Morphologic Characteristics and Mutational Analysis of Fumarate Hydratase Deficient Kidney and Smooth Muscle Tumors.

OBJECTIVES: Fumarate hydratase (FH)-deficient tumors can occur due to germline or somatic mutations and have distinctive morphologic features. The aims of this study are to refine morphologic criteria and identify mutations in FH-deficient smooth muscle tumors (SMTs). METHODS: The morphology of SMTs and kidney tumors submitted to a national reference laboratory for FH immunohistochemistry (IHC) was reviewed by two gynecologic and two genitourinary pathologists, respectively. Fisher exact test was used for analysis. Fourteen SMTs were sequenced using the Illumina TruSight Oncology 500 Assay. RESULTS: Twenty-two kidney tumors (5 FH deficient) and 51 SMTs (27 FH deficient) were reviewed. FH-deficient kidney tumors exclusively showed cord-like growth, rhabdoid change, and absence of coagulative tumor necrosis and psammoma bodies. FH-deficient SMTs were significantly more likely to have staghorn vessels, eosinophilic cytoplasmic inclusions, schwannoma-like areas, or hereditary leiomyomatosis and renal cell cancer-like nuclei (P < .05 for each). Seven of 14 sequenced SMTs showed mutations of the FH gene and no other driver mutations. CONCLUSIONS: FH-deficient SMTs submitted for FH immunohistochemistry (IHC) showed distinct morphology. Although FH IHC is used for screening of FH-deficient tumors, FH mutations were identified in only 50% of FH-deficient SMTs. This highlights the need for additional exploration of mechanisms of FH protein loss in tumors lacking FH mutations.

Algorithmic improvements for discovery of germline copy number variants in next-generation sequencing data.

BACKGROUND: Copy number variants (CNVs) play a significant role in human heredity and disease. However, sensitive and specific characterization of germline CNVs from NGS data has remained challenging, particularly for hybridization-capture data in which read counts are the primary source of copy number information. RESULTS: We describe two algorithmic adaptations that improve CNV detection accuracy in a Hidden Markov Model (HMM) context. First, we present a method for computing target- and copy number-specific emission distributions. Second, we demonstrate that the Pointwise Maximum a posteriori (PMAP) HMM decoding procedure yields improved sensitivity for small CNV calls compared to the more common Viterbi HMM decoder. We develop a prototype implementation, called Cobalt, and compare it to other CNV detection tools using sets of simulated and previously detected CNVs with sizes spanning a single exon to a full chromosome. CONCLUSIONS: In both the simulation and previously detected CNV studies Cobalt shows similar sensitivity but significantly fewer false positive detections compared to other callers. Overall sensitivity is 80-90% for deletion CNVs spanning 1-4 targets and 90-100% for larger deletion events, while sensitivity is somewhat lower for small duplication CNVs.

Genome-Wide Copy Number Variation Detection Using NGS: Data Analysis and Interpretation.

Copy number variants (CNVs) and copy neutral loss of heterozygosity (CN-LOH) represent important types of genomic abnormalities in cancer. Genomic DNA microarray serves as the current gold standard method for detecting genome-wide CNVs and CN-LOH. However, as next-generation sequencing (NGS) is widely used to detect gene variants in clinical testing, the ability of NGS to detect CNVs and CN-LOH has also been demonstrated. This chapter describes a protocol for detecting genome-wide large somatic CNVs and CN-LOH using a single nucleotide polymorphism (SNP) sequencing backbone. When combined with a targeted gene mutation panel, this strategy allows for simultaneous detection of somatic gene mutations and genome-wide CNVs and CN-LOH.

Novel PLP1 Mutations Identified With Next-Generation Sequencing Expand the Spectrum of PLP1-Associated Leukodystrophy Clinical Phenotypes.

Next-generation sequencing was performed for 2 families with an undiagnosed neurologic disease. Analysis revealed X-linked mutations in the proteolipid protein 1 (PLP1) gene, which is associated with X-linked Pelizaeus-Merzbacher disease and Spastic Paraplegia type 2. In family A, the novel PLP1 missense mutation c.617T>A (p.M206K) was hemizygous in the 2 affected male children and heterozygous in the mother. In family B, the novel de novoPLP1 frameshift mutation c.359_369del (p.G120fs) was hemizygous in the affected male child. Although PLP1 mutations have been reported to cause an increasingly wide range of phenotypes inclusive of the dystonia, spastic paraparesis, motor neuronopathy, and leukodystrophy observed in our patients, atypical features included the cerebrospinal fluid deficiency of neurotransmitter and pterin metabolites and the delayed appearance of myelin abnormalities on neuroimaging studies. Next-generation sequencing studies provided a diagnosis for these families with complex leukodystrophy disease phenotypes, which expanded the spectrum of PLP1-associated leukodystrophy clinical phenotypes.

