Identification of copy number variants from exome sequence data

Chromosome 20p11.2 deletions cause congenital hyperinsulinism via the loss of FOXA2 or its regulatory elements

Persistent congenital hyperinsulinism (HI) is a rare genetically heterogeneous condition characterised by dysregulated insulin secretion leading to life-threatening hypoglycaemia. For up to 50% of affected individuals screening of the known HI genes does not identify a disease-causing variant. Large deletions have previously been used to identify novel regulatory regions causing HI. Here, we used genome sequencing to search for novel large (>1 Mb) deletions in 180 probands with HI of unknown cause and replicated our findings in a large cohort of 883 genetically unsolved individuals with HI using off-target copy number variant calling from targeted gene panels. We identified overlapping heterozygous deletions in five individuals (range 3-8 Mb) spanning chromosome 20p11.2. The pancreatic beta-cell transcription factor gene, FOXA2, a known cause of HI was deleted in two of the five individuals. In the remaining three, we found a minimal deleted region of 2.4 Mb adjacent to FOXA2 that encompasses multiple non-coding regulatory elements that are in conformational contact with FOXA2. Our data suggests that the deletions in these three children may cause disease through the dysregulation of FOXA2 expression. These findings provide new insights into the regulation of FOXA2 in the beta-cell and confirm an aetiological role for chromosome 20p11.2 deletions in syndromic HI.

Inborn errors of immunity: A field without frontiers

The study of primary immunodeficiencies or inborn errors of immunity continues to drive our knowledge of the function of the human immune system. From the outset, the study of inborn errors has focused on unraveling genetic etiologies and molecular mechanisms. Aided by the continuous growth in genetic diagnostics, the field has moved from the study of an infection dominated phenotype to embrace and unravel diverse manifestations of autoinflammation, autoimmunity, malignancy, and severe allergy in all medical disciplines. It has now moved from the study of ultrarare presentations to producing meaningful impact in conditions as diverse as inflammatory bowel disease, neurological conditions, and hematology. Beyond offering immunogenetic diagnosis, the study of underlying inborn errors of immunity in these conditions points to targeted treatment which can be lifesaving.

Detection of the Copy Number Variants of Genes in Patients with Familial Cardiac Diseases by Massively Parallel Sequencing

INTRODUCTION

The implication of copy number variations in familial heart disease is known, although in-depth knowledge is lacking; hence, more studies are needed to further our understanding. Massively parallel sequencing, thanks to its recent surge in use, is emerging as a valid tool for the detection of this type of variant, through the use of appropriate software.

METHODS

We conducted a study with 182 patients diagnosed with mendelian cardiovascular diseases who underwent sequencing using a cardiac gene panel and then a specific calling process for copy number variations (CNVs) with ExomeDepth software, which provides us with a Bayes factor (BF), a score of the probability that a CNV detected is true.

RESULTS

After a rigorous CNV prioritization process, we confirmed the variants obtained by MLPA or SNP-based array, finding three real CNVs in five individuals in the MYH11, FBN1 and PDMI7 genes.

CONCLUSION

The confirmed CNVs present in all cases BF values > 60, thus establishing a threshold to consider real CNVs in the calling process carried out by ExomeDepth on our gene panel.

Computational studies reveal co-occurrence of two mutations in IL7R gene of high-grade serous carcinoma patients

Major cause of mortality in ovarian cancer can be attributed to a lack of specific and sensitive biomarkers for diagnosis and prognosis of the disease. Uncovering the mutations in genes involved in crucial oncogenic pathways is a key step in discovery and development of novel biomarkers. Whole exome sequencing (WES) is a powerful method for the detection of cancer driver mutations. The present work focuses on identifying functionally damaging mutations in patients with high-grade serous ovarian carcinoma (HGSC) through computational analysis of WES. In this study, WES data of HGSC patients was retrieved from the genomic literature available in sequence read archive, the variants were identified and comprehensive structural and functional analysis was performed. Interestingly, I66T and V138I mutations were found to be co-occurring in the IL7R gene in four out of five HGSC patient samples investigated in this study. The V138I mutation was located in the fibronectin type-3 domain and computationally assessed to be causing disruptive effects on the structure and dynamics of IL7R protein. This mutation was found to be co-occurring with the neutral I66T mutation in the same domain which compensated the disruptive effects of V138I variant. These comprehensive studies point to a hitherto unexplored significant role of the IL7R gene in ovarian carcinoma. It is envisaged that the work will lay the foundation for the development of a novel biomarker with potential application in molecular profiling and in estimation of the disease prognosis.Communicated by Ramaswamy H. Sarma.

Prevalence of Genetic Diagnoses in a Cohort With Valvar Pulmonary Stenosis

Background:

Valvar pulmonary stenosis (vPS) accounts for 8% to 12% of congenital heart disease cases. Multiple genetic syndromes are associated with vPS, most commonly Noonan syndrome, but the cause is unknown in most cases. We analyzed genomic data from a large cohort with vPS to determine the prevalence of genetic diagnosis.

Methods:

The Pediatric Cardiac Genomics Consortium database was queried to identify probands with vPS without complex congenital heart disease or aneuploidy and with existing whole exome or genome sequencing. A custom analysis workflow was used to identify likely pathogenic or pathogenic variants in disease-associated genes. Demographic and phenotypic characteristics were compared between groups with and without molecular diagnoses.

Results:

Data from 119 probands (105 trios) were included. A molecular diagnosis was identified in 22 (18%); 17 (14%) had Noonan syndrome or a related disorder. Extracardiac and neurodevelopmental comorbidities were seen in 67/119 (56%) of probands. Molecular diagnosis was more common in those with extracardiac and neurodevelopmental phenotypes than those without (18/67 versus 4/52, P =0.0086).

Conclusions:

Clinicians should have high suspicion for a genetic diagnosis in individuals with vPS, particularly if additional phenotypes are present. Our results suggest that clinicians should consider offering sequencing of at least the known congenital heart disease and RASopathy genes to all individuals with vPS, regardless of whether that individual has extracardiac or neurodevelopmental phenotypes present.

SavvyCNV: Genome-wide CNV calling from off-target reads

Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this ‘free data’ to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite.

We have created SavvyCNV, a new tool for calling genetic variants. Large regions of the genome can be deleted or duplicated–these variants can have important consequences, for example causing a patient’s genetic disease. However, many standard genetic tests only target a small fraction of the genome and will miss variants outside of these regions. Therefore, we developed a tool to exploit sequencing data which falls outside of these regions (due to flaws in the targeting process) to call large deletions and duplications. This allows large deletions and duplications to be detected anywhere in the genome. Researchers and diagnostic laboratories can use this tool to discover more genetic variants by re-analysing their sequencing data.

