A robust model for read count data in exome sequencing experiments and implications for copy number variant calling

A homozygous loss-of-function mutation in inositol monophosphatase 1 (IMPA1) causes severe intellectual disability

The genetic basis of intellectual disability (ID) is extremely heterogeneous and relatively little is known about the role of autosomal recessive traits. In a field study performed in a highly inbred area of Northeastern Brazil, we identified and investigated a large consanguineous family with nine adult members affected by severe ID associated with disruptive behavior. The Genome-Wide Human SNP Array 6.0 microarray was used to determine regions of homozygosity by descent from three affected and one normal family member. Whole-exome sequencing (WES) was performed in one affected patient using the Nextera Rapid-Capture Exome kit and Illumina HiSeq2500 system to identify the causative mutation. Potentially deleterious variants detected in regions of homozygosity by descent and not present in either 59 723 unrelated individuals from the Exome Aggregation Consortium (Browser) or 1484 Brazilians were subject to further scrutiny and segregation analysis by Sanger sequencing. Homozygosity-by-descent analysis disclosed a 20.7-Mb candidate region at 8q12.3-q21.2 (lod score: 3.11). WES identified a homozygous deleterious variant in inositol monophosphatase 1 (IMPA1) (NM_005536), consisting of a 5-bp duplication (c.489_493dupGGGCT; chr8: 82,583,247; GRCh37/hg19) leading to a frameshift and a premature stop codon (p.Ser165Trpfs*10) that cosegregated with the disease in 26 genotyped family members. The IMPA1 gene product is responsible for the final step of biotransformation of inositol triphosphate and diacylglycerol, two second messengers. Despite its many physiological functions, no clinical phenotype has been assigned to this gene dysfunction to date. Additionally, IMPA1 is the main target of lithium, a drug that is at the forefront of treatment for bipolar disorder.

Deletion of amelotin exons 3-6 is associated with amelogenesis imperfecta

Amelogenesis imperfecta (AI) is a heterogeneous group of genetic conditions that result in defective dental enamel formation. Amelotin (AMTN) is a secreted protein thought to act as a promoter of matrix mineralization in the final stage of enamel development, and is strongly expressed, almost exclusively, in maturation stage ameloblasts. Amtn overexpression and Amtn knockout mouse models have defective enamel with no other associated phenotypes, highlighting AMTN as an excellent candidate gene for human AI. However, no AMTN mutations have yet been associated with human AI. Using whole exome sequencing, we identified an 8,678 bp heterozygous genomic deletion encompassing exons 3-6 of AMTN in a Costa Rican family segregating dominant hypomineralised AI. The deletion corresponds to an in-frame deletion of 92 amino acids, shortening the protein from 209 to 117 residues. Exfoliated primary teeth from an affected family member had enamel that was of a lower mineral density compared to control enamel and exhibited structural defects at least some of which appeared to be associated with organic material as evidenced using elemental analysis. This study demonstrates for the first time that AMTN mutations cause non-syndromic human AI and explores the human phenotype, comparing it with that of mice with disrupted Amtn function.

Whole exome sequencing identifies genetic variants in inherited thrombocytopenia with secondary qualitative function defects

Inherited thrombocytopenias are a heterogeneous group of disorders characterized by abnormally low platelet counts which can be associated with abnormal bleeding. Next-generation sequencing has previously been employed in these disorders for the confirmation of suspected genetic abnormalities, and more recently in the discovery of novel disease-causing genes. However its full potential has not yet been exploited. Over the past 6 years we have sequenced the exomes from 55 patients, including 37 index cases and 18 additional family members, all of whom were recruited to the UK Genotyping and Phenotyping of Platelets study. All patients had inherited or sustained thrombocytopenia of unknown etiology with platelet counts varying from 11×10⁹/L to 186×10⁹/L. Of the 51 patients phenotypically tested, 37 (73%), had an additional secondary qualitative platelet defect. Using whole exome sequencing analysis we have identified "pathogenic" or "likely pathogenic" variants in 46% (17/37) of our index patients with thrombocytopenia. In addition, we report variants of uncertain significance in 12 index cases, including novel candidate genetic variants in previously unreported genes in four index cases. These results demonstrate that whole exome sequencing is an efficient method for elucidating potential pathogenic genetic variants in inherited thrombocytopenia. Whole exome sequencing also has the added benefit of discovering potentially pathogenic genetic variants for further study in novel genes not previously implicated in inherited thrombocytopenia.

Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq

Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data.

Results: Our method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA.

Availability and Implementation:hapLOHseq is available at scheet.org/software, distributed under an open source MIT license.

Contact:pscheet@alum.wustl.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response

The utility of tumor-derived cell lines is dependent on their ability to recapitulate underlying genomic aberrations and primary tumor biology. Here, we sequenced the exomes of 25 bladder cancer (BCa) cell lines and compared mutations, copy number alterations (CNAs), gene expression and drug response to BCa patient profiles in The Cancer Genome Atlas (TCGA). We observed a mutation pattern associated with altered CpGs and APOBEC-family cytosine deaminases similar to mutation signatures derived from somatic alterations in muscle-invasive (MI) primary tumors, highlighting a major mechanism(s) contributing to cancer-associated alterations in the BCa cell line exomes. Non-silent sequence alterations were confirmed in 76 cancer-associated genes, including mutations that likely activate oncogenes TERT and PIK3CA, and alter chromatin-associated proteins (MLL3, ARID1A, CHD6 and KDM6A) and established BCa genes (TP53, RB1, CDKN2A and TSC1). We identified alterations in signaling pathways and proteins with related functions, including the PI3K/mTOR pathway, altered in 60% of lines; BRCA DNA repair, 44% and SYNE1–SYNE2, 60%. Homozygous deletions of chromosome 9p21 are known to target the cell cycle regulators CDKN2A and CDKN2B. This loci was commonly lost in BCa cell lines and we show the deletions extended to the polyamine enzyme methylthioadenosine (MTA) phosphorylase (MTAP) in 36% of lines, transcription factor DMRTA1 (27%) and antiviral interferon epsilon (IFNE, 19%). Overall, the BCa cell line genomic aberrations were concordant with those found in BCa patient tumors. We used gene expression and copy number data to infer pathway activities for cell lines, then used the inferred pathway activities to build a predictive model of cisplatin response. When applied to platinum-treated patients gathered from TCGA, the model predicted treatment-specific response. Together, these data and analysis represent a valuable community resource to model basic tumor biology and to study the pharmacogenomics of BCa.