Identification of patients with RAG mutations previously diagnosed with common variable immunodeficiency disorders.

PURPOSE: Combined immunodeficiency (CID) presents a unique challenge to clinicians. Two patients presented with the prior clinical diagnosis of common variable immunodeficiency (CVID) disorder marked by an early age of presentation, opportunistic infections, and persistent lymphopenia. Due to the presence of atypical clinical features, next generation sequencing was applied documenting RAG deficiency in both patients. METHODS: Two different genetic analysis techniques were applied in these patients including whole exome sequencing in one patient and the use of a gene panel designed to target genes known to cause primary immunodeficiency disorders (PIDD) in a second patient. Sanger dideoxy sequencing was used to confirm RAG1 mutations in both patients. RESULTS: Two young adults with a history of recurrent bacterial sinopulmonary infections, viral infections, and autoimmune disease as well as progressive hypogammaglobulinemia, abnormal antibody responses, lymphopenia and a prior diagnosis of CVID disorder were evaluated. Compound heterozygous mutations in RAG1 (1) c256_257delAA, p86VfsX32 and (2) c1835A>G, pH612R were documented in one patient. Compound heterozygous mutations in RAG1 (1) c.1566G>T, p.W522C and (2) c.2689C>T, p. R897X) were documented in a second patient post-mortem following a fatal opportunistic infection. CONCLUSION: Astute clinical judgment in the evaluation of patients with PIDD is necessary. Atypical clinical findings such as early onset, granulomatous disease, or opportunistic infections should support the consideration of atypical forms of late onset CID secondary to RAG deficiency. Next generation sequencing approaches provide powerful tools in the investigation of these patients and may expedite definitive treatments.

Next-generation sequencing of custom amplicons to improve coverage of HaloPlex multigene panels.

Next-generation sequencing (NGS) of multigene panels performed for genetic clinical diagnostics requires 100% coverage of all targeted genes. In the genetic diagnostics laboratory, coverage gaps are typically filled with Sanger sequencing after NGS data are collected and analyzed. Libraries prepared using the hybridization-based custom capture HaloPlex method are covered at ~98% and include gaps in coverage because of the location of the restriction enzyme sites used for fragmentation and differences in the designed and actual library insert size. We describe a method for improving the coverage of HaloPlex libraries by generating a set of amplicons spanning known low-coverage regions that are pooled, indexed by sample, and sequenced together with the HaloPlex libraries. This approach reduces the number of post-NGS Sanger sequencing reactions required and complements any NGS library preparation method when complete gene coverage is necessary.

A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data.

High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.

Phevor combines multiple biomedical ontologies for accurate identification of disease-causing alleles in single individuals and small nuclear families.

Phevor integrates phenotype, gene function, and disease information with personal genomic data for improved power to identify disease-causing alleles. Phevor works by combining knowledge resident in multiple biomedical ontologies with the outputs of variant-prioritization tools. It does so by using an algorithm that propagates information across and between ontologies. This process enables Phevor to accurately reprioritize potentially damaging alleles identified by variant-prioritization tools in light of gene function, disease, and phenotype knowledge. Phevor is especially useful for single-exome and family-trio-based diagnostic analyses, the most commonly occurring clinical scenarios and ones for which existing personal genome diagnostic tools are most inaccurate and underpowered. Here, we present a series of benchmark analyses illustrating Phevor's performance characteristics. Also presented are three recent Utah Genome Project case studies in which Phevor was used to identify disease-causing alleles. Collectively, these results show that Phevor improves diagnostic accuracy not only for individuals presenting with established disease phenotypes but also for those with previously undescribed and atypical disease presentations. Importantly, Phevor is not limited to known diseases or known disease-causing alleles. As we demonstrate, Phevor can also use latent information in ontologies to discover genes and disease-causing alleles not previously associated with disease.

A novel germline PIGA mutation in Ferro-Cerebro-Cutaneous syndrome: a neurodegenerative X-linked epileptic encephalopathy with systemic iron-overload.