Copy number variants calling from WES data through eXome hidden Markov model (XHMM) identifies additional 2.5% pathogenic genomic imbalances smaller than 30 kb undetected by array-CGH

It has been estimated that Copy Number Variants (CNVs) account for 10%-20% of patients affected by Developmental Disorder (DD)/Intellectual Disability (ID). Although array comparative genomic hybridization (array-CGH) represents the gold-standard for the detection of genomic imbalances, common Agilent array-CGH 4 × 180 kb arrays fail to detect CNVs smaller than 30 kb. Whole Exome sequencing (WES) is becoming the reference application for the detection of gene variants and makes it possible also to infer genomic imbalances at single exon resolution. However, the contribution of small CNVs in DD/ID is still underinvestigated. We made use of the eXome Hidden Markov Model (XHMM) software, a tool utilized by the ExAC consortium, to detect CNVs from whole exome sequencing data, in a cohort of 200 unsolved DD/DI patients after array-CGH and WES-based single nucleotide/indel variant analyses. In five out of 200 patients (2.5%), we identified pathogenic CNV(s) smaller than 30 kb, ranging from one to six exons. They included two heterozygous deletions in TCF4 and STXBP1 and three homozygous deletions in PPT1, CLCN2, and PIGN. After reverse phenotyping, all variants were reported as causative. This study shows the interest in applying sequencing-based CNV detection, from available WES data, to reduce the diagnostic odyssey of additional patients unsolved DD/DI patients and compare the CNV-detection yield of Agilent array-CGH 4 × 180kb versus whole exome sequencing.

VarGenius-HZD Allows Accurate Detection of Rare Homozygous or Hemizygous Deletions in Targeted Sequencing Leveraging Breadth of Coverage

Homozygous deletions (HDs) may be the cause of rare diseases and cancer, and their discovery in targeted sequencing is a challenging task. Different tools have been developed to disentangle HD discovery but a sensitive caller is still lacking. We present VarGenius-HZD, a sensitive and scalable algorithm that leverages breadth-of-coverage for the detection of rare homozygous and hemizygous single-exon deletions (HDs). To assess its effectiveness, we detected both real and synthetic rare HDs in fifty exomes from the 1000 Genomes Project obtaining higher sensitivity in comparison with state-of-the-art algorithms that each missed at least one event. We then applied our tool on targeted sequencing data from patients with Inherited Retinal Dystrophies and solved five cases that still lacked a genetic diagnosis. We provide VarGenius-HZD either stand-alone or integrated within our recently developed software, enabling the automated selection of samples using the internal database. Hence, it could be extremely useful for both diagnostic and research purposes.

isoCNV: in silico optimization of copy number variant detection from targeted or exome sequencing data

Background

Accurate copy number variant (CNV) detection is especially challenging for both targeted sequencing (TS) and whole‐exome sequencing (WES) data. To maximize the performance, the parameters of the CNV calling algorithms should be optimized for each specific dataset. This requires obtaining validated CNV information using either multiplex ligation-dependent probe amplification (MLPA) or array comparative genomic hybridization (aCGH). They are gold standard but time-consuming and costly approaches.

Results

We present isoCNV which optimizes the parameters of DECoN algorithm using only NGS data. The parameter optimization process is performed using an in silico CNV validated dataset obtained from the overlapping calls of three algorithms: CNVkit, panelcn.MOPS and DECoN. We evaluated the performance of our tool and showed that increases the sensitivity in both TS and WES real datasets.

Conclusions

isoCNV provides an easy-to-use pipeline to optimize DECoN that allows the detection of analysis-ready CNV from a set of DNA alignments obtained under the same conditions. It increases the sensitivity of DECoN without the need for orthogonal methods. isoCNV is available at https://gitlab.com/sequentiateampublic/isocnv.

Benchmarking germline CNV calling tools from exome sequencing data

Whole-exome sequencing is an attractive alternative to microarray analysis because of the low cost and potential ability to detect copy number variations (CNV) of various sizes (from 1-2 exons to several Mb). Previous comparison of the most popular CNV calling tools showed a high portion of false-positive calls. Moreover, due to a lack of a gold standard CNV set, the results are limited and incomparable. Here, we aimed to perform a comprehensive analysis of tools capable of germline CNV calling available at the moment using a single CNV standard and reference sample set. Compiling variants from previous studies with Bayesian estimation approach, we constructed an internal standard for NA12878 sample (pilot National Institute of Standards and Technology Reference Material) including 110,050 CNV or non-CNV exons. The standard was used to evaluate the performance of 16 germline CNV calling tools on the NA12878 sample and 10 correlated exomes as a reference set with respect to length distribution, concordance, and efficiency. Each algorithm had a certain range of detected lengths and showed low concordance with other tools. Most tools are focused on detection of a limited number of CNVs one to seven exons long with a false-positive rate below 50%. EXCAVATOR2, exomeCopy, and FishingCNV focused on detection of a wide range of variations but showed low precision. Upon unified comparison, the tools were not equivalent. The analysis performed allows choosing algorithms or ensembles of algorithms most suitable for a specific goal, e.g. population studies or medical genetics.

Targeted broad-based genetic testing by next-generation sequencing informs diagnosis and facilitates management in patients with kidney diseases

Background

The clinical diagnosis of genetic renal diseases may be limited by the overlapping spectrum of manifestations between diseases or by the advancement of disease where clues to the original process are absent. The objective of this study was to determine whether genetic testing informs diagnosis and facilitates management of kidney disease patients.

Methods

We developed a comprehensive genetic testing panel (KidneySeq) to evaluate patients with various phenotypes including cystic diseases, congenital anomalies of the kidney and urinary tract (CAKUT), tubulointerstitial diseases, transport disorders and glomerular diseases. We evaluated this panel in 127 consecutive patients ranging in age from newborns to 81 years who had samples sent in for genetic testing.

Results

The performance of the sequencing pipeline for single-nucleotide variants was validated using CEPH (Centre de’Etude du Polymorphism) controls and for indels using Genome-in-a-Bottle. To test the reliability of the copy number variant (CNV) analysis, positive samples were re-sequenced and analyzed. For patient samples, a multidisciplinary review board interpreted genetic results in the context of clinical data. A genetic diagnosis was made in 54 (43%) patients and ranged from 54% for CAKUT, 53% for ciliopathies/tubulointerstitial diseases, 45% for transport disorders to 33% for glomerulopathies. Pathogenic and likely pathogenic variants included 46% missense, 11% nonsense, 6% splice site variants, 23% insertion–deletions and 14% CNVs. In 13 cases, the genetic result changed the clinical diagnosis.

Conclusion

Broad genetic testing should be considered in the evaluation of renal patients as it complements other tests and provides insight into the underlying disease and its management.