Somatic copy number alterations detected by ultra-deep targeted sequencing predict prognosis in oral cavity squamous cell carcinoma

Background

Ultra-deep targeted sequencing (UDT-Seq) has advanced our knowledge on the incidence and functional significance of somatic mutations. However, the utility of UDT-Seq in detecting copy number alterations (CNAs) remains unclear. With the goal of improving molecular prognostication and identifying new therapeutic targets, we designed this study to assess whether UDT-Seq may be useful for detecting CNA in oral cavity squamous cell carcinoma (OSCC).

Methods

We sequenced a panel of clinically actionable cancer mutations in 310 formalin-fixed paraffin-embedded OSCC specimens. A linear model was developed to overcome uneven coverage across target regions and multiple samples. The 5-year rates of secondary primary tumors, local recurrence, neck recurrence, distant metastases, and survival served as the outcome measures. We confirmed the prognostic significance of the CNA signatures in an independent sample of 105 primary OSCC specimens.

Results

The CNA burden across 10 targeted genes was found to predict prognosis in two independent cohorts. FGFR1 and PIK3CAamplifications were associated with prognosis independent of clinical risk factors. Genes exhibiting CNA were clustered in the proteoglycan metabolism, the FOXO signaling, and the PI3K-AKT signaling pathways, for which targeted drugs are already available or currently under development.

Conclusions

UDT-Seq is clinically useful to identify CNA, which significantly improve the prognostic information provided by traditional clinicopathological risk factors in OSCC patients.

Candidate driver genes involved in genome maintenance and DNA repair in Sézary syndrome

Sézary syndrome (SS) is a leukemic variant of cutaneous T-cell lymphoma (CTCL) and represents an ideal model for study of T-cell transformation. We describe whole-exome and single-nucleotide polymorphism array-based copy number analyses of CD4(+) tumor cells from untreated patients at diagnosis and targeted resequencing of 101 SS cases. A total of 824 somatic nonsynonymous gene variants were identified including indels, stop-gain/loss, splice variants, and recurrent gene variants indicative of considerable molecular heterogeneity. Driver genes identified using MutSigCV include POT1, which has not been previously reported in CTCL; and TP53 and DNMT3A, which were also identified consistent with previous reports. Mutations in PLCG1 were detected in 11% of tumors including novel variants not previously described in SS. This study is also the first to show BRCA2 defects in a significant proportion (14%) of SS tumors. Aberrations in PRKCQ were found to occur in 20% of tumors highlighting selection for activation of T-cell receptor/NF-κB signaling. A complex but consistent pattern of copy number variants (CNVs) was detected and many CNVs involved genes identified as putative drivers. Frequent defects involving the POT1 and ATM genes responsible for telomere maintenance were detected and may contribute to genomic instability in SS. Genomic aberrations identified were enriched for genes implicated in cell survival and fate, specifically PDGFR, ERK, JAK STAT, MAPK, and TCR/NF-κB signaling; epigenetic regulation (DNMT3A, ASLX3, TET1-3); and homologous recombination (RAD51C, BRCA2, POLD1). This study now provides the basis for a detailed functional analysis of malignant transformation of mature T cells and improved patient stratification and treatment.

CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing

Germline copy number variants (CNVs) and somatic copy number alterations (SCNAs) are of significant importance in syndromic conditions and cancer. Massively parallel sequencing is increasingly used to infer copy number information from variations in the read depth in sequencing data. However, this approach has limitations in the case of targeted re-sequencing, which leaves gaps in coverage between the regions chosen for enrichment and introduces biases related to the efficiency of target capture and library preparation. We present a method for copy number detection, implemented in the software package CNVkit, that uses both the targeted reads and the nonspecifically captured off-target reads to infer copy number evenly across the genome. This combination achieves both exon-level resolution in targeted regions and sufficient resolution in the larger intronic and intergenic regions to identify copy number changes. In particular, we successfully inferred copy number at equivalent to 100-kilobase resolution genome-wide from a platform targeting as few as 293 genes. After normalizing read counts to a pooled reference, we evaluated and corrected for three sources of bias that explain most of the extraneous variability in the sequencing read depth: GC content, target footprint size and spacing, and repetitive sequences. We compared the performance of CNVkit to copy number changes identified by array comparative genomic hybridization. We packaged the components of CNVkit so that it is straightforward to use and provides visualizations, detailed reporting of significant features, and export options for integration into existing analysis pipelines. CNVkit is freely available from https://github.com/etal/cnvkit.

NGS-Based Assay for the Identification of Individuals Carrying Recessive Genetic Mutations in Reproductive Medicine

Next-generation sequencing (NGS) has the capacity of carrier screening in gamete donation (GD) programs. We have developed and validated an NGS carrier-screening test (qCarrier test) that includes 200 genes associated with 368 disorders (277 autosomal recessive and 37 X-linked). Carrier screening is performed on oocyte donation candidates and the male partner of oocyte recipient. Carriers of X-linked conditions are excluded from the GD program, whereas donors are chosen who do not carry mutations for the same gene/disease as the recipients. The validation phase showed a high sensitivity (>99% sensitivity) detecting all single-nucleotide variants, 13 indels, and 25 copy-number variants included in the validation set. A total of 1,301 individuals were analysed with the qCarrier test, including 483 candidate oocyte donors and 635 receptor couples, 105 females receiving sperm donation, and 39 couples seeking pregnancy. We identified 56% of individuals who are carriers for at least one genetic condition and 1.7% of female donors who were excluded from the program due to a carrier state of X-linked conditions. Globally, 3% of a priori assigned donations had a high reproductive risk that could be minimized after testing. Genetic counselling at different stages is essential for helping to facilitate a successful and healthy pregnancy.

