding of collagen mRNAs, leading to development of a FRET‐based approach, dicodon monitoring of protein synthesis (DiCoMPS), that directly monitors the synthesis of collagen. DiCoMPS aimed at detecting collagen synthesis will be helpful in identifying novel anti‐fibrotic compounds in cells derived from patients with fibrosis of any etiology, and, suitably adapted, should be widely applicable in monitoring the synthesis of other proteins in cells. J. Cell. Physiol. 229: 1121–1129, 2014.