Efficient detection of copy-number variations using exome data: Batch- and sex-based analyses

Many algorithms to detect copy number variations (CNVs) using exome sequencing (ES) data have been reported and evaluated on their sensitivity and specificity, reproducibility, and precision. However, operational optimization of such algorithms for a better performance has not been fully addressed. ES of 1199 samples including 763 patients with different disease profiles was performed. ES data were analyzed to detect CNVs by both the eXome Hidden Markov Model (XHMM) and modified Nord's method. To efficiently detect rare CNVs, we aimed to decrease sequencing biases by analyzing, at the same time, the data of all unrelated samples sequenced in the same flow cell as a batch, and to eliminate sex effects of X-linked CNVs by analyzing female and male sequences separately. We also applied several filtering steps for more efficient CNV selection. The average number of CNVs detected in one sample was <5. This optimization together with targeted CNV analysis by Nord's method identified pathogenic/likely pathogenic CNVs in 34 patients (4.5%, 34/763). In particular, among 142 patients with epilepsy, the current protocol detected clinically relevant CNVs in 19 (13.4%) patients, whereas the previous protocol identified them in only 14 (9.9%) patients. Thus, this batch-based XHMM analysis efficiently selected rare pathogenic CNVs in genetic diseases.

Genetic background of ataxia in children younger than 5 years in Finland

Objective

To characterize the genetic background of molecularly undefined childhood-onset ataxias in Finland.

Methods

This study examined a cohort of patients from 50 families with onset of an ataxia syndrome before the age of 5 years collected from a single tertiary center, drawing on the advantages offered by next generation sequencing. A genome-wide genotyping array (Illumina Infinium Global Screening Array MD-24 v.2.0) was used to search for copy number variation undetectable by exome sequencing.

Results

Exome sequencing led to a molecular diagnosis for 20 probands (40%). In the 23 patients examined with a genome-wide genotyping array, 2 additional diagnoses were made. A considerable proportion of probands with a molecular diagnosis had de novo pathogenic variants (45%). In addition, the study identified a de novo variant in a gene not previously linked to ataxia: MED23. Patients in the cohort had medically actionable findings.

Conclusions

There is a high heterogeneity of causative mutations in this cohort despite the defined age at onset, phenotypical overlap between patients, the founder effect, and genetic isolation in the Finnish population. The findings reflect the heterogeneous genetic background of ataxia seen worldwide and the substantial contribution of de novo variants underlying childhood ataxia.

Detection of copy-number variations from NGS data using read depth information: a diagnostic performance evaluation

The detection of copy-number variations (CNVs) from NGS data is underexploited as chip-based or targeted techniques are still commonly used. We assessed the performances of a workflow centered on CANOES, a bioinformatics tool based on read depth information. We applied our workflow to gene panel (GP) and whole-exome sequencing (WES) data, and compared CNV calls to quantitative multiplex PCR of short fluorescent fragments (QMSPF) or array comparative genomic hybridization (aCGH) results. From GP data of 3776 samples, we reached an overall positive predictive value (PPV) of 87.8%. This dataset included a complete comprehensive QMPSF comparison of four genes (60 exons) on which we obtained 100% sensitivity and specificity. From WES data, we first compared 137 samples with aCGH and filtered comparable events (exonic CNVs encompassing enough aCGH probes) and obtained an 87.25% sensitivity. The overall PPV was 86.4% following the targeted confirmation of candidate CNVs from 1056 additional WES. In addition, our CANOES-centered workflow on WES data allowed the detection of CNVs with a resolution of single exons, allowing the detection of CNVs that were missed by aCGH. Overall, switching to an NGS-only approach should be cost-effective as it allows a reduction in overall costs together with likely stable diagnostic yields. Our bioinformatics pipeline is available at: https://gitlab.bioinfo-diag.fr/nc4gpm/canoes-centered-workflow .

Application of Whole-Exome Sequencing in Detecting Copy Number Variants in Patients with Developmental Delay and/or Multiple Congenital Malformations

Overcoming challenges for the unambiguous detection of copy number variations is essential to broaden our understanding of the role of genomic variants in the clinical phenotype. With the improvement of software and databases, whole-exome sequencing quickly can become an excellent strategy in the routine diagnosis of patients with a developmental delay and/or multiple congenital malformations. However, even after a detailed analysis of pathogenic single-nucleotide variants and indels in known disease genes, using whole-exome sequencing, some patients with suspected syndromic conditions are left without a conclusive diagnosis. These negative results could be the result of different factors including nongenetic etiologies, lack of knowledge about the genes that cause different disease phenotypes, or, in some cases, a deletion or duplication of genomic information not routinely detectable by whole-exome sequencing variant calling. Although copy number variant detection is possible using whole-exome sequencing data, such analysis presents significant challenges and cannot yet be used to replace chromosomal arrays for identification of deletions or duplications.

Novel compound heterozygous variant of BSCL2 identified by whole exome sequencing and multiplex ligation‑dependent probe amplification in an infant with congenital generalized lipodystrophy

Congenital generalized lipodystrophy (CGL) is a clinically and genetically heterogeneous condition with autosomal recessive inheritance. CGL is classified into four subtypes on the basis of causative genes. This study reported on a 2-month-old male infant diagnosed with CGL with generalized lipoatrophy and skin hyperpigmentation. Whole exome sequencing (WES) identified a heterozygous small insertion (c.545_546insCCG) in Berardinelli-Seip congenital lipodystrophy 2 (BSCL2) that was inherited from the infant's mother. Copy number variation analysis using exome data suggested a heterozygous deletion involving exon 3 that was inherited from the infant's father. This finding was confirmed by multiplex ligation-dependent probe amplification test. Gap-PCR revealed breakpoints and confirmed a 1274 bp heterozygous deletion encompassing exon 3 of BSCL2 (c.213-1081_c.294+111). This deletion is different from the founder 3.3 kb deletion involving exon 3 of BSCL2 in the Peruvian population. An 11-bp microhomology at the breakpoints may mediate the deletion, and its presence indicates the independent origins of the exon 3 deletion between Chinese and Peruvian populations. The present results expanded the mutational spectrum of the BSCL2 gene in the Chinese population and suggested that introns 2 and 3 of BSCL2 are prone to recombination. Thus, exon 3 deletion should be considered for patients with CGL2 when only one BSCL2 variant is detected through WES.

Comparative study of whole exome sequencing-based copy number variation detection tools

Background

With the rapid development of whole exome sequencing (WES), an increasing number of tools are being proposed for copy number variation (CNV) detection based on this technique. However, no comprehensive guide is available for the use of these tools in clinical settings, which renders them inapplicable in practice. To resolve this problem, in this study, we evaluated the performances of four WES-based CNV tools, and established a guideline for the recommendation of a suitable tool according to the application requirements.

Results

In this study, first, we selected four WES-based CNV detection tools: CoNIFER, cn.MOPS, CNVkit and exomeCopy. Then, we evaluated their performances in terms of three aspects: sensitivity and specificity, overlapping consistency and computational costs. From this evaluation, we obtained four main results: (1) The sensitivity increases and subsequently stabilizes as the coverage or CNV size increases, while the specificity decreases. (2) CoNIFER performs better for CNV insertions than for CNV deletions, while the remaining tools exhibit the opposite trend. (3) CoNIFER, cn.MOPS and CNVkit realize satisfactory overlapping consistency, which indicates their results are trustworthy. (4) CoNIFER has the best space complexity and cn.MOPS has the best time complexity among these four tools. Finally, we established a guideline for tools’ usage according to these results.