A high-throughput sequencing test for diagnosing inherited bleeding, thrombotic, and platelet disorders

Inherited bleeding, thrombotic, and platelet disorders (BPDs) are diseases that affect ∼300 individuals per million births. With the exception of hemophilia and von Willebrand disease patients, a molecular analysis for patients with a BPD is often unavailable. Many specialized tests are usually required to reach a putative diagnosis and they are typically performed in a step-wise manner to control costs. This approach causes delays and a conclusive molecular diagnosis is often never reached, which can compromise treatment and impede rapid identification of affected relatives. To address this unmet diagnostic need, we designed a high-throughput sequencing platform targeting 63 genes relevant for BPDs. The platform can call single nucleotide variants, short insertions/deletions, and large copy number variants (though not inversions) which are subjected to automated filtering for diagnostic prioritization, resulting in an average of 5.34 candidate variants per individual. We sequenced 159 and 137 samples, respectively, from cases with and without previously known causal variants. Among the latter group, 61 cases had clinical and laboratory phenotypes indicative of a particular molecular etiology, whereas the remainder had an a priori highly uncertain etiology. All previously detected variants were recapitulated and, when the etiology was suspected but unknown or uncertain, a molecular diagnosis was reached in 56 of 61 and only 8 of 76 cases, respectively. The latter category highlights the need for further research into novel causes of BPDs. The ThromboGenomics platform thus provides an affordable DNA-based test to diagnose patients suspected of having a known inherited BPD.

Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells

Background

Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags.

Results

Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences.

Conclusions

Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0999-4) contains supplementary material, which is available to authorized users.

Exome sequencing of oral squamous cell carcinoma in users of Arabian snuff reveals novel candidates for driver genes

The study sought to identify genetic aberrations driving oral squamous cell carcinoma (OSCC) development among users of shammah, an Arabian preparation of smokeless tobacco. Twenty archival OSCC samples, 15 of which with a history of shammah exposure, were whole-exome sequenced at an average depth of 127×. Somatic mutations were identified using a novel, matched controls-independent filtration algorithm. CODEX and Exomedepth coupled with a novel, Database of Genomic Variant-based filter were employed to call somatic gene-copy number variations. Significantly mutated genes were identified with Oncodrive FM and the Youn and Simon's method. Candidate driver genes were nominated based on Gene Set Enrichment Analysis. The observed mutational spectrum was similar to that reported by the TCGA project. In addition to confirming known genes of OSCC (TP53, CDKNA2, CASP8, PIK3CA, HRAS, FAT1, TP63, CCND1 and FADD) the analysis identified several candidate novel driver events including mutations of NOTCH3, CSMD3, CRB1, CLTCL1, OSMR and TRPM2, amplification of the proto-oncogenes FOSL1, RELA, TRAF6, MDM2, FRS2 and BAG1, and deletion of the recently described tumor suppressor SMARCC1. Analysis also revealed significantly altered pathways not previously implicated in OSCC including Oncostatin-M signalling pathway, AP-1 and C-MYB transcription networks and endocytosis. There was a trend for higher number of mutations, amplifications and driver events in samples with history of shammah exposure particularly those that tested EBV positive, suggesting an interaction between tobacco exposure and EBV. The work provides further evidence for the genetic heterogeneity of oral cancer and suggests shammah-associated OSCC is characterized by extensive amplification of oncogenes.

Homozygous deletion in MICU1 presenting with fatigue and lethargy in childhood

OBJECTIVE

To define the mechanism responsible for fatigue, lethargy, and weakness in 2 cousins who had a normal muscle biopsy.

METHODS

Exome sequencing, long-range PCR, and Sanger sequencing to identify the pathogenic mutation. Functional analysis in the patient fibroblasts included oxygen consumption measurements, extracellular acidification studies, Western blotting, and calcium imaging, followed by overexpression of the wild-type protein.

RESULTS

Analysis of the exome sequencing depth revealed a homozygous deletion of exon 1 of MICU1 within a 2,755-base pair deletion. No MICU1 protein was detected in patient fibroblasts, which had impaired mitochondrial calcium uptake that was rescued through the overexpression of the wild-type allele.

CONCLUSIONS

MICU1 mutations cause fatigue and lethargy in patients with normal mitochondrial enzyme activities in muscle. The fluctuating clinical course is likely mediated through the mitochondrial calcium uniporter, which is regulated by MICU1.

Independent Loss of Methylthioadenosine Phosphorylase (MTAP) in Primary Cutaneous T-Cell Lymphoma

Methylthioadenosine phosphorylase (MTAP) and the tumor suppressor genes CDKN2A-CDKN2B are frequently deleted in malignancies. The specific role of MTAP in cutaneous T-cell lymphoma subgroups, mycosis fungoides (MF) and Sézary syndrome (SS), is unknown. In 213 skin samples from patients with MF/SS, MTAP copy number loss (34%) was more frequent than CDKN2A (12%) in all cutaneous T-cell lymphoma stages using quantitative reverse transcription PCR. Importantly, in early stage MF, MTAP loss occurred independently of CDKN2A loss in 37% of samples. In peripheral blood mononuclear cells from patients with SS, codeletion with CDKN2A occurred in 18% of samples but loss of MTAP alone was uncommon. In CD4(+) cells from SS, reduced MTAP mRNA expression correlated with MTAP copy number loss (P < 0.01) but reduced MTAP expression was also detected in the absence of copy number loss. Deep sequencing of MTAP/CDKN2A-CDKN2B loci in 77 peripheral blood mononuclear cell DNA samples from patients with SS did not show any nonsynonymous mutations, but read-depth analysis suggested focal deletions consistent with MTAP and CDKN2A copy number loss detected with quantitative reverse transcription PCR. In a cutaneous T-cell lymphoma cell line, promoter hypermethylation was shown to downregulate MTAP expression and may represent a mechanism of MTAP inactivation. In conclusion, our findings suggest that there may be selection in early stages of MF for MTAP deletion within the cutaneous tumor microenvironment.

Whole Genome Sequencing Increases Molecular Diagnostic Yield Compared with Current Diagnostic Testing for Inherited Retinal Disease

PURPOSE

To compare the efficacy of whole genome sequencing (WGS) with targeted next-generation sequencing (NGS) in the diagnosis of inherited retinal disease (IRD).

