The role and challenges of exome sequencing in studies of human diseases

Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program's strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.

Closing the gap: Solving complex medically relevant genes at scale

Comprehending the mechanism behind human diseases with an established heritable component represents the forefront of personalized medicine. Nevertheless, numerous medically important genes are inaccurately represented in short-read sequencing data analysis due to their complexity and repetitiveness or the so-called 'dark regions' of the human genome. The advent of PacBio as a long-read platform has provided new insights, yet HiFi whole-genome sequencing (WGS) cost remains frequently prohibitive. We introduce a targeted sequencing and analysis framework, Twist Alliance Dark Genes Panel (TADGP), designed to offer phased variants across 389 medically important yet complex autosomal genes. We highlight TADGP accuracy across eleven control samples and compare it to WGS. This demonstrates that TADGP achieves variant calling accuracy comparable to HiFi-WGS data, but at a fraction of the cost. Thus, enabling scalability and broad applicability for studying rare diseases or complementing previously sequenced samples to gain insights into these complex genes. TADGP revealed several candidate variants across all cases and provided insight into LPA diversity when tested on samples from rare disease and cardiovascular disease cohorts. In both cohorts, we identified novel variants affecting individual disease-associated genes (e.g., IKZF1, KCNE1). Nevertheless, the annotation of the variants across these 389 medically important genes remains challenging due to their underrepresentation in ClinVar and gnomAD. Consequently, we also offer an annotation resource to enhance the evaluation and prioritization of these variants. Overall, we can demonstrate that TADGP offers a cost-efficient and scalable approach to routinely assess the dark regions of the human genome with clinical relevance.

Incremental yield of whole-genome sequencing over chromosomal microarray analysis and exome sequencing for congenital anomalies in prenatal period and infancy: systematic review and meta-analysis

OBJECTIVES

First, to determine the incremental yield of whole-genome sequencing (WGS) over quantitative fluorescence polymerase chain reaction (QF-PCR)/chromosomal microarray analysis (CMA) with and without exome sequencing (ES) in fetuses, neonates and infants with a congenital anomaly that was or could have been detected on prenatal ultrasound. Second, to evaluate the turnaround time (TAT) and quantity of DNA required for testing using these pathways.

METHODS

This review was registered prospectively in December 2022. Ovid MEDLINE, EMBASE, MEDLINE (Web of Science), The Cochrane Library and ClinicalTrials.gov databases were searched electronically (January 2010 to December 2022). Inclusion criteria were cohort studies including three or more fetuses, neonates or infants with (i) one or more congenital anomalies; (ii) an anomaly which was or would have been detectable on prenatal ultrasound; and (iii) negative QF-PCR and CMA. In instances in which the CMA result was unavailable, all cases of causative pathogenic copy number variants > 50 kb were excluded, as these would have been detectable on standard prenatal CMA. Pooled incremental yield was determined using a random-effects model and heterogeneity was assessed using Higgins' I2 test. Subanalyses were performed based on pre- or postnatal cohorts, cases with multisystem anomalies and those meeting the NHS England prenatal ES inclusion criteria.

RESULTS

A total of 18 studies incorporating 902 eligible cases were included, of which eight (44.4%) studies focused on prenatal cohorts, incorporating 755 cases, and the remaining studies focused on fetuses undergoing postmortem testing or neonates/infants with congenital structural anomalies, constituting the postnatal cohort. The incremental yield of WGS over QF-PCR/CMA was 26% (95% CI, 18-36%) (I2  = 86%), 16% (95% CI, 9-24%) (I2  = 85%) and 39% (95% CI, 27-51%) (I2  = 53%) for all, prenatal and postnatal cases, respectively. The incremental yield increased in cases in which sequencing was performed in line with the NHS England prenatal ES criteria (32% (95% CI, 22-42%); I2  = 70%) and in those with multisystem anomalies (30% (95% CI, 19-43%); I2  = 65%). The incremental yield of WGS for variants of uncertain significance (VUS) was 18% (95% CI, 7-33%) (I2  = 74%). The incremental yield of WGS over QF-PCR/CMA and ES was 1% (95% CI, 0-4%) (I2  = 47%). The pooled median TAT of WGS was 18 (range, 1-912) days, and the quantity of DNA required was 100 ± 0 ng for WGS and 350 ± 50 ng for QF-PCR/CMA and ES (P = 0.03).

CONCLUSION

While WGS in cases with congenital anomaly holds great promise, its incremental yield over ES is yet to be demonstrated. However, the laboratory pathway for WGS requires less DNA with a potentially faster TAT compared with sequential QF-PCR/CMA and ES. There was a relatively high rate of VUS using WGS. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Acquired resistance to KRAS G12C small-molecule inhibitors via genetic/nongenetic mechanisms in lung cancer

Inherent or acquired resistance to sotorasib poses a substantialt challenge for NSCLC treatment. Here, we demonstrate that acquired resistance to sotorasib in isogenic cells correlated with increased expression of integrin β4 (ITGB4), a component of the focal adhesion complex. Silencing ITGB4 in tolerant cells improved sotorasib sensitivity, while overexpressing ITGB4 enhanced tolerance to sotorasib by supporting AKT-mTOR bypass signaling. Chronic treatment with sotorasib induced WNT expression and activated the WNT/β-catenin signaling pathway. Thus, silencing both ITGB4 and β-catenin significantly improved sotorasib sensitivity in tolerant, acquired, and inherently resistant cells. In addition, the proteasome inhibitor carfilzomib (CFZ) exhibited synergism with sotorasib by down-regulating ITGB4 and β-catenin expression. Furthermore, adagrasib phenocopies the combination effect of sotorasib and CFZ by suppressing KRAS activity and inhibiting cell cycle progression in inherently resistant cells. Overall, our findings unveil previously unrecognized nongenetic mechanisms underlying resistance to sotorasib and propose a promising treatment strategy to overcome resistance.

Genome-wide identification of exon extension/shrinkage events induced by splice-site-creating mutations

Mutations that affect phenotypes have been identified primarily as those that directly alter amino acid sequences or disrupt splice sites. However, some mutations not located in functionally important sites can also affect phenotypes, such as splice-site-creating mutations (SCMs). To investigate how frequent exon extension/shrinkage events induced by SCMs occur in normal individuals, we used personal genome sequencing data and transcriptome data of the corresponding individuals and identified 371 exon extension/shrinkage events in normal individuals. This number was about three times higher than the number of pseudo-exon activation events identified in the previous study. The average numbers of exon extension and exon shrinkage events in each sample were 3.3 and 11.2, respectively. We also evaluated the impact of exon extension/shrinkage events on the resulting transcripts and their protein products and found that 40.2% of the identified events may have possible functional impacts by either generating premature termination codons in transcripts or affecting protein domains. Our results indicated that a certain fraction of SCMs identified in this study can be pathogenic mutations by creating novel splice sites.