Conclusion

No available tool performs excellently under all conditions; however, some tools perform excellently in some scenarios. Users can obtain a CNV tool recommendation from our paper according to the targeted CNV size, the CNV type or computational costs of their projects, as presented in Table 1, which is helpful even for users with limited knowledge of computer science.

Whole-Exome Sequencing Identifies Somatic Mutations Associated With Mortality in Metastatic Clear Cell Kidney Carcinoma

Clear cell renal cell carcinoma (ccRCC) is among the most aggressive histologic subtypes of kidney cancer, representing about 3% of all human cancers. Patients at stage IV have nearly 60% of mortality in 2–3 years after diagnosis. To date, most ccRCC studies have used DNA microarrays and targeted sequencing of a small set of well-established, commonly altered genes. An exception is the large multi-omics study of The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC), which identified new ccRCC genes based on whole exome-sequencing (WES) data, and molecular prognostic signatures based on transcriptomics, epigenetics and proteomics data. Applying WES to simultaneously interrogate virtually all exons in the human genome for somatic variation, here we analyzed the burden of coding somatic mutations in metastatic ccRCC primary tumors, and its association with patient mortality from cancer, in patients who received VEGF receptor-targeting drugs as the first-line therapy. To this end, we sequenced the exomes of ten tumor–normal pairs of ccRCC patient tissues from primary biopsies at >100× mean depth and called somatic coding variation. Mutation burden analysis prioritized 138 genes linked to patient mortality. A gene set enrichment analysis evidenced strong statistical support for the abundance of genes involved in the development of kidney cancer (p = 2.31 × 10⁻⁹) and carcinoma (p = 1.22 × 10⁻⁵), with 49 genes having direct links with kidney cancer according to the published records. Two of these genes, SIPA1L2 and EIF3A, demonstrated independent associations with mortality in TCGA-KIRC project data. Besides, three mutational signatures were found to be operative in the tumor exomes, one of which (COSMIC signature 12) has not been previously reported in ccRCC. Selection analysis yielded no detectable evidence of overall positive or negative selection, with the exome-wide number of nonsynonymous substitutions per synonymous site reflecting largely neutral tumor evolution. Despite the limited sample size, our results provide evidence for candidate genes where somatic mutation burden is tentatively associated with patient mortality in metastatic ccRCC, offering new potential pharmacological targets and a basis for further validation studies.

Progress in finding pathogenic DNA copy number variations in dyslipidemia

PURPOSE OF REVIEW

DNA copy number variations (CNVs) are large-scale mutations that include deletions and duplications larger than 50 bp in size. In the era when single-nucleotide variations were the major focus of genetic technology and research, CNVs were largely overlooked. However, CNVs clearly underlie a substantial proportion of clinical disorders. Here, we update recent progress in identifying CNVs in dyslipidemias.

RECENT FINDINGS

Until last year, only the LDLR and LPA genes were appreciated as loci within which clinically relevant CNVs contributed to familial hypercholesterolemia and variation in Lp(a) levels, respectively. Since 2017, next-generation sequencing panels have identified pathogenic CNVs in at least five more genes underlying dyslipidemias, including a PCSK9 whole-gene duplication in familial hypercholesterolemia; LPL, GPIHBP1, and APOC2 deletions in hypertriglyceridemia; and ABCA1 deletions in hypoalphalipoproteinemia.

SUMMARY

CNVs are an important class of mutation that contribute to the molecular genetic heterogeneity underlying dyslipidemias. Clinical applications of next-generation sequencing technologies need to consider CNVs concurrently with familiar small-scale genetic variation, given the likely implications for improved diagnosis and treatment.

High-resolution deconstruction of evolution induced by chemotherapy treatments in breast cancer xenografts

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertainty <3%. For one patient, we discovered two predominant subclones that were granularly intermixed in all 48 co-derived xenograft samples. These two subclones exhibited differential chemotherapy sensitivity–when xenografts were treated with cisplatin for 3 weeks, the post-treatment volume change was proportional to the post-treatment ratio of subclones on a xenograft-to-xenograft basis. A subsequent cohort in which xenografts were treated with cisplatin, allowed a drug holiday, then treated a second time continued to exhibit this proportionality. In contrast, xenografts from other treatment cohorts, spatially dissected xenograft fragments, and cell cultures evolved in diverse ways but with substantial population bottlenecks. These results show that ecosystems susceptible to successive retreatment can arise spontaneously in breast cancer in spite of a background of irregular subclonal bottlenecks, and our work provides to our knowledge the first quantification of the population genetics of such a system. Intriguingly, in such an ecosystem the ratio of common subclones is predictive of the state of treatment susceptibility, showing how measurements of subclonal heterogeneity could guide treatment for some patients.

Increasing the diagnostic yield of exome sequencing by copy number variant analysis

As whole exome sequencing (WES) becomes more widely used in the clinical realm, a wealth of unanalyzed information will be routinely generated. Using WES read depth data to predict copy number variation (CNV) could extend the diagnostic utility of this previously underutilized data by providing clinically important information such as previously unsuspected deletions or duplications. We evaluated ExomeDepth, a free R package, in addition to an aneuploidy prediction method, to detect CNVs in WES data. First, in a blinded pilot study, five out of five genomic alterations were correctly identified from clinical samples with previously defined chromosomal gains or losses, including submicroscopic deletions, duplications, and chromosomal trisomy. We then examined CNV calls among 53 patients participating in the NCGENES research study and undergoing WES, who had existing clinical chromosomal microarray (CMA) data that could be used for validation. For unique CNVs that overlap well with WES coverage regions, sensitivity was 89% for deletions and 65% for duplications. While specificity of the algorithm calls remains a concern, this is less of an issue at high threshold filtering levels. When applied to all 672 patients from the exome sequencing study, ExomeDepth identified eleven diagnostically relevant CNVs ranging in size from a two exon deletion to whole chromosome duplications, as well as numerous other CNVs with varying clinical significance. This opportunistic analysis of WES data yields an additional 1.6% of patients in this study with pathogenic or likely pathogenic CNVs that are clinically relevant to their phenotype as well as clinically relevant secondary findings. Finally, we demonstrate the potential value of copy number analysis in cases where a single heterozygous likely or known pathogenic single nucleotide alteration is identified in a gene associated with an autosomal recessive condition.