DESIGN

Case series.

PARTICIPANTS

A total of 562 patients diagnosed with IRD.

METHODS

We performed a direct comparative analysis of current molecular diagnostics with WGS. We retrospectively reviewed the findings from a diagnostic NGS DNA test for 562 patients with IRD. A subset of 46 of 562 patients (encompassing potential clinical outcomes of diagnostic analysis) also underwent WGS, and we compared mutation detection rates and molecular diagnostic yields. In addition, we compared the sensitivity and specificity of the 2 techniques to identify known single nucleotide variants (SNVs) using 6 control samples with publically available genotype data.

MAIN OUTCOME MEASURES

Diagnostic yield of genomic testing.

RESULTS

Across known disease-causing genes, targeted NGS and WGS achieved similar levels of sensitivity and specificity for SNV detection. However, WGS also identified 14 clinically relevant genetic variants through WGS that had not been identified by NGS diagnostic testing for the 46 individuals with IRD. These variants included large deletions and variants in noncoding regions of the genome. Identification of these variants confirmed a molecular diagnosis of IRD for 11 of the 33 individuals referred for WGS who had not obtained a molecular diagnosis through targeted NGS testing. Weighted estimates, accounting for population structure, suggest that WGS methods could result in an overall 29% (95% confidence interval, 15-45) uplift in diagnostic yield.

CONCLUSIONS

We show that WGS methods can detect disease-causing genetic variants missed by current NGS diagnostic methodologies for IRD and thereby demonstrate the clinical utility and additional value of WGS.

Bi-allelic Truncating Mutations in TANGO2 Cause Infancy-Onset Recurrent Metabolic Crises with Encephalocardiomyopathy

Molecular diagnosis of mitochondrial disorders is challenging because of extreme clinical and genetic heterogeneity. By exome sequencing, we identified three different bi-allelic truncating mutations in TANGO2 in three unrelated individuals with infancy-onset episodic metabolic crises characterized by encephalopathy, hypoglycemia, rhabdomyolysis, arrhythmias, and laboratory findings suggestive of a defect in mitochondrial fatty acid oxidation. Over the course of the disease, all individuals developed global brain atrophy with cognitive impairment and pyramidal signs. TANGO2 (transport and Golgi organization 2) encodes a protein with a putative function in redistribution of Golgi membranes into the endoplasmic reticulum in Drosophila and a mitochondrial localization has been confirmed in mice. Investigation of palmitate-dependent respiration in mutant fibroblasts showed evidence of a functional defect in mitochondrial β-oxidation. Our results establish TANGO2 deficiency as a clinically recognizable cause of pediatric disease with multi-organ involvement.

Next-Generation Molecular Testing of Newborn Dried Blood Spots for Cystic Fibrosis

Newborn screening for cystic fibrosis enables early detection and management of this debilitating genetic disease. Implementing comprehensive CFTR analysis using Sanger sequencing as a component of confirmatory testing of all screen-positive newborns has remained impractical due to relatively lengthy turnaround times and high cost. Here, we describe CFseq, a highly sensitive, specific, rapid (<3 days), and cost-effective assay for comprehensive CFTR gene analysis from dried blood spots, the common newborn screening specimen. The unique design of CFseq integrates optimized dried blood spot sample processing, a novel multiplex amplification method from as little as 1 ng of genomic DNA, and multiplex next-generation sequencing of 96 samples in a single run to detect all relevant CFTR mutation types. Sequence data analysis utilizes publicly available software supplemented by an expert-curated compendium of >2000 CFTR variants. Validation studies across 190 dried blood spots demonstrated 100% sensitivity and a positive predictive value of 100% for single-nucleotide variants and insertions and deletions and complete concordance across the polymorphic poly-TG and consecutive poly-T tracts. Additionally, we accurately detected both a known exon 2,3 deletion and a previously undetected exon 22,23 deletion. CFseq is thus able to replace all existing CFTR molecular assays with a single robust, definitive assay at significant cost and time savings and could be adapted to high-throughput screening of other inherited conditions.

Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing

Retinal dystrophies (RD) constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different nonsyndromic and syndromic forms of RD can be attributed to mutations in more than 200 genes. Consequently, next generation sequencing (NGS) technologies are among the most promising approaches to identify mutations in RD. We screened a large cohort of patients comprising 89 independent cases and families with various subforms of RD applying different NGS platforms. While mutation screening in 50 cases was performed using a RD gene capture panel, 47 cases were analyzed using whole exome sequencing. One family was analyzed using whole genome sequencing. A detection rate of 61% was achieved including mutations in 34 known and two novel RD genes. A total of 69 distinct mutations were identified, including 39 novel mutations. Notably, genetic findings in several families were not consistent with the initial clinical diagnosis. Clinical reassessment resulted in refinement of the clinical diagnosis in some of these families and confirmed the broad clinical spectrum associated with mutations in RD genes.

cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data

Background

With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies.

Results

We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets.

We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families.

Conclusions

In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2374-2) contains supplementary material, which is available to authorized users.

Autosomal-Dominant Corneal Endothelial Dystrophies CHED1 and PPCD1 Are Allelic Disorders Caused by Non-coding Mutations in the Promoter of OVOL2

Congenital hereditary endothelial dystrophy 1 (CHED1) and posterior polymorphous corneal dystrophy 1 (PPCD1) are autosomal-dominant corneal endothelial dystrophies that have been genetically mapped to overlapping loci on the short arm of chromosome 20. We combined genetic and genomic approaches to identify the cause of disease in extensive pedigrees comprising over 100 affected individuals. After exclusion of pathogenic coding, splice-site, and copy-number variations, a parallel approach using targeted and whole-genome sequencing facilitated the identification of pathogenic variants in a conserved region of the OVOL2 proximal promoter sequence in the index families (c.−339_361dup for CHED1 and c.−370T>C for PPCD1). Direct sequencing of the OVOL2 promoter in other unrelated affected individuals identified two additional mutations within the conserved proximal promoter sequence (c.−274T>G and c.−307T>C). OVOL2 encodes ovo-like zinc finger 2, a C2H2 zinc-finger transcription factor that regulates mesenchymal-to-epithelial transition and acts as a direct transcriptional repressor of the established PPCD-associated gene ZEB1. Interestingly, we did not detect OVOL2 expression in the normal corneal endothelium. Our in vitro data demonstrate that all four mutated OVOL2 promoters exhibited more transcriptional activity than the corresponding wild-type promoter, and we postulate that the mutations identified create cryptic cis-acting regulatory sequence binding sites that drive aberrant OVOL2 expression during endothelial cell development. Our data establish CHED1 and PPCD1 as allelic conditions and show that CHED1 represents the extreme of what can be considered a disease spectrum. They also implicate transcriptional dysregulation of OVOL2 as a common cause of dominantly inherited corneal endothelial dystrophies.