Clinics and genetic background of hereditary gingival fibromatosis

BACKGROUND

Hereditary gingival fibromatosis (HGF) is a rare condition characterized by slowly progressive overgrowth of the gingiva. The severity of overgrowth may differ from mild causing phonetic and masticatory issues, to severe resulting in diastemas or malposition of teeth. Both, autosomal-dominant and autosomal-recessive forms of HGF are described. The aim of this review is a clinical overview, as well as a summary and discussion of the involvement of candidate chromosomal regions, pathogenic variants of genes, and candidate genes in the pathogenesis of HGF. The loci related to non-syndromic HGF have been identified on chromosome 2 (GINGF, GINGF3), chromosome 5 (GINGF2), chromosome 11 (GINGF4), and 4 (GINGF5). Of these loci, pathogenic variants of the SOS-1 and REST genes inducing HGF have been identified in the GINGF and the GINGF5, respectively. Furthermore, among the top 10 clusters of genes ranked by enrichment score, ATP binding, and fibronectin encoding genes were proposed as related to HGF.

CONCLUSION

The analysis of clinical reports as well as translational genetic studies published since the late'90s indicate the clinical and genetic heterogeneity of non-syndromic HGF and point out the importance of genetic studies and bioinformatics of more numerous unrelated families to identify novel pathogenic variants potentially inducing HGF. This strategy will help to unravel the molecular  mechanisms as well as uncover specific targets for novel and less invasive therapies of this rare, orphan condition.

Challenges targeting cancer neoantigens in 2021: a systematic literature review

Introduction: Cancer neoantigens represent important targets of cancer immunotherapy. The goal of cancer neoantigen vaccines is to induce neoantigen-specific immune responses and antitumor immunity while minimizing the potential for autoimmune toxicity. Advances in sequencing technologies, neoantigen prediction algorithms, and other technologies have dramatically improved the ability to identify and prioritize cancer neoantigens. Unfortunately, results from preclinical studies and early phase clinical trials highlight important challenges to the successful clinical translation of neoantigen cancer vaccines.Areas covered: In this review, we provide an overview of current strategies for the identification and prioritization of cancer neoantigens with a particular emphasis on the two most common strategies used for neoantigen identification: (1) direct identification of peptide ligands eluted from peptide-MHC complexes, and (2) next-generation sequencing combined with neoantigen prediction algorithms. We highlight the limitations of current neoantigen prediction pipelines, and discuss broader challenges associated with cancer neoantigen vaccines including tumor purity/heterogeneity and the immunosuppressive tumor microenvironment.Expert opinion: Despite current limitations, neoantigen prediction is likely to improve rapidly based on advances in sequencing, machine learning, and information sharing. The successful development of robust cancer neoantigen prediction strategies is likely to have a significant impact, with the potential to facilitate cancer neoantigen vaccine design.

SICaRiO: short indel call filtering with boosting

Despite impressive improvement in the next-generation sequencing technology, reliable detection of indels is still a difficult endeavour. Recognition of true indels is of prime importance in many applications, such as personalized health care, disease genomics and population genetics. Recently, advanced machine learning techniques have been successfully applied to classification problems with large-scale data. In this paper, we present SICaRiO, a gradient boosting classifier for the reliable detection of true indels, trained with the gold-standard dataset from 'Genome in a Bottle' (GIAB) consortium. Our filtering scheme significantly improves the performance of each variant calling pipeline used in GIAB and beyond. SICaRiO uses genomic features that can be computed from publicly available resources, i.e. it does not require sequencing pipeline-specific information (e.g. read depth). This study also sheds lights on prior genomic contexts responsible for the erroneous calling of indels made by sequencing pipelines. We have compared prediction difficulty for three categories of indels over different sequencing pipelines. We have also ranked genomic features according to their predictivity in determining false positives.

A comparison of BeadChip and WGS genotyping outputs using partial validation by sanger sequencing

Background

Head-to-head comparison of BeadChip and WGS/WES genotyping techniques for their precision is far from straightforward. A tool for validation of high-throughput genotyping calls such as Sanger sequencing is neither scalable nor practical for large-scale DNA processing. Here we report a cross-validation analysis of genotyping calls obtained via Illumina GSA BeadChip and WGS (Illumina HiSeq X Ten) techniques.

Results

When compared to each other, the average precision and accuracy of BeadChip and WGS genotyping techniques exceeded 0.991 and 0.997, respectively. The average fraction of discordant variants for both platforms was found to be 0.639%. A sliding window approach was utilized to explore genomic regions not exceeding 500 bp encompassing a maximal amount of discordant variants for further validation by Sanger sequencing. Notably, 12 variants out of 26 located within eight identified regions were consistently discordant in related calls made by WGS and BeadChip. When Sanger sequenced, a total of 16 of these genotypes were successfully resolved, indicating that a precision of WGS and BeadChip genotyping for this genotype subset was at 0.81 and 0.5, respectively, with accuracy values of 0.87 and 0.61.

Conclusions

We conclude that WGS genotype calling exhibits higher overall precision within the selected variety of discordantly genotyped variants, though the amount of validated variants remained insufficient.

Review: Understanding Rare Genetic Diseases in Low Resource Regions Like Jammu and Kashmir - India

Rare diseases (RDs) are the clinical conditions affecting a few percentage of individuals in a general population compared to other diseases. Limited clinical information and a lack of reliable epidemiological data make their timely diagnosis and therapeutic management difficult. Emerging Next-Generation DNA Sequencing technologies have enhanced our horizons on patho-physiological understanding of many of the RDs and ushered us into an era of diagnostic and therapeutic research related to this ignored health challenge. Unfortunately, relevant research is meager in developing countries which lack a reliable estimate of the exact burden of most of the RDs. India is to be considered as the "Pandora's Box of genetic disorders." Owing to its huge population heterogeneity and high inbreeding or endogamy rates, a higher burden of rare recessive genetic diseases is expected and supported by the literature findings that endogamy is highly detrimental to health as it enhances the degree of homozygosity of recessive alleles in the general population. The population of a low resource region Jammu and Kashmir (J&K) - India, is highly inbred. Some of its population groups variably practice consanguinity. In context with the region's typical geographical topography, highly inbred population structure and unique but heterogeneous gene pool, a huge burden of known and uncharacterized genetic disorders is expected. Unfortunately, many suspected cases of genetic disorders remain undiagnosed or misdiagnosed due to lack of appropriate clinical as well as diagnostic resources in the region, causing patients to face a huge psycho-socio-economic crisis and many a time suffer life-long with their ailment. In this review, the major challenges associated with RDs are highlighted in general and an account on the methods that can be adopted for conducting fruitful molecular genetic studies in genetically vulnerable and low resource regions is also provided, with an example of a region like J&K - India.

Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage

Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated. WES dominated large-scale resequencing projects because of lower cost and easier data storage and processing. Rapid development of 3^rd generation sequencing methods and novel exome sequencing kits predicate the need for a robust statistical framework allowing informative and easy performance comparison of the emerging methods. In our study we developed a set of statistical tools to systematically assess coverage of coding regions provided by several modern WES platforms, as well as PCR-free WGS. We identified a substantial problem in most previously published comparisons which did not account for mappability limitations of short reads. Using regression analysis and simple machine learning, as well as several novel metrics of coverage evenness, we analyzed the contribution from the major determinants of CDS coverage. Contrary to a common view, most of the observed bias in modern WES stems from mappability limitations of short reads and exome probe design rather than sequence composition. We also identified the ~ 500 kb region of human exome that could not be effectively characterized using short read technology and should receive special attention during variant analysis. Using our novel metrics of sequencing coverage, we identified main determinants of WES and WGS performance. Overall, our study points out avenues for improvement of enrichment-based methods and development of novel approaches that would maximize variant discovery at optimal cost.

Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives

Genomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy in silico detection and analysis of clinically relevant mutations. However, the variability in the in silico prediction methods and categorization of functionally relevant genetic variants can pose specific challenges in some populations. In silico mutation prediction tools could lead to high rates of false positive/negative results, particularly in African genomes that harbor the highest genetic diversity and that are disproportionately underrepresented in public databases and reference panels. These issues are particularly relevant with the recent increase in initiatives, such as the Human Heredity and Health (H3Africa), that are generating huge amounts of genomic sequence data in the absence of policies to guide genomic researchers to return results of variants in so-called actionable genes to research participants. This report (i) provides an inventory of publicly available Whole Exome/Genome data from Africa which could help improve reference panels and explore the frequency of pathogenic variants in actionable genes and related challenges, (ii) reviews available in silico prediction mutation tools and the criteria for categorization of pathogenicity of novel variants, and (iii) proposes recommendations for analyzing pathogenic variants in African genomes for their use in research and clinical practice. In conclusion, this work proposes criteria to define mutation pathogenicity and actionability in human genetic research and clinical practice in Africa and recommends setting up an African expert panel to oversee the proposed criteria.

Genome sequencing and implications for rare disorders

The practice of genomic medicine stands to revolutionize our approach to medical care, and to realize this goal will require discovery of the relationship between rare variation at each of the ~ 20,000 protein-coding genes and their consequent impact on individual health and expression of Mendelian disease. The step-wise evolution of broad-based, genome-wide cytogenetic and molecular genomic testing approaches (karyotyping, chromosomal microarray [CMA], exome sequencing [ES]) has driven much of the rare disease discovery to this point, with genome sequencing representing the newest member of this team. Each step has brought increased sensitivity to interrogate individual genomic variation in an unbiased method that does not require clinical prediction of the locus or loci involved. Notably, each step has also brought unique limitations in variant detection, for example, the low sensitivity of ES for detection of triploidy, and of CMA for detection of copy neutral structural variants. The utility of genome sequencing (GS) as a clinical molecular diagnostic test, and the increased sensitivity afforded by addition of long-read sequencing or other -omics technologies such as RNAseq or metabolomics, are not yet fully explored, though recent work supports improved sensitivity of variant detection, at least in a subset of cases. The utility of GS will also rely upon further elucidation of the complexities of genetic and allelic heterogeneity, multilocus rare variation, and the impact of rare and common variation at a locus, as well as advances in functional annotation of identified variants. Much discovery remains to be done before the potential utility of GS is fully appreciated.

A Key Role for the Genetic Counsellor in the Genomics Era

New genetic testing technologies such as microarrays and whole exome sequencing mean the diagnostic potential for a child with a development disorder is greatly increased over traditional testing techniques.  With this increased potential comes increased expectations from families and professionals about the answers a diagnosis will provide.  However, limitations remain and a proportion of individuals will continue to remain undiagnosed.  In addition, some individuals will receive novel or very rare diagnoses about which very little is known in terms of prognosis and effective treatments.  In this paper, I present an argument for why these families would benefit from additional Genetic Counsellor support and how Clinical Genetics services in the UK could provide this support.  I acknowledge that resources are limited, but as demands on services increase and interactions with families become shorter, I argue that this kind of service should be prioritised, for the benefit of these families.

Whole exome sequencing reveals HSPA1L as a genetic risk factor for spontaneous preterm birth

Preterm birth is a leading cause of morbidity and mortality in infants. Genetic and environmental factors play a role in the susceptibility to preterm birth, but despite many investigations, the genetic basis for preterm birth remain largely unknown. Our objective was to identify rare, possibly damaging, nucleotide variants in mothers from families with recurrent spontaneous preterm births (SPTB). DNA samples from 17 Finnish mothers who delivered at least one infant preterm were subjected to whole exome sequencing. All mothers were of northern Finnish origin and were from seven multiplex families. Additional replication samples of European origin consisted of 93 Danish sister pairs (and two sister triads), all with a history of a preterm delivery. Rare exonic variants (frequency <1%) were analyzed to identify genes and pathways likely to affect SPTB susceptibility. We identified rare, possibly damaging, variants in genes that were common to multiple affected individuals. The glucocorticoid receptor signaling pathway was the most significant (p<1.7e-8) with genes containing these variants in a subgroup of ten Finnish mothers, each having had 2-4 SPTBs. This pathway was replicated among the Danish sister pairs. A gene in this pathway, heat shock protein family A (Hsp70) member 1 like (HSPA1L), contains two likely damaging missense alleles that were found in four different Finnish families. One of the variants (rs34620296) had a higher frequency in cases compared to controls (0.0025 vs. 0.0010, p = 0.002) in a large preterm birth genome-wide association study (GWAS) consisting of mothers of general European ancestry. Sister pairs in replication samples also shared rare, likely damaging HSPA1L variants. Furthermore, in silico analysis predicted an additional phosphorylation site generated by rs34620296 that could potentially affect chaperone activity or HSPA1L protein stability. Finally, in vitro functional experiment showed a link between HSPA1L activity and decidualization. In conclusion, rare, likely damaging, variants in HSPA1L were observed in multiple families with recurrent SPTB.

Effective discovery of rare variants by pooled target capture sequencing: A comparative analysis with individually indexed target capture sequencing

Identification of all genetic variants associated with complex traits is one of the most important goals in modern human genetics. Genome-wide association studies (GWAS) have been successfully applied to identify common variants, which thus far explain only small portion of heritability. Interests in rare variants have been increasingly growing as an answer for this missing heritability. While next-generation sequencing allows detection of rare variants, its cost is still prohibitively high to sequence a large number of human DNA samples required for rare variant association studies. In this study, we evaluated the sensitivity and specificity of sequencing for pooled DNA samples of multiple individuals (Pool-seq) as a cost-effective and robust approach for rare variant discovery. We comparatively analyzed Pool-seq vs. individual-seq of indexed target capture of up to 960 genes in ∼1000 individuals, followed by independent genotyping validation studies. We found that Pool-seq was as effective and accurate as individual-seq in detecting rare variants and accurately estimating their minor allele frequencies (MAFs). Our results suggest that Pool-seq can be used as an efficient and cost-effective method for discovery of rare variants for population-based sequencing studies in individual laboratories.