Perspective: DNA Copy Number Variations in Cardiovascular Diseases

Human genome contains many variations, often called mutations, which are difficult to detect and have remained a challenge for years. A substantial part of the genome encompasses repeats and when such repeats are in the coding region they may lead to change in the gene expression profile followed by pathological conditions. Structural variants are alterations which change one or more sequence feature in the chromosome such as change in the copy number, rearrangements, and translocations of a sequence and can be balanced or unbalanced. Copy number variants (CNVs) may increase or decrease the copies of a given region and have a pivotal role in the onset of many diseases including cardiovascular disorders. Cardiovascular disorders have a magnitude of well-established risk factors and etiology, but their correlation with CNVs is still being studied. In this article, we have discussed history of CNVs and a summary on the diseases associated with CNVs. To detect such variations, we shed light on the number of techniques introduced so far and their limitations. The lack of studies on cardiovascular diseases to determine the frequency of such variants needs clinical studies with larger cohorts. This review is a compilation of articles suggesting the importance of CNVs in multitude of cardiovascular anomalies. Finally, future perspectives for better understanding of CNVs and cardiovascular disorders have also been discussed.

A multiplex ligation‑dependent probe amplification‑based next‑generation sequencing approach for the detection of copy number variations in the human genome

The aim of the present study was to describe a multiplex ligation‑dependent probe amplification (MLPA)‑based next‑generation sequencing (NGS) assay that exhibited a significantly higher efficiency in detecting copy number variations (CNVs) and known single‑nucleotide variants, compared with traditional MLPA. MLPA polymerase chain reaction products were used to construct a library with indexed adapters, which was subsequently tested on an NGS platform, and the resulting data were analyzed by a series of analytical software. The reads from each probe reflected genetic variations in the target regions, and fragment differentiation was based on the specific base composition of the sequences, rather than fragment length, which was determined by capillary electrophoresis. The results of this approach were not only consistent with the MLPA results following capillary electrophoresis, but also coincided with the CNV results from the single‑nucleotide polymorphism array chip. This method allowed high‑throughput screening for the number of fragments and samples by integrating additional indices for detection. Furthermore, this technology precisely and accurately performed large‑scale detection and quantification of DNA variations, thereby serving as an effective and sensitive method for diagnosing genetic disorders caused by CNVs and known single‑nucleotide variations. Notably, MLPA‑NGS circumvents the problems associated with the inaccuracies of NGS in CNV detection due to the use of target sequence capture.

Evaluation of copy number variant detection from panel-based next-generation sequencing data

Background

Targeted gene capture and next‐generation sequencing (NGS) has been widely utilized as a robust and cost‐effective approach for detecting small variants among a group of disease genes. Copy number variations (CNV) can also be inferred from the read‐depth information but the accuracy of CNVs called from panel‐based NGS data has not been well evaluated.

Methods

Sequencing data were acquired from patients underwent routine clinical targeted panel sequencing testing. Pathogenic CNVs detected from targeted panel sequencing data were evaluated using CNVs generated by two clinical accepted platforms, namely chromosome microarray analysis (CMA) and multiple ligation‐dependent probe amplification (MLPA) as benchmarks. CNVkit was used in our study to call CNVs from sequencing data using read‐depth information. CMA and MLPA tests were used to confirm and further assess the size and breakpoints of CNVs.

Results

The size of CNVs detected using panel‐based NGS data are over 300 kb. The sizes of CNVs detected are slightly larger (102.3% on average) using the NGS platform than using the CMA platform, and the size accuracy improved as the size of variants increases. The breakpoints of CNVs detected using NGS data are quite close (within 2.3% of margin) to the breakpoints detected by CMA. CNVs on sex chromosomes, however, are less concordant between NGS and CMA platforms.

Conclusion

Copy number variations covering adequate exons on autosomes can be accurately detected using targeted panel sequencing data as using CMA. CNVs detected from sex chromosomes need further evaluation and validation. Except for exon‐level deletion/duplication and CNV on sex chromosome, our data support the use of panel‐based NGS data for routine clinical detection of pathogenic CNVs.

Whole-exome sequencing identifies an α-globin cluster triplication resulting in increased clinical severity of β-thalassemia

Whole-exome sequencing (WES) has been increasingly useful for the diagnosis of patients with rare causes of anemia, particularly when there is an atypical clinical presentation or targeted genotyping approaches are inconclusive. Here, we describe a 20-yr-old man with a lifelong moderate-to-severe anemia with accompanying splenomegaly who lacked a definitive diagnosis. After a thorough clinical workup and targeted genetic sequencing, we identified a paternally inherited β-globin mutation (HBB:c.93-21G>A, IVS-I-110:G>A), a known cause of β-thalassemia minor. As this mutation alone was inconsistent with the severity of the anemia, we performed WES. Although we could not identify any relevant pathogenic single-nucleotide variants (SNVs) or small indels, copy-number variant (CNV) analyses revealed a likely triplication of the entire α-globin cluster, which was subsequently confirmed by multiplex ligation-dependent probe amplification. Treatment and follow-up was redefined according to the diagnosis of β-thalassemia intermedia resulting from a single β-thalassemia mutation in combination with an α-globin cluster triplication. Thus, we describe a case where the typical WES-based analysis of SNVs and small indels was unrevealing, but WES-based CNV analysis resulted in a definitive diagnosis that informed clinical decision-making. More generally, this case illustrates the value of performing CNV analysis when WES is otherwise unable to elucidate a clear genetic diagnosis.

Evaluation of three read-depth based CNV detection tools using whole-exome sequencing data

Background

Whole exome sequencing (WES) has been widely accepted as a robust and cost-effective approach for clinical genetic testing of small sequence variants. Detection of copy number variants (CNV) within WES data have become possible through the development of various algorithms and software programs that utilize read-depth as the main information. The aim of this study was to evaluate three commonly used, WES read-depth based CNV detection programs using high-resolution chromosomal microarray analysis (CMA) as a standard.

Methods

Paired CMA and WES data were acquired for 45 samples. A total of 219 CNVs (size ranged from 2.3 kb – 35 mb) identified on three CMA platforms (Affymetrix, Agilent and Illumina) were used as standards. CNVs were called from WES data using XHMM, CoNIFER, and CNVnator with modified settings.

Results

All three software packages detected an elevated proportion of small variants (< 20 kb) compared to CMA. XHMM and CoNIFER had poor detection sensitivity (22.2 and 14.6%), which correlated with the number of capturing probes involved. CNVnator detected most variants and had better sensitivity (87.7%); however, suffered from an overwhelming detection of small CNVs below 20 kb, which required further confirmation. Size estimation of variants was exaggerated by CNVnator and understated by XHMM and CoNIFER.

Conclusion

Low concordances of CNV, detected by three different read-depth based programs, indicate the immature status of WES-based CNV detection. Low sensitivity and uncertain specificity of WES-based CNV detection in comparison with CMA based CNV detection suggests that CMA will continue to play an important role in detecting clinical grade CNV in the NGS era, which is largely based on WES.