Three related males presented with a newly recognized x-linked syndrome associated with neurodegeneration, cutaneous abnormalities, and systemic iron overload. Linkage studies demonstrated that they shared a haplotype on Xp21.3-Xp22.2 and exome sequencing was used to identify candidate variants. Of the segregating variants, only a PIGA mutation segregated with disease in the family. The c.328_330delCCT PIGA variant predicts, p.Leu110del (or c.1030_1032delCTT, p.Leu344del depending on the reference sequence). The unaffected great-grandfather shared his X allele with the proband but he did not have the PIGA mutation, indicating that the mutation arose de novo in his daughter. A single family with a germline PIGA mutation has been reported; affected males had a phenotype characterized by multiple congenital anomalies and severe neurologic impairment resulting in infantile lethality. In contrast, affected boys in the family described here were born without anomalies and were neurologically normal prior to onset of seizures after 6 months of age, with two surviving to the second decade. PIGA encodes an enzyme in the GPI anchor biosynthesis pathway. An affected individual in the family studied here was deficient in GPI anchor proteins on granulocytes but not erythrocytes. In conclusion, the PIGA mutation in this family likely causes a reduction in GPI anchor protein cell surface expression in various cell types, resulting in the observed pleiotropic phenotype involving central nervous system, skin, and iron metabolism.

VarBin, a novel method for classifying true and false positive variants in NGS data.

BACKGROUND: Variant discovery for rare genetic diseases using Illumina genome or exome sequencing involves screening of up to millions of variants to find only the one or few causative variant(s). Sequencing or alignment errors create "false positive" variants, which are often retained in the variant screening process. Methods to remove false positive variants often retain many false positive variants. This report presents VarBin, a method to prioritize variants based on a false positive variant likelihood prediction. METHODS: VarBin uses the Genome Analysis Toolkit variant calling software to calculate the variant-to-wild type genotype likelihood ratio at each variant change and position divided by read depth. The resulting Phred-scaled, likelihood-ratio by depth (PLRD) was used to segregate variants into 4 Bins with Bin 1 variants most likely true and Bin 4 most likely false positive. PLRD values were calculated for a proband of interest and 41 additional Illumina HiSeq, exome and whole genome samples (proband's family or unrelated samples). At variant sites without apparent sequencing or alignment error, wild type/non-variant calls cluster near -3 PLRD and variant calls typically cluster above 10 PLRD. Sites with systematic variant calling problems (evident by variant quality scores and biases as well as displayed on the iGV viewer) tend to have higher and more variable wild type/non-variant PLRD values. Depending on the separation of a proband's variant PLRD value from the cluster of wild type/non-variant PLRD values for background samples at the same variant change and position, the VarBin method's classification is assigned to each proband variant (Bin 1 to Bin 4). RESULTS: To assess VarBin performance, Sanger sequencing was performed on 98 variants in the proband and background samples. True variants were confirmed in 97% of Bin 1 variants, 30% of Bin 2, and 0% of Bin 3/Bin 4. CONCLUSIONS: These data indicate that VarBin correctly classifies the majority of true variants as Bin 1 and Bin 3/4 contained only false positive variants. The "uncertain" Bin 2 contained both true and false positive variants. Future work will further differentiate the variants in Bin 2.

Germline mutations in NFKB2 implicate the noncanonical NF-κB pathway in the pathogenesis of common variable immunodeficiency.

Common variable immunodeficiency (CVID) is a heterogeneous disorder characterized by antibody deficiency, poor humoral response to antigens, and recurrent infections. To investigate the molecular cause of CVID, we carried out exome sequence analysis of a family diagnosed with CVID and identified a heterozygous frameshift mutation, c.2564delA (p.Lys855Serfs(∗)7), in NFKB2 affecting the C terminus of NF-κB2 (also known as p100/p52 or p100/p49). Subsequent screening of NFKB2 in 33 unrelated CVID-affected individuals uncovered a second heterozygous nonsense mutation, c.2557C>T (p.Arg853(∗)), in one simplex case. Affected individuals in both families presented with an unusual combination of childhood-onset hypogammaglobulinemia with recurrent infections, autoimmune features, and adrenal insufficiency. NF-κB2 is the principal protein involved in the noncanonical NF-κB pathway, is evolutionarily conserved, and functions in peripheral lymphoid organ development, B cell development, and antibody production. In addition, Nfkb2 mouse models demonstrate a CVID-like phenotype with hypogammaglobulinemia and poor humoral response to antigens. Immunoblot analysis and immunofluorescence microscopy of transformed B cells from affected individuals show that the NFKB2 mutations affect phosphorylation and proteasomal processing of p100 and, ultimately, p52 nuclear translocation. These findings describe germline mutations in NFKB2 and establish the noncanonical NF-κB signaling pathway as a genetic etiology for this primary immunodeficiency syndrome.

Developing genome and exome sequencing for candidate gene identification in inherited disorders: an integrated technical and bioinformatics approach.