Concurrent detection of targeted copy number variants and mutations using a myeloid malignancy next generation sequencing panel allows comprehensive genetic analysis using a single testing strategy

Currently, comprehensive genetic testing of myeloid malignancies requires multiple testing strategies with high costs. Somatic mutations can be detected by next generation sequencing (NGS) but copy number variants (CNVs) require cytogenetic methods including karyotyping, fluorescence in situ hybidization and microarray. Here, we evaluated a new method for CNV detection using read depth data derived from a targeted NGS mutation panel. In a cohort of 270 samples, we detected pathogenic mutations in 208 samples and targeted CNVs in 68 cases. The most frequent CNVs were 7q deletion including LUC7L2 and EZH2, TP53 deletion, ETV6 deletion, gain of RAD21 on 8q, and 5q deletion, including NSD1 and NPM1. We were also able to detect exon-level duplications, including so-called KMT2A (MLL) partial tandem duplication, in 9 cases. In the 63 cases that were negative for mutations, targeted CNVs were observed in 4 cases. Targeted CNV detection by NGS had very high concordance with single nucleotide polymorphism microarray, the current gold standard. We found that ETV6 deletion was strongly associated with TP53 alterations and 7q deletion was associated with mutations in TP53, KRAS and IDH1. This proof-of-concept study demonstrates the feasibility of using the same NGS data to simultaneously detect both somatic mutations and targeted CNVs.

VisCap: inference and visualization of germ-line copy-number variants from targeted clinical sequencing data

Purpose:

To develop and validate VisCap, a software program targeted to clinical laboratories for inference and visualization of germ-line copy-number variants (CNVs) from targeted next-generation sequencing data.

Genet Med18 7, 712–719.

Methods:

VisCap calculates the fraction of overall sequence coverage assigned to genomic intervals and computes log2 ratios of these values to the median of reference samples profiled using the same test configuration. Candidate CNVs are called when log2 ratios exceed user-defined thresholds.

Genet Med18 7, 712–719.

Results:

We optimized VisCap using 14 cases with known CNVs, followed by prospective analysis of 1,104 cases referred for diagnostic DNA sequencing. To verify calls in the prospective cohort, we used droplet digital polymerase chain reaction (PCR) to confirm 10/27 candidate CNVs and 72/72 copy-neutral genomic regions scored by VisCap. We also used a genome-wide bead array to confirm the absence of CNV calls across panels applied to 10 cases. To improve specificity, we instituted a visual scoring system that enabled experienced reviewers to differentiate true-positive from false-positive calls with minimal impact on laboratory workflow.

Genet Med18 7, 712–719.

Conclusions:

VisCap is a sensitive method for inferring CNVs from targeted sequence data from targeted gene panels. Visual scoring of data underlying CNV calls is a critical step to reduce false-positive calls for follow-up testing.

Genet Med18 7, 712–719.

Exome sequencing explained: a practical guide to its clinical application

Next-generation sequencing has catapulted healthcare into a revolutionary genomics era. One such technology, whole-exome sequencing, which targets the protein-coding regions of the genome, has proven success in identifying new causal mutations for diseases of previously unknown etiology. With a successful diagnostic rate approaching 25% for rare disease in recent studies, its clinical utility is becoming increasingly popular. However, the interpretation of whole-exome sequencing data requires expertise in genomic informatics and clinical medicine to ensure the accurate and safe reporting of findings back to the bedside. This is challenged by vast amounts of sequencing data harbouring approximately 25 000 variants per sequenced individual. Computational strategies and fastidious filtering frameworks are thus required to extricate candidate variants in a sea of common polymorphisms. Once prioritized, identified variants require intensive scrutiny at a biological level, and require judicious assessment alongside the clinical phenotype. In the final step, all evidence is collated and documented alongside pathogenicity guidelines to produce an exome report that returns to the clinic. This review provides a practical guide for clinicians and genomic informaticians on the clinical application of whole-exome sequencing. We address sequencing capture and methodology, quality control parameters at different stages of sequencing analysis and propose an exome data filtering strategy that includes primary filtering (for the removal of probable benign variants) and secondary filtering for the prioritization of remaining candidates.

Statistical Approach to Decreasing the Error Rate of Noninvasive Prenatal Aneuploid Detection caused by Maternal Copy Number Variation

Analyses of cell-free fetal DNA (cff-DNA) from maternal plasma using massively parallel sequencing enable the noninvasive detection of feto-placental chromosome aneuploidy; this technique has been widely used in clinics worldwide. Noninvasive prenatal tests (NIPT) based on cff-DNA have achieved very high accuracy; however, they suffer from maternal copy-number variations (CNV) that may cause false positives and false negatives. In this study, we developed an algorithm to exclude the effect of maternal CNV and refined the Z-score that is used to determine fetal aneuploidy. The simulation results showed that the algorithm is robust against variations of fetal concentration and maternal CNV size. We also introduced a method based on the discrepancy between feto-placental concentrations to help reduce the false-positive ratio. A total of 6615 pregnant women were enrolled in a prospective study to validate the accuracy of our method. All 106 fetuses with T21, 20 with T18, and three with T13 were tested using our method, with sensitivity of 100% and specificity of 99.97%. In the results, two cases with maternal duplications in chromosome 21, which were falsely predicted as T21 by the previous NIPT method, were correctly classified as normal by our algorithm, which demonstrated the effectiveness of our approach.