Next-generation sequencing identifies articular cartilage and subchondral bone miRNAs after ESWT on early osteoarthritis knee

Extracorporeal shockwave therapy (ESWT) has shown chondroprotective effects on the initiation of the osteoarthritis (OA) changes of the rat knee. This study evaluated 69 significant expressed profiles of microRNA (miRNA) in the articular cartilage and subchondral bone after ESWT. There were 118 target genes identified for miRNAs of interest in articular cartilage and 214 target genes in subchondral bone by next generation sequencing (NGS). In principal component analysis (PCA), the relationships of miRNA expression in bone and cartilage were improved after ESWT. Global functional annotation showed that predicted targets were involved in cartilage development, inflammatory and immune response, ion binding, angiogenesis, cell adhesion, cell cycle, transcription and translation, gene expression, NTP binding, signal transduction, collagen fibril organization, apoptotic process, chondrocyte differentiation, cell differentiation, bone development as well as cell proliferation. The miRNAs profile and the target genes were comprehensively surveyed and compared in articular cartilage and subchondral bone of early OA knee before and after ESWT. Our study represents the direct assessment to date of miRNA expression profiling in early OA articular cartilage and subchondral bone. The results provide insights that could contribute to the development of new biomarkers and therapeutic strategies for OA changes and the treatment with ESWT.

MTTE: an innovative strategy for the evaluation of targeted/exome enrichment efficiency

Although currently available strategies for the preparation of exome-enriched libraries are well established, a final validation of the libraries in terms of exome enrichment efficiency prior to the sequencing step is of considerable importance. Here, we present a strategy for the evaluation of exome enrichment, i.e., the Multipoint Test for Targeted-enrichment Efficiency (MTTE), PCR-based approach utilizing multiplex ligation-dependent probe amplification with capillary electrophoresis separation. We used MTTE for the analysis of subsequent steps of the Illumina TruSeq Exome Enrichment procedure. The calculated values of enrichment-associated parameters (i.e., relative enrichment, relative clearance, overall clearance, and fold enrichment) and the comparison of MTTE results with the actual enrichment revealed the high reliability of our assay. Additionally, the MTTE assay enabled the determination of the sequence-associated features that may confer bias in the enrichment of different targets. Importantly, the MTTE is low cost method that can be easily adapted to the region of interest important for a particular project. Thus, the MTTE strategy is attractive for post-capture validation in a variety of targeted/exome enrichment NGS projects.

Whole-exome sequencing and gene-based rare variant association tests suggest that PLA2G4E might be a risk gene for panic disorder

Panic disorder (PD) is characterized by recurrent and unexpected panic attacks, subsequent anticipatory anxiety, and phobic avoidance. Recent epidemiological and genetic studies have revealed that genetic factors contribute to the pathogenesis of PD. We performed whole-exome sequencing on one Japanese family, including multiple patients with panic disorder, which identified seven rare protein-altering variants. We then screened these genes in a Japanese PD case-control group (384 sporadic PD patients and 571 controls), resulting in the detection of three novel single nucleotide variants as potential candidates for PD (chr15: 42631993, T>C in GANC; chr15: 42342861, G>T in PLA2G4E; chr20: 3641457, G>C in GFRA4). Statistical analyses of these three genes showed that PLA2G4E yielded the lowest p value in gene-based rare variant association tests by Efficient and Parallelizable Association Container Toolbox algorithms; however, the p value did not reach the significance threshold in the Japanese. Likewise, in a German case-control study (96 sporadic PD patients and 96 controls), PLA2G4E showed the lowest p value but again did not reach the significance threshold. In conclusion, we failed to find any significant variants or genes responsible for the development of PD. Nonetheless, our results still leave open the possibility that rare protein-altering variants in PLA2G4E contribute to the risk of PD, considering the function of this gene.

Utility of rapid whole-exome sequencing in the diagnosis of Niemann-Pick disease type C presenting with fetal hydrops and acute liver failure

Rapid whole-exome sequencing (rWES) is used in critically ill newborn infants to inform about diagnosis, clinical management, and prognosis. Here we report a male newborn infant with hydrops, pancytopenia, and acute liver failure who was listed for liver transplantation. Given the acuity of the presentation, the procedure-related morbidity and mortality, and lack of diagnosis, we used rWES in the proband and both parents with a turnaround time of 10 business days. rWES returned one maternally inherited, likely pathogenic and one paternally inherited, likely pathogenic variant in NPC1, suggestive of a diagnosis of Niemann–Pick disease type C (NPC). Interestingly, a diagnosis of NPC was entertained prior to rWES, but deemed unlikely in light of absent cholesterol storage on liver biopsy and near-normal oxysterol levels in dried blood. The diagnosis of NPC was confirmed on filipin stain in fibroblasts demonstrating defective cholesterol trafficking. NPC is a slowly progressive neurodegenerative disorder that may also affect the liver with overall poor prognosis. It was decided to take the infant off the transplant list and transfer to palliative care, where he died after 4 wk. This case highlights the utility of rWES in an acute clinical setting for several domains of precision medicine including (1) diagnosis, (2) prognosis and outcome, (3) management and therapy, and (4) utilization of resources.

Whole-exome analysis in osteosarcoma to identify a personalized therapy

Osteosarcoma is the most common pediatric primary non-hematopoietic bone tumor. Survival of these young patients is related to the response to chemotherapy and development of metastases. Despite many advances in cancer research, chemotherapy regimens for osteosarcoma are still based on non-selective cytotoxic drugs. It is essential to investigate new specific molecular therapies for osteosarcoma to increase the survival rate of these patients. We performed exomic sequence analyses of 8 diagnostic biopsies of patients with conventional high grade osteosarcoma to advance our understanding of their genetic underpinnings and to correlate the genetic alteration with the clinical and pathological features of each patient to identify a personalized therapy. We identified 18,275 somatic variations in 8,247 genes and we found three mutated genes in 7/8 (87%) samples (KIF1B, NEB and KMT2C). KMT2C showed the highest number of variations; it is an important component of a histone H3 lysine 4 methyltransferase complex and it is one of the histone modifiers previously implicated in carcinogenesis, never studied in osteosarcoma. Moreover, we found a group of 15 genes that showed variations only in patients that did not respond to therapy and developed metastasis and some of these genes are involved in carcinogenesis and tumor progression in other tumors. These data could offer the opportunity to get a key molecular target to identify possible new strategies for early diagnosis and new therapeutic approaches for osteosarcoma and to provide a tailored treatment for each patient based on their genetic profile.