CONTEXT: Advances in sequencing technology with the commercialization of next-generation sequencing (NGS) has substantially increased the feasibility of sequencing human genomes and exomes. Next-generation sequencing has been successfully applied to the discovery of disease-causing genes in rare, inherited disorders. By necessity, the advent of NGS has fostered the concurrent development of bioinformatics approaches to expeditiously analyze the large data sets generated. Next-generation sequencing has been used for important discoveries in the research setting and is now being implemented into the clinical diagnostic arena. OBJECTIVE: To review the current literature on technical and bioinformatics approaches for exome and genome sequencing and highlight examples of successful disease gene discovery in inherited disorders. To discuss the challenges for implementing NGS in the clinical research and diagnostic arenas. DATA SOURCES: Literature review and authors' experience. CONCLUSIONS: Next-generation sequencing approaches are powerful and require an investment in infrastructure and personnel expertise for effective use; however, the potential for improvement of patient care through faster and more accurate molecular diagnoses is high.

A direct comparison of next generation sequencing enrichment methods using an aortopathy gene panel- clinical diagnostics perspective.

BACKGROUND: Aortopathies are a group of disorders characterized by aneurysms, dilation, and tortuosity of the aorta. Because of the phenotypic overlap and genetic heterogeneity of diseases featuring aortopathy, molecular testing is often required for timely and correct diagnosis of affected individuals. In this setting next generation sequencing (NGS) offers several advantages over traditional molecular techniques. METHODS: The purpose of our study was to compare NGS enrichment methods for a clinical assay targeting the nine genes known to be associated with aortopathy. RainDance emulsion PCR and SureSelect RNA-bait hybridization capture enrichment methods were directly compared by enriching DNA from eight samples. Enriched samples were barcoded, pooled, and sequenced on the Illumina HiSeq2000 platform. Depth of coverage, consistency of coverage across samples, and the overlap of variants identified were assessed. This data was also compared to whole-exome sequencing data from ten individuals. RESULTS: Read depth was greater and less variable among samples that had been enriched using the RNA-bait hybridization capture enrichment method. In addition, samples enriched by hybridization capture had fewer exons with mean coverage less than 10, reducing the need for followup Sanger sequencing. Variants sets produced were 77% concordant, with both techniques yielding similar numbers of discordant variants. CONCLUSIONS: When comparing the design flexibility, performance, and cost of the targeted enrichment methods to whole-exome sequencing, the RNA-bait hybridization capture enrichment gene panel offers the better solution for interrogating the aortopathy genes in a clinical laboratory setting.

Mycobacterium chelonae-abscessus complex associated with sinopulmonary disease, Northeastern USA.

Members of the Mycobacterium chelonae-abscessus complex represent Mycobacterium species that cause invasive infections in immunocompetent and immunocompromised hosts. We report the detection of a new pathogen that had been misidentified as M. chelonae with an atypical antimicrobial drug susceptibility profile. The discovery prompted a multicenter investigation of 26 patients. Almost all patients were from the northeastern United States, and most had underlying sinus or pulmonary disease. Infected patients had clinical features similar to those with M. abscessus infections. Taxonomically, the new pathogen shared molecular identity with members of the M. chelonae-abscessus complex. Multilocus DNA target sequencing, DNA-DNA hybridization, and deep multilocus sequencing (43 full-length genes) support a new taxon for these microorganisms. Because most isolates originated in Pennsylvania, we propose the name M. franklinii sp. nov. This investigation underscores the need for accurate identification of Mycobacterium spp. to detect new pathogens implicated in human disease.

Variant identification in multi-sample pools by illumina genome analyzer sequencing.

Multi-sample pooling and Illumina Genome Analyzer (GA) sequencing allows high throughput sequencing of multiple samples to determine population sequence variation. A preliminary experiment, using the RET proto-oncogene as a model, predicted ≤ 30 samples could be pooled to reliably detect singleton variants without requiring additional confirmation testing. This report used 30 and 50 sample pools to test the hypothesized pooling limit and also to test recent protocol improvements, Illumina GAIIx upgrades, and longer read chemistry. The SequalPrep(TM) method was used to normalize amplicons before pooling. For comparison, a single 'control' sample was run in a different flow cell lane. Data was evaluated by variant read percentages and the subtractive correction method which utilizes the control sample. In total, 59 variants were detected within the pooled samples, which included all 47 known true variants. The 15 known singleton variants due to Sanger sequencing had an average of 1.62 ± 0.26% variant reads for the 30 pool (expected 1.67% for a singleton variant [unique variant within the pool]) and 1.01 ± 0.19% for the 50 pool (expected 1%). The 76 base read lengths had higher error rates than shorter read lengths (33 and 50 base reads), which eliminated the distinction of true singleton variants from background error. This report demonstrated pooling limits from 30 up to 50 samples (depending on error rates and coverage), for reliable singleton variant detection. The presented pooling protocols and analysis methods can be used for variant discovery in other genes, facilitating molecular diagnostic test design and interpretation.

