Assessing structural variation in a personal genome-towards a human reference diploid genome.

BACKGROUND: Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods. RESULTS: We demonstrate Parliament's efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus. CONCLUSIONS: HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

Identifying gene disruptions in novel balanced de novo constitutional translocations in childhood cancer patients by whole-genome sequencing.

PURPOSE: We applied whole-genome sequencing (WGS) to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations to discover novel genic disruptions. METHODS: We applied the structural variation (SV) calling programs CREST, BreakDancer, SV-STAT, and CGAP-CNV, and we developed an annotative filtering strategy to achieve nucleotide resolution at the translocations. RESULTS: We identified the breakpoints for t(6;12)(p21.1;q24.31), disrupting HNF1A in a patient diagnosed with hepatic adenomas and maturity-onset diabetes of the young (MODY). Translocation as the disruptive event of HNF1A, a gene known to be involved in MODY3, has not been previously reported. In a subject with Hodgkin lymphoma and subsequent low-grade glioma, we identified t(5;18)(q35.1;q21.2), disrupting both SLIT3 and DCC, genes previously implicated in both glioma and lymphoma. CONCLUSION: These examples suggest that implementing clinical WGS in the diagnostic workup of patients with novel but apparently balanced translocations may reveal unanticipated disruption of disease-associated genes and aid in prediction of the clinical phenotype.

Stargazin and other transmembrane AMPA receptor regulating proteins interact with synaptic scaffolding protein MAGI-2 in brain.

The spatial coordination of neurotransmitter receptors with other postsynaptic signaling and structural molecules is regulated by a diverse array of cell-specific scaffolding proteins. The synaptic trafficking of AMPA receptors by the stargazin protein in some neurons, for example, depends on specific interactions between the C terminus of stargazin and the PDZ [postsynaptic density-95 (PSD-95)/Discs large/zona occludens-1] domains of membrane-associated guanylate kinase scaffolding proteins PSD-93 or PSD-95. Stargazin [Cacng2 (Ca2+ channel gamma2 subunit)] is one of four closely related proteins recently categorized as transmembrane AMPA receptor regulating proteins (TARPs) that appear to share similar functions but exhibit distinct expression patterns in the CNS. We used yeast two-hybrid screening to identify MAGI-2 (membrane associated guanylate kinase, WW and PDZ domain containing 2) as a novel candidate interactor with the cytoplasmic C termini of the TARPs. MAGI-2 [also known as S-SCAM (synaptic scaffolding molecule)] is a multi-PDZ domain scaffolding protein that interacts with several different ligands in brain, including PTEN (phosphatase and tensin homolog), dasm1 (dendrite arborization and synapse maturation 1), dendrin, axin, beta- and delta-catenin, neuroligin, hyperpolarization-activated cation channels, beta1-adrenergic receptors, and NMDA receptors. We confirmed that MAGI-2 coimmunoprecipitated with stargazin in vivo from mouse cerebral cortex and used in vitro assays to localize the interaction to the C-terminal -TTPV amino acid motif of stargazin and the PDZ1, PDZ3, and PDZ5 domains of MAGI-2. Expression of stargazin recruited MAGI-2 to cell membranes and cell-cell contact sites in transfected HEK-293T cells dependent on the presence of the stargazin -TTPV motif. These experiments identify MAGI-2 as a strong candidate for linking TARP/AMPA receptor complexes to a wide range of other postsynaptic molecules and pathways and advance our knowledge of protein interactions at mammalian CNS synapses.

Somatic cancer variant curation and harmonization through consensus minimum variant level data.

BACKGROUND: To truly achieve personalized medicine in oncology, it is critical to catalog and curate cancer sequence variants for their clinical relevance. The Somatic Working Group (WG) of the Clinical Genome Resource (ClinGen), in cooperation with ClinVar and multiple cancer variant curation stakeholders, has developed a consensus set of minimal variant level data (MVLD). MVLD is a framework of standardized data elements to curate cancer variants for clinical utility. With implementation of MVLD standards, and in a working partnership with ClinVar, we aim to streamline the somatic variant curation efforts in the community and reduce redundancy and time burden for the interpretation of cancer variants in clinical practice. METHODS: We developed MVLD through a consensus approach by i) reviewing clinical actionability interpretations from institutions participating in the WG, ii) conducting extensive literature search of clinical somatic interpretation schemas, and iii) survey of cancer variant web portals. A forthcoming guideline on cancer variant interpretation, from the Association of Molecular Pathology (AMP), can be incorporated into MVLD. RESULTS: Along with harmonizing standardized terminology for allele interpretive and descriptive fields that are collected by many databases, the MVLD includes unique fields for cancer variants such as Biomarker Class, Therapeutic Context and Effect. In addition, MVLD includes recommendations for controlled semantics and ontologies. The Somatic WG is collaborating with ClinVar to evaluate MVLD use for somatic variant submissions. ClinVar is an open and centralized repository where sequencing laboratories can report summary-level variant data with clinical significance, and ClinVar accepts cancer variant data. CONCLUSIONS: We expect the use of the MVLD to streamline clinical interpretation of cancer variants, enhance interoperability among multiple redundant curation efforts, and increase submission of somatic variants to ClinVar, all of which will enhance translation to clinical oncology practice.

SV-STAT accurately detects structural variation via alignment to reference-based assemblies.