Analysis of potential protein-modifying variants in 9000 endometriosis patients and 150000 controls of European ancestry

Genome-wide association (GWA) studies have identified 19 independent common risk loci for endometriosis. Most of the GWA variants are non-coding and the genes responsible for the association signals have not been identified. Herein, we aimed to assess the potential role of protein-modifying variants in endometriosis using exome-array genotyping in 7164 cases and 21005 controls, and a replication set of 1840 cases and 129016 controls of European ancestry. Results in the discovery sample identified significant evidence for association with coding variants in single-variant (rs1801232-CUBN) and gene-level (CIITA and PARP4) meta-analyses, but these did not survive replication. In the combined analysis, there was genome-wide significant evidence for rs13394619 (P = 2.3 × 10⁻⁹) in GREB1 at 2p25.1 — a locus previously identified in a GWA meta-analysis of European and Japanese samples. Despite sufficient power, our results did not identify any protein-modifying variants (MAF > 0.01) with moderate or large effect sizes in endometriosis, although these variants may exist in non-European populations or in high-risk families. The results suggest continued discovery efforts should focus on genotyping large numbers of surgically-confirmed endometriosis cases and controls, and/or sequencing high-risk families to identify novel rare variants to provide greater insights into the molecular pathogenesis of the disease.

REST Final-Exon-Truncating Mutations Cause Hereditary Gingival Fibromatosis

Hereditary gingival fibromatosis (HGF) is the most common genetic form of gingival fibromatosis that develops as a slowly progressive, benign, localized or generalized enlargement of keratinized gingiva. HGF is a genetically heterogeneous disorder and can be transmitted either as an autosomal-dominant or autosomal-recessive trait or appear sporadically. To date, four loci (2p22.1, 2p23.3-p22.3, 5q13-q22, and 11p15) have been mapped to autosomes and one gene (SOS1) has been associated with the HGF trait observed to segregate in a dominant inheritance pattern. Here we report 11 individuals with HGF from three unrelated families. Whole-exome sequencing (WES) revealed three different truncating mutations including two frameshifts and one nonsense variant in RE1-silencing transcription factor (REST) in the probands from all families and further genetic and genomic analyses confirmed the WES-identified findings. REST is a transcriptional repressor that is expressed throughout the body; it has different roles in different cellular contexts, such as oncogenic and tumor-suppressor functions and hematopoietic and cardiac differentiation. Here we show the consequences of germline final-exon-truncating mutations in REST for organismal development and the association with the HGF phenotype.

A Path to Implement Precision Child Health Cardiovascular Medicine

Congenital heart defects (CHDs) affect approximately 1% of live births and are a major source of childhood morbidity and mortality even in countries with advanced healthcare systems. Along with phenotypic heterogeneity, the underlying etiology of CHDs is multifactorial, involving genetic, epigenetic, and/or environmental contributors. Clear dissection of the underlying mechanism is a powerful step to establish individualized therapies. However, the majority of CHDs are yet to be clearly diagnosed for the underlying genetic and environmental factors, and even less with effective therapies. Although the survival rate for CHDs is steadily improving, there is still a significant unmet need for refining diagnostic precision and establishing targeted therapies to optimize life quality and to minimize future complications. In particular, proper identification of disease associated genetic variants in humans has been challenging, and this greatly impedes our ability to delineate gene–environment interactions that contribute to the pathogenesis of CHDs. Implementing a systematic multileveled approach can establish a continuum from phenotypic characterization in the clinic to molecular dissection using combined next-generation sequencing platforms and validation studies in suitable models at the bench. Key elements necessary to advance the field are: first, proper delineation of the phenotypic spectrum of CHDs; second, defining the molecular genotype/phenotype by combining whole-exome sequencing and transcriptome analysis; third, integration of phenotypic, genotypic, and molecular datasets to identify molecular network contributing to CHDs; fourth, generation of relevant disease models and multileveled experimental investigations. In order to achieve all these goals, access to high-quality biological specimens from well-defined patient cohorts is a crucial step. Therefore, establishing a CHD BioCore is an essential infrastructure and a critical step on the path toward precision child health cardiovascular medicine.

Molecular Genetics of Neurodegenerative Dementias

Neurodegenerative dementias are clinically heterogeneous, progressive diseases with frequently overlapping symptoms, such as cognitive impairments and behavior and movement deficits. Although a majority of cases appear to be sporadic, there is a large genetic component that has yet to be fully explained. Here, we review the recent genetic and genomic findings pertaining to Alzheimer's disease, frontotemporal dementia, Lewy body dementia, and prion dementia. In this review, we describe causal and susceptibility genes identified for these dementias and discuss recent research pertaining to the molecular function of these genes. Of particular interest, there is a large overlap in clinical phenotypes, genes, and/or aggregating protein products involved in these diseases, as well as frequent comorbid presentation, indicating that these dementias may represent a continuum of syndromes rather than individual diseases.

Identification of a novel DMD duplication identified by a combination of MLPA and targeted exome sequencing

Background

Duchenne muscular dystrophy (DMD) is an X-linked recessive muscle-wasting disease caused by a mutation in the DMD gene. The aim of this study was to identify a de novo mutation of the DMD gene in the family of a 9-month-old Chinese male patient, as well as to describe the phenotypic characteristics of this patient.

Results

The patient was suspected to suffer from DMD according to physical examination, biochemical analyses, and electromyogram. We identified a duplication of exons 4–42 in DMD gene with targeted exome sequencing and multiplex ligation-dependent probe amplification (MLPA). In addition, the patient’s mother was a carrier of the same mutation.

Conclusions

We identified a de novo duplication of exons 4–42 in a patient with early stage DMD. The discovery of this mutation may provide insights into future investigations.

The genetic background of Parkinson's disease: current progress and future prospects

Almost two decades of genetic research in Parkinson's disease (PD) have remarkably increased our knowledge regarding the genetic basis of PD with numerous genes and genetic loci having been found to cause familial PD or affect the risk for PD. Approximately 5-10% of PD patients have monogenic forms of the disease, exhibiting a classical Mendelian type of inheritance, however, the majority PD cases are sporadic, probably caused by a combination of genetic and environmental risk factors. Nowadays, six genes, alpha synuclein, LRRK2, VPS35, Parkin, PINK1 and DJ-1, have definitely been associated with an autosomal dominant or recessive PD mode of inheritance. The advent of genome-wide association studies (GWAS) and the implementation of new technologies, like next generation sequencing (NGS) and exome sequencing has undoubtedly greatly aided the identification on novel risk variants for sporadic PD. In this review, we will summarize the current progress and future prospects in the field of PD genetics.

Impact of post-alignment processing in variant discovery from whole exome data

Background

GATK Best Practices workflows are widely used in large-scale sequencing projects and recommend post-alignment processing before variant calling. Two key post-processing steps include the computationally intensive local realignment around known INDELs and base quality score recalibration (BQSR). Both have been shown to reduce erroneous calls; however, the findings are mainly supported by the analytical pipeline that incorporates BWA and GATK UnifiedGenotyper. It is not known whether there is any benefit of post-processing and to what extent the benefit might be for pipelines implementing other methods, especially given that both mappers and callers are typically updated. Moreover, because sequencing platforms are upgraded regularly and the new platforms provide better estimations of read quality scores, the need for post-processing is also unknown. Finally, some regions in the human genome show high sequence divergence from the reference genome; it is unclear whether there is benefit from post-processing in these regions.