Multi-sample pooling and illumina genome analyzer sequencing methods to determine gene sequence variation for database development.

Determination of sequence variation within a genetic locus to develop clinically relevant databases is critical for molecular assay design and clinical test interpretation, so multisample pooling for Illumina genome analyzer (GA) sequencing was investigated using the RET proto-oncogene as a model. Samples were Sanger-sequenced for RET exons 10, 11, and 13-16. Ten samples with 13 known unique variants ("singleton variants" within the pool) and seven common changes were amplified and then equimolar-pooled before sequencing on a single flow cell lane, generating 36 base reads. For comparison, a single "control" sample was run in a different lane. After alignment, a 24-base quality score-screening threshold and 3; read end trimming of three bases yielded low background error rates with a 27% decrease in aligned read coverage. Sequencing data were evaluated using an established variant detection method (percent variant reads), by the presented subtractive correction method, and with SNPSeeker software. In total, 41 variants (of which 23 were singleton variants) were detected in the 10 pool data, which included all Sanger-identified variants. The 23 singleton variants were detected near the expected 5% allele frequency (average 5.17%+/-0.90% variant reads), well above the highest background error (1.25%). Based on background error rates, read coverage, simulated 30, 40, and 50 sample pool data, expected singleton allele frequencies within pools, and variant detection methods; >or=30 samples (which demonstrated a minimum 1% variant reads for singletons) could be pooled to reliably detect singleton variants by GA sequencing.

Next generation sequencing for clinical diagnostics-principles and application to targeted resequencing for hypertrophic cardiomyopathy: a paper from the 2009 William Beaumont Hospital Symposium on Molecular Pathology.

During the past five years, new high-throughput DNA sequencing technologies have emerged; these technologies are collectively referred to as next generation sequencing (NGS). By virtue of sequencing clonally amplified DNA templates or single DNA molecules in a massively parallel fashion in a flow cell, NGS provides both qualitative and quantitative sequence data. This combination of information has made NGS the technology of choice for complex genetic analyses that were previously either technically infeasible or cost prohibitive. As a result, NGS has had a fundamental and broad impact on many facets of biomedical research. In contrast, the dissemination of NGS into the clinical diagnostic realm is in its early stages. Though NGS is powerful and can be envisioned to have multiple applications in clinical diagnostics, the technology is currently complex. Successful adoption of NGS into the clinical laboratory will require expertise in both molecular biology techniques and bioinformatics. The current report presents principles that underlie NGS including sequencing library preparation, sequencing chemistries, and an introduction to NGS data analysis. These concepts are subsequently further illustrated by showing representative results from a case study using NGS for targeted resequencing of genes implicated in hypertrophic cardiomyopathy.

Comparison of the Illumina Genome Analyzer and Roche 454 GS FLX for resequencing of hypertrophic cardiomyopathy-associated genes.

Next-generation sequencing (NGS) is widely used in biomedical research, but its adoption has been limited in molecular diagnostics. One application of NGS is the targeted resequencing of genes whose mutations lead to an overlapping clinical phenotype. This study evaluated the comparative performance of the Illumina Genome Analyzer and Roche 454 GS FLX for the resequencing of 16 genes associated with hypertrophic cardiomyopathy (HCM). Using a single human genomic DNA sample enriched by long-range PCR (LR-PCR), 40 GS FLX and 31 Genome Analyzer exon variants were identified using >or=30-fold read-coverage and >or=20% read-percentage selection criteria. Twenty-seven platform concordant variants were Sanger-confirmed. The discordant variants segregated into two categories: variants with read coverages >or=30 on one platform but <30-fold on the alternate platform and variants with read percentages >or=20% on one platform but <20% on the alternate platform. All variants with <30-fold coverage were Sanger-confirmed, suggesting that the coverage criterion of >or=30-fold is too stringent for variant discovery. The variants with <20% read percentage were identified as reference sequence based on Sanger sequencing. These variants were found in homopolymer tracts and short-read misalignments, specifically in genes with high identity. The results of the current study demonstrate the feasibility of combining LR-PCR with the Genome Analyzer or GS FLX for targeted resequencing of HCM-associated genes.