Overexpression of KLC2 due to a homozygous deletion in the non-coding region causes SPOAN syndrome

SPOAN syndrome is a neurodegenerative disorder mainly characterized by spastic paraplegia, optic atrophy and neuropathy (SPOAN). Affected patients are wheelchair bound after 15 years old, with progressive joint contractures and spine deformities. SPOAN patients also have sub normal vision secondary to apparently non-progressive congenital optic atrophy. A potential causative gene was mapped at 11q13 ten years ago. Here we performed next-generation sequencing in SPOAN-derived samples. While whole-exome sequencing failed to identify the causative mutation, whole-genome sequencing allowed to detect a homozygous 216-bp deletion (chr11.hg19:g.66,024,557_66,024,773del) located at the non-coding upstream region of the KLC2 gene. Expression assays performed with patient's fibroblasts and motor neurons derived from SPOAN patients showed KLC2 overexpression. Luciferase assay in constructs with 216-bp deletion confirmed the overexpression of gene reporter, varying from 48 to 74%, as compared with wild-type. Knockdown and overexpression of klc2 in Danio rerio revealed mild to severe curly-tail phenotype, which is suggestive of a neuromuscular disorder. Overexpression of a gene caused by a small deletion in the non-coding region is a novel mechanism, which to the best of our knowledge, was never reported before in a recessive condition. Although the molecular mechanism of KLC2 up-regulation still remains to be uncovered, such example adds to the importance of non-coding regions in human pathology.

CLAMMS: a scalable algorithm for calling common and rare copy number variants from exome sequencing data

MOTIVATION

Several algorithms exist for detecting copy number variants (CNVs) from human exome sequencing read depth, but previous tools have not been well suited for large population studies on the order of tens or hundreds of thousands of exomes. Their limitations include being difficult to integrate into automated variant-calling pipelines and being ill-suited for detecting common variants. To address these issues, we developed a new algorithm--Copy number estimation using Lattice-Aligned Mixture Models (CLAMMS)--which is highly scalable and suitable for detecting CNVs across the whole allele frequency spectrum.

RESULTS

In this note, we summarize the methods and intended use-case of CLAMMS, compare it to previous algorithms and briefly describe results of validation experiments. We evaluate the adherence of CNV calls from CLAMMS and four other algorithms to Mendelian inheritance patterns on a pedigree; we compare calls from CLAMMS and other algorithms to calls from SNP genotyping arrays for a set of 3164 samples; and we use TaqMan quantitative polymerase chain reaction to validate CNVs predicted by CLAMMS at 39 loci (95% of rare variants validate; across 19 common variant loci, the mean precision and recall are 99% and 94%, respectively). In the Supplementary Materials (available at the CLAMMS Github repository), we present our methods and validation results in greater detail.

AVAILABILITY AND IMPLEMENTATION

https://github.com/rgcgithub/clamms (implemented in C).

CONTACT

jeffrey.reid@regeneron.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Sparse Model Based Detection of Copy Number Variations From Exome Sequencing Data

GOAL

Whole-exome sequencing provides a more cost-effective way than whole-genome sequencing for detecting genetic variants, such as copy number variations (CNVs). Although a number of approaches have been proposed to detect CNVs from whole-genome sequencing, a direct adoption of these approaches to whole-exome sequencing will often fail because exons are separately located along a genome. Therefore, an appropriate method is needed to target the specific features of exome sequencing data.

METHODS

In this paper, a novel sparse model based method is proposed to discover CNVs from multiple exome sequencing data. First, exome sequencing data are represented with a penalized matrix approximation, and technical variability and random sequencing errors are assumed to follow a generalized Gaussian distribution. Second, an iteratively reweighted least squares algorithm is used to estimate the solution.

RESULTS

The method is tested and validated on both synthetic and real data, and compared with other approaches including CoNIFER, XHMM, and cn.MOPS. The test demonstrates that the proposed method outperform other approaches.

CONCLUSION

The proposed sparse model can detect CNVs from exome sequencing data with high power and precision. Significance: Sparse model can target the specific features of exome sequencing data. The software codes are freely available at http://www.tulane.edu/ wyp/software/Exon_CNV.m.

Evaluation of somatic copy number estimation tools for whole-exome sequencing data

Whole-exome sequencing (WES) has become a standard method for detecting genetic variants in human diseases. Although the primary use of WES data has been the identification of single nucleotide variations and indels, these data also offer a possibility of detecting copy number variations (CNVs) at high resolution. However, WES data have uneven read coverage along the genome owing to the target capture step, and the development of a robust WES-based CNV tool is challenging. Here, we evaluate six WES somatic CNV detection tools: ADTEx, CONTRA, Control-FREEC, EXCAVATOR, ExomeCNV and Varscan2. Using WES data from 50 kidney chromophobe, 50 bladder urothelial carcinoma, and 50 stomach adenocarcinoma patients from The Cancer Genome Atlas, we compared the CNV calls from the six tools with a reference CNV set that was identified by both single nucleotide polymorphism array 6.0 and whole-genome sequencing data. We found that these algorithms gave highly variable results: visual inspection reveals significant differences between the WES-based segmentation profiles and the reference profile, as well as among the WES-based profiles. Using a 50% overlap criterion, 13-77% of WES CNV calls were covered by CNVs from the reference set, up to 21% of the copy gains were called as losses or vice versa, and dramatic differences in CNV sizes and CNV numbers were observed. Overall, ADTEx and EXCAVATOR had the best performance with relatively high precision and sensitivity. We suggest that the current algorithms for somatic CNV detection from WES data are limited in their performance and that more robust algorithms are needed.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

Truncating Homozygous Mutation of Carboxypeptidase E (CPE) in a Morbidly Obese Female with Type 2 Diabetes Mellitus, Intellectual Disability and Hypogonadotrophic Hypogonadism

Carboxypeptidase E is a peptide processing enzyme, involved in cleaving numerous peptide precursors, including neuropeptides and hormones involved in appetite control and glucose metabolism. Exome sequencing of a morbidly obese female from a consanguineous family revealed homozygosity for a truncating mutation of the CPE gene (c.76_98del; p.E26RfsX68). Analysis detected no CPE expression in whole blood-derived RNA from the proband, consistent with nonsense-mediated decay. The morbid obesity, intellectual disability, abnormal glucose homeostasis and hypogonadotrophic hypogonadism seen in this individual recapitulates phenotypes in the previously described fat/fat and Cpe knockout mouse models, evidencing the importance of this peptide/hormone-processing enzyme in regulating body weight, metabolism, and brain and reproductive function in humans.