BACKGROUND: Genomic deletions, inversions, and other rearrangements known collectively as structural variations (SVs) are implicated in many human disorders. Technologies for sequencing DNA provide a potentially rich source of information in which to detect breakpoints of structural variations at base-pair resolution. However, accurate prediction of SVs remains challenging, and existing informatics tools predict rearrangements with significant rates of false positives or negatives. RESULTS: To address this challenge, we developed 'Structural Variation detection by STAck and Tail' (SV-STAT) which implements a novel scoring metric. The software uses this statistic to quantify evidence for structural variation in genomic regions suspected of harboring rearrangements. To demonstrate SV-STAT, we used targeted and genome-wide approaches. First, we applied a custom capture array followed by Roche/454 and SV-STAT to three pediatric B-lineage acute lymphoblastic leukemias, identifying five structural variations joining known and novel breakpoint regions. Next, we detected SVs genome-wide in paired-end Illumina data collected from additional tumor samples. SV-STAT showed predictive accuracy as high as or higher than leading alternatives. The software is freely available under the terms of the GNU General Public License version 3 at https://gitorious.org/svstat/svstat. CONCLUSIONS: SV-STAT works across multiple sequencing chemistries, paired and single-end technologies, targeted or whole-genome strategies, and it complements existing SV-detection software. The method is a significant advance towards accurate detection and genotyping of genomic rearrangements from DNA sequencing data.

Focused Analysis of Exome Sequencing Data for Rare Germline Mutations in Familial and Sporadic Lung Cancer.

INTRODUCTION: The association between smoking-induced chronic obstructive pulmonary disease (COPD) and lung cancer (LC) is well documented. Recent genome-wide association studies (GWAS) have identified 28 susceptibility loci for LC, 10 for COPD, 32 for smoking behavior, and 63 for pulmonary function, totaling 107 nonoverlapping loci. Given that common variants have been found to be associated with LC in genome-wide association studies, exome sequencing of these high-priority regions has great potential to identify novel rare causal variants. METHODS: To search for disease-causing rare germline mutations, we used a variation of the extreme phenotype approach to select 48 patients with sporadic LC who reported histories of heavy smoking-37 of whom also exhibited carefully documented severe COPD (in whom smoking is considered the overwhelming determinant)-and 54 unique familial LC cases from families with at least three first-degree relatives with LC (who are likely enriched for genomic effects). RESULTS: By focusing on exome profiles of the 107 target loci, we identified two key rare mutations. A heterozygous p.Arg696Cys variant in the coiled-coil domain containing 147 (CCDC147) gene at 10q25.1 was identified in one sporadic and two familial cases. The minor allele frequency (MAF) of this variant in the 1000 Genomes database is 0.0026. The p.Val26Met variant in the dopamine ß-hydroxylase (DBH) gene at 9q34.2 was identified in two sporadic cases; the minor allele frequency of this mutation is 0.0034 according to the 1000 Genomes database. We also observed three suggestive rare mutations on 15q25.1: iron-responsive element binding protein neuronal 2 (IREB2); cholinergic receptor, nicotinic, alpha 5 (neuronal) (CHRNA5); and cholinergic receptor, nicotinic, beta 4 (CHRNB4). CONCLUSIONS: Our results demonstrated highly disruptive risk-conferring CCDC147 and DBH mutations.

The somatic genomic landscape of chromophobe renal cell carcinoma.

We describe the landscape of somatic genomic alterations of 66 chromophobe renal cell carcinomas (ChRCCs) on the basis of multidimensional and comprehensive characterization, including mtDNA and whole-genome sequencing. The result is consistent that ChRCC originates from the distal nephron compared with other kidney cancers with more proximal origins. Combined mtDNA and gene expression analysis implicates changes in mitochondrial function as a component of the disease biology, while suggesting alternative roles for mtDNA mutations in cancers relying on oxidative phosphorylation. Genomic rearrangements lead to recurrent structural breakpoints within TERT promoter region, which correlates with highly elevated TERT expression and manifestation of kataegis, representing a mechanism of TERT upregulation in cancer distinct from previously observed amplifications and point mutations.

The alpha-amino-3-hydroxyl-5-methyl-4-isoxazolepropionate receptor trafficking regulator "stargazin" is related to the claudin family of proteins by Its ability to mediate cell-cell adhesion.

Mutations in the Cacng2 gene encoding the neuronal transmembrane protein stargazin result in recessively inherited epilepsy and ataxia in "stargazer" mice. Functional studies suggest a dual role for stargazin, both as a modulatory gamma subunit for voltage-dependent calcium channels and as a regulator of post-synaptic membrane targeting for alpha-amino-3-hydroxyl-5-methyl-4-isoxazolepropionate (AMPA)-type glutamate receptors. Co-immunoprecipitation experiments demonstrate that stargazin can bind proteins of either complex in vivo, but it remains unclear whether it can associate with both complexes simultaneously. Cacng2 is one of eight closely related genes (Cacng1-8) encoding proteins with four transmembrane segments, cytoplasmic termini, and molecular masses between 25 and 44 kDa. This group of Cacng genes constitutes only one branch of a larger monophyletic assembly dominated by over 20 genes encoding proteins known as claudins. Claudins regulate cell adhesion and paracellular permeability as fundamental components of non-neuronal tight junctions. Because stargazin is structurally similar to claudins, we hypothesized that it might also have retained claudin-like functions inherited from a common ancestor. Here, we report that expression of stargazin in mouse L-fibroblasts results in cell aggregation comparable with that produced by claudins, and present evidence that the interaction is heterotypic and calcium dependent. The data suggest that the cell adhesion function of stargazin preceded its current role in neurons as a regulator of either voltage-dependent calcium channels or AMPA receptors. We speculate these complexes may have co-opted the established presence of stargazin at sites of close cell-cell contact to facilitate their own evolving intercellular signaling functions.