Results

We used both simulated and NA12878 exome data to comprehensively assess the impact of post-processing for five or six popular mappers together with five callers. Focusing on chromosome 6p21.3, which is a region of high sequence divergence harboring the human leukocyte antigen (HLA) system, we found that local realignment had little or no impact on SNP calling, but increased sensitivity was observed in INDEL calling for the Stampy + GATK UnifiedGenotyper pipeline. No or only a modest effect of local realignment was detected on the three haplotype-based callers and no evidence of effect on Novoalign. BQSR had virtually negligible effect on INDEL calling and generally reduced sensitivity for SNP calling that depended on caller, coverage and level of divergence. Specifically, for SAMtools and FreeBayes calling in the regions with low divergence, BQSR reduced the SNP calling sensitivity but improved the precision when the coverage is insufficient. However, in regions of high divergence (e.g., the HLA region), BQSR reduced the sensitivity of both callers with little gain in precision rate. For the other three callers, BQSR reduced the sensitivity without increasing the precision rate regardless of coverage and divergence level.

Conclusions

We demonstrated that the gain from post-processing is not universal; rather, it depends on mapper and caller combination, and the benefit is influenced further by sequencing depth and divergence level. Our analysis highlights the importance of considering these key factors in deciding to apply the computationally intensive post-processing to Illumina exome data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1279-z) contains supplementary material, which is available to authorized users.

An analytical workflow for accurate variant discovery in highly divergent regions

Background

Current variant discovery methods often start with the mapping of short reads to a reference genome; yet, their performance deteriorates in genomic regions where the reads are highly divergent from the reference sequence. This is particularly problematic for the human leukocyte antigen (HLA) region on chromosome 6p21.3. This region is associated with over 100 diseases, but variant calling is hindered by the extreme divergence across different haplotypes.

Results

We simulated reads from chromosome 6 exonic regions over a wide range of sequence divergence and coverage depth. We systematically assessed combinations between five mappers and five callers for their performance on simulated data and exome-seq data from NA12878, a well-studied individual in which multiple public call sets have been generated. Among those combinations, the number of known SNPs differed by about 5 % in the non-HLA regions of chromosome 6 but over 20 % in the HLA region. Notably, GSNAP mapping combined with GATK UnifiedGenotyper calling identified about 20 % more known SNPs than most existing methods without a noticeable loss of specificity, with 100 % sensitivity in three highly polymorphic HLA genes examined. Much larger differences were observed among these combinations in INDEL calling from both non-HLA and HLA regions. We obtained similar results with our internal exome-seq data from a cohort of chronic lymphocytic leukemia patients.

Conclusions

We have established a workflow enabling variant detection, with high sensitivity and specificity, over the full spectrum of divergence seen in the human genome. Comparing to public call sets from NA12878 has highlighted the overall superiority of GATK UnifiedGenotyper, followed by GATK HaplotypeCaller and SAMtools, in SNP calling, and of GATK HaplotypeCaller and Platypus in INDEL calling, particularly in regions of high sequence divergence such as the HLA region. GSNAP and Novoalign are the ideal mappers in combination with the above callers. We expect that the proposed workflow should be applicable to variant discovery in other highly divergent regions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3045-z) contains supplementary material, which is available to authorized users.

Sequence capture by hybridization to explore modern and ancient genomic diversity in model and nonmodel organisms

The recent expansion of next-generation sequencing has significantly improved biological research. Nevertheless, deep exploration of genomes or metagenomic samples remains difficult because of the sequencing depth and the associated costs required. Therefore, different partitioning strategies have been developed to sequence informative subsets of studied genomes. Among these strategies, hybridization capture has proven to be an innovative and efficient tool for targeting and enriching specific biomarkers in complex DNA mixtures. It has been successfully applied in numerous areas of biology, such as exome resequencing for the identification of mutations underlying Mendelian or complex diseases and cancers, and its usefulness has been demonstrated in the agronomic field through the linking of genetic variants to agricultural phenotypic traits of interest. Moreover, hybridization capture has provided access to underexplored, but relevant fractions of genomes through its ability to enrich defined targets and their flanking regions. Finally, on the basis of restricted genomic information, this method has also allowed the expansion of knowledge of nonreference species and ancient genomes and provided a better understanding of metagenomic samples. In this review, we present the major advances and discoveries permitted by hybridization capture and highlight the potency of this approach in all areas of biology.

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.

Exome sequencing in seven families and gene-based association studies indicate genetic heterogeneity and suggest possible candidates for fibromuscular dysplasia

BACKGROUND

Fibromuscular dysplasia (FMD) is a nonatherosclerotic vascular disease leading to stenosis, aneurysm and dissection, mainly of renal arteries and carotids. FMD occurs predominantly in women with nearly four out of 1000 prevalence and cause hypertension, renal ischemia or stroke. The pathogenesis of FMD is unknown and a genetic origin is suspected given its demonstrated familial aggregation.

METHOD

We performed whole exome sequencing (WES) in 16 cases (seven families). Coding variants in 3971 genes were prioritized on frequency (minor allele frequency < 0.01) and in silico predicted functionality.

RESULTS

No gene harbours variants that are shared among all affected members of at least three families. Variants from 16 genes of vascular and connective tissue diseases are excluded as causative in these families. Genes with at least four variants in the 16 patients and vascular genes were followed-up using genotypes from 249 unrelated cases and 689 controls. Gene-based association analyses using SKAT-O shows nominal significant association with multifocal FMD (N = 164) for myosin light chain kinase (MYLK, P = 0.01) previously involved in thoracic aortic aneurysm, obscurin (OBSCN), a sarcomeric protein (P = 0.003), dynein cytoplasmic heavy chain 1 (DYNC2H1, P = 0.02) and RNF213 previously associated with Moyamoya disease (P = 0.01).

CONCLUSION

Our study indicates genetic heterogeneity and the unlikely existence of a major gene for FMD and excludes the role of several vascular genes in familial FMD. We also suggest four possible candidate genes for multifocal FMD, though these findings need further genetic and functional confirmation. More powerful WES and association studies [e.g. genome-wide association study (GWAS)] will better decipher the genetic basis of FMD.

Advances in genetics and genomics: use and limitations in achieving malaria elimination goals

Success of the global research agenda towards eradication of malaria will depend on the development of new tools, including drugs, vaccines, insecticides and diagnostics. Genetic and genomic information now available for the malaria parasites, their mosquito vectors and human host, can be harnessed to both develop these tools and monitor their effectiveness. Here we review and provide specific examples of current technological advances and how these genetic and genomic tools have increased our knowledge of host, parasite and vector biology in relation to malaria elimination and in turn enhanced the potential to reach that goal. We then discuss limitations of these tools and future prospects for the successful achievement of global malaria elimination goals.