Targeted NGS meets expert clinical characterization: Efficient diagnosis of spastic paraplegia type 11

Next generation sequencing (NGS) is transforming the diagnostic approach for neurological disorders, since it allows simultaneous analysis of hundreds of genes, even based on just a broad, syndromic patient categorization. However, such an approach bears a high risk of incidental and uncertain genetic findings. We report a patient with spastic paraplegia whose comprehensive neurological and imaging examination raised a high clinical suspicion of SPG11. Thus, although our NGS pipeline for this group of disorders includes gene panel and exome sequencing, in this sample only the spatacsin gene region was captured and subsequently searched for mutations. Two probably pathogenic variants were quickly and clearly identified, confirming the diagnosis of SPG11. This case illustrates how combination of expert clinical characterization with highly oriented NGS protocols leads to a fast, cost-efficient diagnosis, minimizing the risk of findings with unclear significance.

A missense mutation in KCTD17 causes autosomal dominant myoclonus-dystonia

Myoclonus-dystonia (M-D) is a rare movement disorder characterized by a combination of non-epileptic myoclonic jerks and dystonia. SGCE mutations represent a major cause for familial M-D being responsible for 30%-50% of cases. After excluding SGCE mutations, we identified through a combination of linkage analysis and whole-exome sequencing KCTD17 c.434 G>A p.(Arg145His) as the only segregating variant in a dominant British pedigree with seven subjects affected by M-D. A subsequent screening in a cohort of M-D cases without mutations in SGCE revealed the same KCTD17 variant in a German family. The clinical presentation of the KCTD17-mutated cases was distinct from the phenotype usually observed in M-D due to SGCE mutations. All cases initially presented with mild myoclonus affecting the upper limbs. Dystonia showed a progressive course, with increasing severity of symptoms and spreading from the cranio-cervical region to other sites. KCTD17 is abundantly expressed in all brain regions with the highest expression in the putamen. Weighted gene co-expression network analysis, based on mRNA expression profile of brain samples from neuropathologically healthy individuals, showed that KCTD17 is part of a putamen gene network, which is significantly enriched for dystonia genes. Functional annotation of the network showed an over-representation of genes involved in post-synaptic dopaminergic transmission. Functional studies in mutation bearing fibroblasts demonstrated abnormalities in endoplasmic reticulum-dependent calcium signaling. In conclusion, we demonstrate that the KCTD17 c.434 G>A p.(Arg145His) mutation causes autosomal dominant M-D. Further functional studies are warranted to further characterize the nature of KCTD17 contribution to the molecular pathogenesis of M-D.

Leveraging the power of high performance computing for next generation sequencing data analysis: tricks and twists from a high throughput exome workflow

Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files.

Next-generation diagnostics: gene panel, exome, or whole genome?

Although the benefits of next-generation sequencing (NGS) for the diagnosis of heterogeneous diseases such as intellectual disability (ID) are undisputed, there is little consensus on the relative merits of targeted enrichment, whole-exome sequencing (WES) or whole-genome sequencing (WGS). To answer this question, WES and WGS data from the same nine samples were compared, and WES was shown not to miss any variants identified by WGS in a gene panel including ∼500 genes linked to ID (500GP). Additionally, deeply sequenced WES data were shown to adequately cover ∼99% of the 500GP; thus, little additional benefit was to be expected from a targeted enrichment approach. To reduce costs, minimal sequencing criteria were determined by investigating the relation between sequenced reads and outcome parameters such as coverage and variant yield. Our analysis indicated that 60 million reads yielded a mean coverage of ∼60×: ∼97% of the 500GP sequences were sufficiently covered to exclude variants, whereas variant yield was ∼99.5% and false-positive and false-negative rates were controlled. Our findings indicate that WES is currently the optimal approach to ID diagnostics. This result depends on the capture kit and sequencing strategy used. The developed framework however is amenable to other sequencing approaches.

Allele-specific copy-number discovery from whole-genome and whole-exome sequencing

Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/.

Mutations in TUBGCP4 alter microtubule organization via the γ-tubulin ring complex in autosomal-recessive microcephaly with chorioretinopathy

We have identified TUBGCP4 variants in individuals with autosomal-recessive microcephaly and chorioretinopathy. Whole-exome sequencing performed on one family with two affected siblings and independently on another family with one affected child revealed compound-heterozygous mutations in TUBGCP4. Subsequent Sanger sequencing was performed on a panel of individuals from 12 French families affected by microcephaly and ophthalmic manifestations, and one other individual was identified with compound-heterozygous mutations in TUBGCP4. One synonymous variant was common to all three families and was shown to induce exon skipping; the other mutations were frameshift mutations and a deletion. TUBGCP4 encodes γ-tubulin complex protein 4, a component belonging to the γ-tubulin ring complex (γ-TuRC) and known to regulate the nucleation and organization of microtubules. Functional analysis of individual fibroblasts disclosed reduced levels of the γ-TuRC, altered nucleation and organization of microtubules, abnormal nuclear shape, and aneuploidy. Moreover, zebrafish treated with morpholinos against tubgcp4 were found to have reduced head volume and eye developmental anomalies with chorioretinal dysplasia. In summary, the identification of TUBGCP4 mutations in individuals with microcephaly and a spectrum of anomalies in eye development, particularly photoreceptor anomalies, provides evidence of an important role for the γ-TuRC in brain and eye development.

Cost effective assay choice for rare disease study designs

High throughput assays tend to be expensive per subject. Often studies are limited not so much by the number of subjects available as by assay costs, making assay choice a critical issue. We have developed a framework for assay choice that maximises the number of true disease causing mechanisms ‘seen’, given limited resources. Although straightforward, some of the ramifications of our methodology run counter to received wisdom on study design. We illustrate our methodology with examples, and have built a website allowing calculation of quantities of interest to those designing rare disease studies.