Electronic supplementary material

The online version of this article (doi:10.1186/s13039-017-0333-5) contains supplementary material, which is available to authorized users.

Whole-exome sequencing and digital PCR identified a novel compound heterozygous mutation in the NPHP1 gene in a case of Joubert syndrome and related disorders

BACKGROUND

Joubert syndrome and related disorders (JSRD) is a clinically and genetically heterogeneous condition with autosomal recessive or X-linked inheritance, which share a distinctive neuroradiological hallmark, the so-called molar tooth sign. JSRD is classified into six clinical subtypes based on associated variable multiorgan involvement. To date, 21 causative genes have been identified in JSRD, which makes genetic diagnosis difficult.

CASE PRESENTATION

We report here a case of a 28-year-old Japanese woman diagnosed with JS with oculorenal defects with a novel compound heterozygous mutation (p.Ser219*/deletion) in the NPHP1 gene. Whole-exome sequencing (WES) of the patient identified the novel nonsense mutation in an apparently homozygous state. However, it was absent in her mother and heterozygous in her father. A read depth-based copy number variation (CNV) detection algorithm using WES data of the family predicted a large heterozygous deletion mutation in the patient and her mother, which was validated by digital polymerase chain reaction, indicating that the patient was compound heterozygous for the paternal nonsense mutation and the maternal deletion mutation spanning the site of the single nucleotide change.

CONCLUSION

It should be noted that analytical pipelines that focus purely on sequence information cannot distinguish homozygosity from hemizygosity because of its inability to detect large deletions. The ability to detect CNVs in addition to single nucleotide variants and small insertion/deletions makes WES an attractive diagnostic tool for genetically heterogeneous disorders.

Expanding Genetic and Functional Diagnoses of IGF1R Haploinsufficiencies

BACKGROUND

The growth-promoting effects of IGF-I is mediated through the IGF-I receptor (IGF1R), a widely expressed cell-surface tyrosine kinase receptor. IGF1R copy number variants (CNV) can cause pre- and postnatal growth restriction or overgrowth.

METHODS

Whole exome sequence (WES), chromosomal microarray, and targeted IGF1R gene analyses were performed on 3 unrelated children who share features of small for gestational age, short stature, and elevated serum IGF-I, but otherwise had clinical heterogeneity. Fluorescence-activated cell sorting (FACS) analysis of cell-surface IGF1R was performed on live primary cells derived from the patients.

RESULTS

Two novel IGF1R CNV and a heterozygous IGF1R nonsense variant were identified in the 3 patients. One CNV (4.492 Mb) was successfully called from WES, utilizing eXome-Hidden Markov Model (XHMM) analysis. FACS analysis of cell-surface IGF1R on live primary cells derived from the patients demonstrated a ∼50% reduction in IGF1R availability associated with the haploinsufficiency state.

CONCLUSION

In addition to conventional methods, IGF1R CNV can be identified from WES data. FACS analysis of live primary cells is a promising method for efficiently evaluating and screening for IGF1R haploinsufficiency. Further investigations are necessary to delineate how comparable IGF1R availability leads to the wide spectrum of clinical phenotypes and variable responsiveness to rhGH therapy.

Primary immunodeficiency diseases: Genomic approaches delineate heterogeneous Mendelian disorders

BACKGROUND

Primary immunodeficiency diseases (PIDDs) are clinically and genetically heterogeneous disorders thus far associated with mutations in more than 300 genes. The clinical phenotypes derived from distinct genotypes can overlap. Genetic etiology can be a prognostic indicator of disease severity and can influence treatment decisions.

OBJECTIVE

We sought to investigate the ability of whole-exome screening methods to detect disease-causing variants in patients with PIDDs.

METHODS

Patients with PIDDs from 278 families from 22 countries were investigated by using whole-exome sequencing. Computational copy number variant (CNV) prediction pipelines and an exome-tiling chromosomal microarray were also applied to identify intragenic CNVs. Analytic approaches initially focused on 475 known or candidate PIDD genes but were nonexclusive and further tailored based on clinical data, family history, and immunophenotyping.

RESULTS

A likely molecular diagnosis was achieved in 110 (40%) unrelated probands. Clinical diagnosis was revised in about half (60/110) and management was directly altered in nearly a quarter (26/110) of families based on molecular findings. Twelve PIDD-causing CNVs were detected, including 7 smaller than 30 Kb that would not have been detected with conventional diagnostic CNV arrays.

CONCLUSION

This high-throughput genomic approach enabled detection of disease-related variants in unexpected genes; permitted detection of low-grade constitutional, somatic, and revertant mosaicism; and provided evidence of a mutational burden in mixed PIDD immunophenotypes.

Upregulation of Glutaredoxin-1 Activates Microglia and Promotes Neurodegeneration: Implications for Parkinson's Disease

AIMS

Neuroinflammation and redox dysfunction are recognized factors in Parkinson's disease (PD) pathogenesis, and diabetes is implicated as a potentially predisposing condition. Remarkably, upregulation of glutaredoxin-1 (Grx1) is implicated in regulation of inflammatory responses in various disease contexts, including diabetes. In this study, we investigated the potential impact of Grx1 upregulation in the central nervous system on dopaminergic (DA) viability.

RESULTS

Increased GLRX copy number in PD patients was associated with earlier PD onset, and Grx1 levels correlated with levels of proinflammatory tumor necrosis factor-alpha (TNF-α) in mouse and human brain samples, prompting mechanistic in vitro studies. Grx1 content/activity in microglia was upregulated by lipopolysaccharide (LPS), or TNF-α, treatment. Adenoviral overexpression of Grx1, matching the extent of induction by LPS, increased microglial activation; Grx1 silencing diminished activation. Selective inhibitors/probes of nuclear factor κB (NF-κB) activation revealed glrx1 induction to be mediated by the Nurr1/NF-κB axis. Upregulation of Grx1 in microglia corresponded to increased death of neuronal cells in coculture. With a mouse diabetes model of diet-induced insulin resistance, we found upregulation of Grx1 in brain was associated with DA loss (decreased tyrosine hydroxylase [TH]; diminished TH-positive striatal axonal terminals); these effects were not seen with Grx1-knockout mice.

INNOVATION

Our results indicate that Grx1 upregulation promotes neuroinflammation and consequent neuronal cell death in vitro, and synergizes with proinflammatory insults to promote DA loss in vivo. Our findings also suggest a genetic link between elevated Grx1 and PD development.

CONCLUSION

In vitro and in vivo data suggest Grx1 upregulation promotes neurotoxic neuroinflammation, potentially contributing to PD. Antioxid. Redox Signal. 25, 967-982.

A potential founder variant in CARMIL2/RLTPR in three Norwegian families with warts, molluscum contagiosum, and T-cell dysfunction

Background

Four patients from three Norwegian families presented with a common skin phenotype of warts, molluscum contagiosum, and dermatitis since early childhood, and various other immunological features. Warts are a common manifestation of human papilloma virus (HPV), but when they are overwhelming, disseminated and/or persistent, and presenting together with other immunological features, a primary immunodeficiency disease (PIDD) may be suspected.