Identification of IDUA and WNT16 Phosphorylation-Related Non-Synonymous Polymorphisms for Bone Mineral Density in Meta-Analyses of Genome-Wide Association Studies

Protein phosphorylation regulates a wide variety of cellular processes. Thus, we hypothesize that single-nucleotide polymorphisms (SNPs) that may modulate protein phosphorylation could affect osteoporosis risk. Based on a previous conventional genome-wide association (GWA) study, we conducted a three-stage meta-analysis targeting phosphorylation-related SNPs (phosSNPs) for femoral neck (FN)-bone mineral density (BMD), total hip (HIP)-BMD, and lumbar spine (LS)-BMD phenotypes. In stage 1, 9593 phosSNPs were meta-analyzed in 11,140 individuals of various ancestries. Genome-wide significance (GWS) and suggestive significance were defined by α = 5.21 × 10(-6) (0.05/9593) and 1.00 × 10(-4), respectively. In stage 2, nine stage 1-discovered phosSNPs (based on α = 1.00 × 10(-4)) were in silico meta-analyzed in Dutch, Korean, and Australian cohorts. In stage 3, four phosSNPs that replicated in stage 2 (based on α = 5.56 × 10(-3), 0.05/9) were de novo genotyped in two independent cohorts. IDUA rs3755955 and rs6831280, and WNT16 rs2707466 were associated with BMD phenotypes in each respective stage, and in three stages combined, achieving GWS for both FN-BMD (p = 8.36 × 10(-10), p = 5.26 × 10(-10), and p = 3.01 × 10(-10), respectively) and HIP-BMD (p = 3.26 × 10(-6), p = 1.97 × 10(-6), and p = 1.63 × 10(-12), respectively). Although in vitro studies demonstrated no differences in expressions of wild-type and mutant forms of IDUA and WNT16B proteins, in silico analyses predicts that WNT16 rs2707466 directly abolishes a phosphorylation site, which could cause a deleterious effect on WNT16 protein, and that IDUA phosSNPs rs3755955 and rs6831280 could exert indirect effects on nearby phosphorylation sites. Further studies will be required to determine the detailed and specific molecular effects of these BMD-associated non-synonymous variants.

Cross-Comparison of Exome Analysis, Next-Generation Sequencing of Amplicons, and the iPLEX(®) ADME PGx Panel for Pharmacogenomic Profiling

Whole-exome sequencing (WES) has been widely used for analysis of human genetic diseases, but its value for the pharmacogenomic profiling of individuals is not well studied. Initially, we performed an in-depth evaluation of the accuracy of WES variant calling in the pharmacogenes CYP2D6 and CYP2C19 by comparison with MiSeq(®) amplicon sequencing data (n = 36). This analysis revealed that the concordance rate between WES and MiSeq(®) was high, achieving 99.60% for variants that were called without exceeding the truth-sensitivity threshold (99%), defined during variant quality score recalibration (VQSR). Beyond this threshold, the proportion of discordant calls increased markedly. Subsequently, we expanded our findings beyond CYP2D6 and CYP2C19 to include more genes genotyped by the iPLEX(®) ADME PGx Panel in the subset of twelve samples. WES performed well, agreeing with the genotyping panel in approximately 99% of the selected pass-filter variant calls. Overall, our results have demonstrated WES to be a promising approach for pharmacogenomic profiling, with an estimated error rate of lower than 1%. Quality filters, particularly VQSR, are important for reducing the number of false variants. Future studies may benefit from examining the role of WES in the clinical setting for guiding drug therapy.

An integrated approach for analyzing clinical genomic variant data from next-generation sequencing

Next-generation sequencing (NGS) technologies provide the potential for developing high-throughput and low-cost platforms for clinical diagnostics. A limiting factor to clinical applications of genomic NGS is downstream bioinformatics analysis for data interpretation. We have developed an integrated approach for end-to-end clinical NGS data analysis from variant detection to functional profiling. Robust bioinformatics pipelines were implemented for genome alignment, single nucleotide polymorphism (SNP), small insertion/deletion (InDel), and copy number variation (CNV) detection of whole exome sequencing (WES) data from the Illumina platform. Quality-control metrics were analyzed at each step of the pipeline by use of a validated training dataset to ensure data integrity for clinical applications. We annotate the variants with data regarding the disease population and variant impact. Custom algorithms were developed to filter variants based on criteria, such as quality of variant, inheritance pattern, and impact of variant on protein function. The developed clinical variant pipeline links the identified rare variants to Integrated Genome Viewer for visualization in a genomic context and to the Protein Information Resource's iProXpress for rich protein and disease information. With the application of our system of annotations, prioritizations, inheritance filters, and functional profiling and analysis, we have created a unique methodology for downstream variant filtering that empowers clinicians and researchers to interpret more effectively the relevance of genomic alterations within a rare genetic disease.

PBAP: a pipeline for file processing and quality control of pedigree data with dense genetic markers

MOTIVATION

Huge genetic datasets with dense marker panels are now common. With the availability of sequence data and recognition of importance of rare variants, smaller studies based on pedigrees are again also common. Pedigree-based samples often start with a dense marker panel, a subset of which may be used for linkage analysis to reduce computational burden and to limit linkage disequilibrium between single-nucleotide polymorphisms (SNPs). Programs attempting to select markers for linkage panels exist but lack flexibility.

RESULTS

We developed a pedigree-based analysis pipeline (PBAP) suite of programs geared towards SNPs and sequence data. PBAP performs quality control, marker selection and file preparation. PBAP sets up files for MORGAN, which can handle analyses for small and large pedigrees, typically human, and results can be used with other programs and for downstream analyses. We evaluate and illustrate its features with two real datasets.

AVAILABILITY AND IMPLEMENTATION

PBAP scripts may be downloaded from http://faculty.washington.edu/wijsman/software.shtml.

CONTACT

wijsman@uw.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Utility and limitations of exome sequencing as a genetic diagnostic tool for conditions associated with pediatric sudden cardiac arrest/sudden cardiac death

Background

Conditions associated with sudden cardiac arrest/death (SCA/D) in youth often have a genetic etiology. While SCA/D is uncommon, a pro-active family screening approach may identify these inherited structural and electrical abnormalities prior to symptomatic events and allow appropriate surveillance and treatment. This study investigated the diagnostic utility of exome sequencing (ES) by evaluating the capture and coverage of genes related to SCA/D.

Methods

Samples from 102 individuals (13 with known molecular etiologies for SCA/D, 30 individuals without known molecular etiologies for SCA/D and 59 with other conditions) were analyzed following exome capture and sequencing at an average read depth of 100X. Reads were mapped to human genome GRCh37 using Novoalign, and post-processing and analysis was done using Picard and GATK. A total of 103 genes (2,190 exons) related to SCA/D were used as a primary filter. An additional 100 random variants within the targeted genes associated with SCA/D were also selected and evaluated for depth of sequencing and coverage. Although the primary objective was to evaluate the adequacy of depth of sequencing and coverage of targeted SCA/D genes and not for primary diagnosis, all patients who had SCA/D (known or unknown molecular etiologies) were evaluated with the project’s variant analysis pipeline to determine if the molecular etiologies could be successfully identified.