Would raising the total cholesterol diagnostic cut-off from 7.5 mmol/L to 9.3 mmol/L improve detection rate of patients with monogenic familial hypercholesterolaemia?

A previous report suggested that 88% of individuals in the general population with total cholesterol (TC) > 9.3 mmol/L have familial hypercholesterolaemia (FH). We tested this hypothesis in a cohort of 4896 UK civil servants, mean (SD) age 44 (±6) years, using next generation sequencing to achieve a comprehensive genetic diagnosis. 25 (0.5%) participants (mean age 49.2 years) had baseline TC > 9.3 mmol/L, and overall we found an FH-causing mutation in the LDLR gene in seven (28%) subjects. The detection rate increased to 39% by excluding eight participants with triglyceride levels over 2.3 mmol/L, and reached 75% in those with TC > 10.4 mmol/L. By extrapolation, the detection rate would be ∼25% by including all participants with TC > 8.6 mmol/L (2.5 standard deviations from the mean). Based on the 1/500 FH frequency, 30% of all FH-cases in this cohort would be missed using the 9.3 mmol/L cut-off. Given that an overall detection rate of 25% is considered economically acceptable, these data suggest that a diagnostic TC cut-off of 8.6 mmol/L, rather than 9.3 mmol/L would be clinically useful for FH in the general population.

•

28% of sequenced UK individuals with total cholesterol >9.3 mmol/L were found to have an FH mutation using NGS.

•

Detection rate was higher (39%) in individuals with triglycerides lower than 2.3 mmol/L.

•

By extrapolation, a 8.6 mmol/L (2.5 SD from the mean) cholesterol cut-off may be most economically sustainable.

CODEX: a normalization and copy number variation detection method for whole exome sequencing

High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.

Combinatorial approach to estimate copy number genotype using whole-exome sequencing data

Copy number variations (CNVs) are known risk factors in complex diseases. Array-based approaches have been widely used to detect CNVs, but limitations of array-based CNV detection methods, such as noisy signal and low resolution, have hindered detection of small CNVs. Recently, the development of next-generation sequencing techniques has increased rapidly owing to declines in cost. Particularly, whole-exome sequencing has proved useful for finding causal genes and variants in complex diseases. Because gene copy number may affect expression, CNV genotyping can be very valuable in disease association studies. However, almost all current CNV detection tools consider only two types of CNV genotypes. In this study, we propose a CNV genotype estimation approach using a combination of existing methods. Our approach was comprehensively compared with the customized Agilent array-comparative genomic hybridization. We found that our genotyping approach proved to be accurate, and reproducible, suggesting that it can complement existing CNV genotyping methods.

Homozygous missense mutation in MED25 segregates with syndromic intellectual disability in a large consanguineous family

BACKGROUND

Intellectual disability (ID) is a highly heterogeneous condition affecting 2% of the population worldwide. In a field study conducted in a highly inbred area of Northeastern Brazil, we investigated a consanguineous family in which seven adults presented syndromic ID.

METHODS

Genome-Wide Human SNP Array 6.0 (Affymetrix) microarray was used to determine regions of homozygosity-by-descent and whole exome sequencing (WES) was performed in one affected individual using Extended Nextera Rapid-Capture Exome and Illumina HiSeq2500.

RESULTS

We found two regions with an logarithm of the odds (LOD) score of 3.234: a region spanning 4.0 Mb in 19q13.32-q13.33 and a pericentromeric 20 Mb area in chromosome 2 (2p12-q11.2). WES disclosed in the critical region of chromosome 19 a homozygous variant (c.418C>T, p.Arg140Trp) in Mediator complex subunit 25 (MED25), predicted as deleterious by PolyPhen-2, Provean, Mutation Taster and Sorting Intolerant From Tolerant (SIFT). MED25 is a component of the Mediator complex, involved in regulation of transcription of nearly all RNA polymerase II-dependent genes. Deleterious mutations in MED12, MED17 and MED23 have already been associated with ID.

CONCLUSIONS

These findings demonstrate that the combination of field investigation of families in highly inbred regions with modern technologies is an effective way for identifying new genes associated with ID.

Copy number variation analysis based on AluScan sequences

BACKGROUND

AluScan combines inter-Alu PCR using multiple Alu-based primers with opposite orientations and next-generation sequencing to capture a huge number of Alu-proximal genomic sequences for investigation. Its requirement of only sub-microgram quantities of DNA facilitates the examination of large numbers of samples. However, the special features of AluScan data rendered difficult the calling of copy number variation (CNV) directly using the calling algorithms designed for whole genome sequencing (WGS) or exome sequencing.

RESULTS

In this study, an AluScanCNV package has been assembled for efficient CNV calling from AluScan sequencing data employing a Geary-Hinkley transformation (GHT) of read-depth ratios between either paired test-control samples, or between test samples and a reference template constructed from reference samples, to call the localized CNVs, followed by use of a GISTIC-like algorithm to identify recurrent CNVs and circular binary segmentation (CBS) to reveal large extended CNVs. To evaluate the utility of CNVs called from AluScan data, the AluScans from 23 non-cancer and 38 cancer genomes were analyzed in this study. The glioma samples analyzed yielded the familiar extended copy-number losses on chromosomes 1p and 9. Also, the recurrent somatic CNVs identified from liver cancer samples were similar to those reported for liver cancer WGS with respect to a striking enrichment of copy-number gains in chromosomes 1q and 8q. When localized or recurrent CNV-features capable of distinguishing between liver and non-liver cancer samples were selected by correlation-based machine learning, a highly accurate separation of the liver and non-liver cancer classes was attained.

CONCLUSIONS

The results obtained from non-cancer and cancerous tissues indicated that the AluScanCNV package can be employed to call localized, recurrent and extended CNVs from AluScan sequences. Moreover, both the localized and recurrent CNVs identified by this method could be subjected to machine-learning selection to yield distinguishing CNV-features that were capable of separating between liver cancers and other types of cancers. Since the method is applicable to any human DNA sample with or without the availability of a paired control, it can also be employed to analyze the constitutional CNVs of individuals.