Methods and results

The four patients were exome sequenced as part of a larger study for detecting genetic causes of primary immunodeficiencies. No disease‐causing variants were identified in known primary immunodeficiency genes or in other disease‐related OMIM genes. However, the same homozygous missense variant in CARMIL2 (also known as RLTPR) was identified in all four patients. In each family, the variant was located within a narrow region of homozygosity, representing a potential region of autozygosity. CARMIL2 is a protein of undetermined function. A role in T‐cell activation has been suggested and the mouse protein homolog (Rltpr) is essential for costimulation of T‐cell activation via CD28, and for the development of regulatory T cells. Immunophenotyping demonstrated reduced regulatory, CD4+ memory, and CD4+ follicular T cells in all four patients. In addition, they all seem to have a deficiency in IFNγ ‐synthesis in CD4+ T cells and NK cells.

Conclusions

We report a novel primary immunodeficiency, and a differential molecular diagnosis to CXCR4‐,DOCK8‐,GATA2‐,MAGT1‐,MCM4‐,STK4‐,RHOH‐,TMC6‐, and TMC8‐related diseases. The specific variant may represent a Norwegian founder variant segregating on a population‐specific haplotype.

arrEYE: a customized platform for high-resolution copy number analysis of coding and noncoding regions of known and candidate retinal dystrophy genes and retinal noncoding RNAs

Purpose:

Our goal was to design a customized microarray, arrEYE, for high-resolution copy number variant (CNV) analysis of known and candidate genes for inherited retinal dystrophy (iRD) and retina-expressed noncoding RNAs (ncRNAs).

Methods:

arrEYE contains probes for the full genomic region of 106 known iRD genes, including those implicated in retinitis pigmentosa (RP) (the most frequent iRD), cone–rod dystrophies, macular dystrophies, and an additional 60 candidate iRD genes and 196 ncRNAs. Eight CNVs in iRD genes identified by other techniques were used as positive controls. The test cohort consisted of 57 patients with autosomal dominant, X-linked, or simplex RP.

Results:

In an RP patient, a novel heterozygous deletion of exons 7 and 8 of the HGSNAT gene was identified: c.634-408_820+338delinsAGAATATG, p.(Glu212Glyfs*2). A known variant was found on the second allele: c.1843G>A, p.(Ala615Thr). Furthermore, we expanded the allelic spectrum of USH2A and RCBTB1 with novel CNVs.

Conclusion:

The arrEYE platform revealed subtle single-exon to larger CNVs in iRD genes that could be characterized at the nucleotide level, facilitated by the high resolution of the platform. We report the first CNV in HGSNAT that, combined with another mutation, leads to RP, further supporting its recently identified role in nonsyndromic iRD.

Genet Med19 4, 457–466.

Unsolved challenges of clinical whole-exome sequencing: a systematic literature review of end-users' views

BACKGROUND

Whole-exome sequencing (WES) consists in the capture, sequencing and analysis of all exons in the human genome. Originally developed in the research context, this technology is now increasingly used clinically to inform patient care. The implementation of WES into healthcare poses significant organizational, regulatory, and ethical hurdles, which are widely discussed in the literature.

METHODS

In order to inform future policy decisions on the integration of WES into standard clinical practice, we performed a systematic literature review to identify the most important challenges directly reported by technology users.

RESULTS

Out of 2094 articles, we selected and analyzed 147 which reported a total of 23 different challenges linked to the production, analysis, reporting and sharing of patients' WES data. Interpretation of variants of unknown significance, incidental findings, and the cost and reimbursement of WES-based tests were the most reported challenges across all articles.

CONCLUSIONS

WES is already used in the clinical setting, and may soon be considered the standard of care for specific medical conditions. Yet, technology users are calling for certain standards and guidelines to be published before this technology replaces more focused approaches such as gene panels sequencing. In addition, a number of infrastructural adjustments will have to be made for clinics to store, process and analyze the amounts of data produced by WES.

Amplicon-based semiconductor sequencing of human exomes: performance evaluation and optimization strategies

The Ion Proton platform allows to perform whole exome sequencing (WES) at low cost, providing rapid turnaround time and great flexibility. Products for WES on Ion Proton system include the AmpliSeq Exome kit and the recently introduced HiQ sequencing chemistry. Here, we used gold standard variants from GIAB consortium to assess the performances in variants identification, characterize the erroneous calls and develop a filtering strategy to reduce false positives. The AmpliSeq Exome kit captures a large fraction of bases (>94 %) in human CDS, ClinVar genes and ACMG genes, but with 2,041 (7 %), 449 (13 %) and 11 (19 %) genes not fully represented, respectively. Overall, 515 protein coding genes contain hard-to-sequence regions, including 90 genes from ClinVar. Performance in variants detection was maximum at mean coverage >120×, while at 90× and 70× we measured a loss of variants of 3.2 and 4.5 %, respectively. WES using HiQ chemistry showed ~71/97.5 % sensitivity, ~37/2 % FDR and ~0.66/0.98 F1 score for indels and SNPs, respectively. The proposed low, medium or high-stringency filters reduced the amount of false positives by 10.2, 21.2 and 40.4 % for indels and 21.2, 41.9 and 68.2 % for SNP, respectively. Amplicon-based WES on Ion Proton platform using HiQ chemistry emerged as a competitive approach, with improved accuracy in variants identification. False-positive variants remain an issue for the Ion Torrent technology, but our filtering strategy can be applied to reduce erroneous variants.

Loss of B Cells in Patients with Heterozygous Mutations in IKAROS

BACKGROUND

Common variable immunodeficiency (CVID) is characterized by late-onset hypogammaglobulinemia in the absence of predisposing factors. The genetic cause is unknown in the majority of cases, and less than 10% of patients have a family history of the disease. Most patients have normal numbers of B cells but lack plasma cells.

METHODS

We used whole-exome sequencing and array-based comparative genomic hybridization to evaluate a subset of patients with CVID and low B-cell numbers. Mutant proteins were analyzed for DNA binding with the use of an electrophoretic mobility-shift assay (EMSA) and confocal microscopy. Flow cytometry was used to analyze peripheral-blood lymphocytes and bone marrow aspirates.

RESULTS

Six different heterozygous mutations in IKZF1, the gene encoding the transcription factor IKAROS, were identified in 29 persons from six families. In two families, the mutation was a de novo event in the proband. All the mutations, four amino acid substitutions, an intragenic deletion, and a 4.7-Mb multigene deletion involved the DNA-binding domain of IKAROS. The proteins bearing missense mutations failed to bind target DNA sequences on EMSA and confocal microscopy; however, they did not inhibit the binding of wild-type IKAROS. Studies in family members showed progressive loss of B cells and serum immunoglobulins. Bone marrow aspirates in two patients had markedly decreased early B-cell precursors, but plasma cells were present. Acute lymphoblastic leukemia developed in 2 of the 29 patients.

CONCLUSIONS

Heterozygous mutations in the transcription factor IKAROS caused an autosomal dominant form of CVID that is associated with a striking decrease in B-cell numbers. (Funded by the National Institutes of Health and others.).

Diagnosis of late-onset Pompe disease and other muscle disorders by next-generation sequencing

Background

Late-onset Pompe disease (LOPD) is a rare treatable lysosomal storage disorder characterized by progressive lysosomal glycogen accumulation and muscle weakness, with often a limb-girdle pattern. Despite published guidelines, testing for LOPD is often overlooked or delayed in adults, owing to its low frequency compared to other muscle disorders with similar muscle patterns. Next-generation sequencing has the capability to test concurrently for several muscle disorders. This could potentially lead to increased diagnosis of LOPD, disorders with non-specific muscle weakness or atypical patients.

Methods

We developed a gene panel to further study its clinical utility in a cohort of patients with suspected muscle disorders. We designed a gene panel to analyze the coding sequences and splice site junctions of GAA causing LOPD, along with 77 other genes causing muscle disorders with overlapping phenotypes.

Results

At a median coverage of ~200X (sequences per base), all GAA exons were successfully covered with >20X and only 0.3 % of exons across all genes were <20X. The panel showed an excellent sensitivity (100 %) and specificity (98 %) across all selected genes, using known variations in Pompe patients and controls. We determined its clinical utility by analyzing 34 patients with suspected muscle disorders of undetermined etiology and various muscle patterns, who were referred or followed in neuromuscular and genetics clinics. A putative diagnosis was found in up to 32 % of patients. The gene panel was instrumental in reaching a diagnosis in atypical patients, including one LOPD case. Acid alpha-glucosidase activity was used to confirm the molecular results in all patients.

Conclusion

This work highlights the high clinical utility of gene panels in patients with suspected muscle disorders and its potential to facilitate the diagnosis of patients showing non-specific muscle weakness or atypical phenotypes. We propose that gene panels should be used as a first-tier test in patients with suspected muscle disorders of undetermined etiology, which could further increase overall diagnosis of muscle conditions, and potentially reduce diagnostic delay. Further studies are necessary to determine the impact of first-tier gene panels on diagnostic delay and on treatment outcome for LOPD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13023-016-0390-6) contains supplementary material, which is available to authorized users.

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.

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.

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.

Whole-Exome Sequencing and Targeted Copy Number Analysis in Primary Ciliary Dyskinesia

Primary ciliary dyskinesia (PCD) is an autosomal-recessive disorder resulting from loss of normal ciliary function. Symptoms include neonatal respiratory distress, chronic sinusitis, bronchiectasis, situs inversus, and infertility. Clinical features may be subtle and highly variable, making the diagnosis of PCD challenging. The diagnosis can be confirmed with ciliary ultrastructure analysis and/or molecular genetic testing of 32 PCD-associated genes. However, because of this genetic heterogeneity, comprehensive molecular genetic testing is not considered the standard of care, and the most efficient molecular approach has yet to be elucidated. Here, we propose a cost-effective and time-efficient molecular genetic algorithm to solve cases of PCD. We conducted targeted copy number variation (CNV) analysis and/or whole-exome sequencing on 20 families (22 patients) from a subset of 45 families (52 patients) with a clinical diagnosis of PCD who did not have a molecular genetic diagnosis after Sanger sequencing of 12 PCD-associated genes. This combined molecular genetic approach led to the identification of 4 of 20 (20%) families with clinically significant CNVs and 7 of 20 (35%) families with biallelic pathogenic mutations in recently identified PCD genes, resulting in an increased molecular genetic diagnostic rate of 55% (11/20). In patients with a clinical diagnosis of PCD, whole-exome sequencing followed by targeted CNV analysis results in an overall molecular genetic yield of 76% (34/45).

Detection of Genomic Structural Variants from Next-Generation Sequencing Data

Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools – and their underlying algorithms – designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication – with particular emphasis on human genetics and copy number variants – for researchers involved in the investigation of these genomic events.

A genome-wide copy number variant study of suicidal behavior

Suicide and suicide attempts are complex behaviors that result from the interaction of different factors, including genetic variants that increase the predisposition to suicidal behaviors. Copy number variations (CNVs) are deletions or duplications of a segment of DNA usually larger than one kilobase. These structural genetic changes, although quite rare, have been associated with genetic liability to mental disorders, such as autism, schizophrenia, and bipolar disorder. No genome-wide level studies have been published investigating the potential role of CNVs in suicidal behaviors. Based on single-nucleotide polymorphism array data, we followed the Penn-CNV standards to detect CNVs in 1,608 subjects, comprising 475 suicide and suicide attempt cases and 1,133 controls. Although the initial algorithms determined the presence of CNVs on chromosomes 6 and 12 in seven and eight cases, respectively, compared with none of the controls, visual inspection of the raw data did not support this finding. Furthermore we were unable to validate these findings by CNV-specific real-time polymerase chain reaction. Additionally, rare CNV burden analysis did not find an association between the frequency or length of rare CNVs and suicidal behavior in our sample population. Although our findings suggest CNVs do not play an important role in the etiology of suicidal behaviors, they are not inconsistent with the strong evidence from the literature suggesting that other genetic variants account for a portion of the total phenotypic variability in suicidal behavior.

The impact of DNA input amount and DNA source on the performance of whole-exome sequencing in cancer epidemiology

BACKGROUND

Whole-exome sequencing (WES) has recently emerged as an appealing approach to systematically study coding variants. However, the requirement for a large amount of high-quality DNA poses a barrier that may limit its application in large cancer epidemiologic studies. We evaluated the performance of WES with low input amount and saliva DNA as an alternative source material.

METHODS

Five breast cancer patients were randomly selected from the Pathways Study. From each patient, four samples, including 3 μg, 1 μg, and 0.2 μg blood DNA and 1 μg saliva DNA, were aliquoted for library preparation using the Agilent SureSelect Kit and sequencing using Illumina HiSeq2500. Quality metrics of sequencing and variant calling, as well as concordance of variant calls from the whole exome and 21 known breast cancer genes, were assessed by input amount and DNA source.

RESULTS

There was little difference by input amount or DNA source on the quality of sequencing and variant calling. The concordance rate was about 98% for single-nucleotide variant calls and 83% to 86% for short insertion/deletion calls. For the 21 known breast cancer genes, WES based on low input amount and saliva DNA identified the same set variants in samples from a same patient.

CONCLUSIONS

Low DNA input amount, as well as saliva DNA, can be used to generate WES data of satisfactory quality.

IMPACT

Our findings support the expansion of WES applications in cancer epidemiologic studies where only low DNA amount or saliva samples are available.