Results

The majority of exons (97.6 %) were captured and fully covered on average at minimum of 20x sequencing depth. The proportion of unique genomic positions reported within poorly covered exons remained small (4 %). Exonic regions with less coverage reflect the need to enrich these areas to improve coverage. Despite limitations in coverage, we identified 100 % of cases with a prior known molecular etiology for SCA/D, and analysis of an additional 30 individuals with SCA/D but no known molecular etiology revealed a diagnostic answer in 5/30 (17 %). We also demonstrated 95 % of 100 randomly selected reported variants within our targeted genes would have been picked up on ES based on our coverage analysis.

Conclusions

ES is a helpful clinical diagnostic tool for SCA/D given its potential to successfully identify a molecular diagnosis, but clinicians should be aware of limitations of available platforms from technical and diagnostic perspectives.

Electronic supplementary material

The online version of this article (doi:10.1186/s40246-015-0038-y) contains supplementary material, which is available to authorized users.

Actionable clinical decisions based on comprehensive genomic evaluation in asymptomatic adults

Whole-exome sequencing (WES) arises as a new approach in diagnosing individuals affected by multigenic and complex phenotypes. Herein, we aim to examine whether WES is useful in screening asymptomatic individuals for actionable interventions, which has not yet been established. Twenty-five healthy adults underwent WES, bioinformatics, and manual curation of their exomes. Six participants (24%) harbored significant, management-changing variants in cancer predisposition genes, American College of Medical Genetics, and genomics reportable cardiac diseases and pharmacogenomic biomarkers that have led to clinical recommendations and interventions. Furthermore, more than 80% of the participants (21) carried 1–3 genetic variants with an associated clinical guideline for an altered drug dosing or administration based on the FDA’s table of pharmacogenomics. These results support WES potential not only to answer specific diagnostic questions presented by the relevant personal and/or family history but also to uncover clinically important genetic findings unrelated to the primary indication for sequencing.

WHATIF: An open-source desktop application for extraction and management of the incidental findings from next-generation sequencing variant data

BACKGROUND

Identification and evaluation of incidental findings in patients following whole exome (WGS) or whole genome sequencing (WGS) is challenging for both practicing physicians and researchers. The American College of Medical Genetics and Genomics (ACMG) recently recommended a list of reportable incidental genetic findings. However, no informatics tools are currently available to support evaluation of incidental findings in next-generation sequencing data.

METHODS

The Wisconsin Hierarchical Analysis Tool for Incidental Findings (WHATIF), was developed as a stand-alone Windows-based desktop executable, to support the interactive analysis of incidental findings in the context of the ACMG recommendations. WHATIF integrates the European Bioinformatics Institute Variant Effect Predictor (VEP) tool for biological interpretation and the National Center for Biotechnology Information ClinVar tool for clinical interpretation.

RESULTS

An open-source desktop program was created to annotate incidental findings and present the results with a user-friendly interface. Further, a meaningful index (WHATIF Index) was devised for each gene to facilitate ranking of the relative importance of the variants and estimate the potential workload associated with further evaluation of the variants. Our WHATIF application is available at: http://tinyurl.com/WHATIF-SOFTWARE CONCLUSIONS: The WHATIF application offers a user-friendly interface and allows users to investigate the extracted variant information efficiently and intuitively while always accessing the up to date information on variants via application programming interfaces (API) connections. WHATIF׳s highly flexible design and straightforward implementation aids users in customizing the source code to meet their own special needs.

DVL1 frameshift mutations clustering in the penultimate exon cause autosomal-dominant Robinow syndrome

Robinow syndrome is a genetically heterogeneous disorder characterized by mesomelic limb shortening, genital hypoplasia, and distinctive facial features and for which both autosomal-recessive and autosomal-dominant inheritance patterns have been described. Causative variants in the non-canonical signaling gene WNT5A underlie a subset of autosomal-dominant Robinow syndrome (DRS) cases, but most individuals with DRS remain without a molecular diagnosis. We performed whole-exome sequencing in four unrelated DRS-affected individuals without coding mutations in WNT5A and found heterozygous DVL1 exon 14 mutations in three of them. Targeted Sanger sequencing in additional subjects with DRS uncovered DVL1 exon 14 mutations in five individuals, including a pair of monozygotic twins. In total, six distinct frameshift mutations were found in eight subjects, and all were heterozygous truncating variants within the penultimate exon of DVL1. In five families in which samples from unaffected parents were available, the variants were demonstrated to represent de novo mutations. All variant alleles are predicted to result in a premature termination codon within the last exon, escape nonsense-mediated decay (NMD), and most likely generate a C-terminally truncated protein with a distinct -1 reading-frame terminus. Study of the transcripts extracted from affected subjects' leukocytes confirmed expression of both wild-type and variant alleles, supporting the hypothesis that mutant mRNA escapes NMD. Genomic variants identified in our study suggest that truncation of the C-terminal domain of DVL1, a protein hypothesized to have a downstream role in the Wnt-5a non-canonical pathway, is a common cause of DRS.

New insights into the performance of human whole-exome capture platforms

Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.

A founder AGL mutation causing glycogen storage disease type IIIa in Inuit identified through whole-exome sequencing: a case series

BACKGROUND

Glycogen storage disease type III is caused by mutations in both alleles of the AGL gene, which leads to reduced activity of glycogen-debranching enzyme. The clinical picture encompasses hypoglycemia, with glycogen accumulation leading to hepatomegaly and muscle involvement (skeletal and cardiac). We sought to identify the genetic cause of this disease within the Inuit community of Nunavik, in whom previous DNA sequencing had not identified such mutations.

METHODS

Five Inuit children with a clinical and biochemical diagnosis of glycogen storage disease type IIIa were recruited to undergo genetic testing: 2 underwent whole-exome sequencing and all 5 underwent Sanger sequencing to confirm the identified mutation. Selected DNA regions near the AGL gene were also sequenced to identify a potential founder effect in the community. In addition, control samples from 4 adults of European descent and 7 family members of the affected children were analyzed for the specific mutation by Sanger sequencing.

RESULTS

We identified a homozygous frame-shift deletion, c.4456delT, in exon 33 of the AGL gene in 2 children by whole-exome sequencing. Confirmation by Sanger sequencing showed the same mutation in all 5 patients, and 5 family members were found to be carriers. With the identification of this mutation in 5 probands, the estimated prevalence of genetically confirmed glycogen storage disease type IIIa in this region is among the highest worldwide (1:2500). Despite identical mutations, we saw variations in clinical features of the disease.

INTERPRETATION

Our detection of a homozygous frameshift mutation in 5 Inuit children determines the cause of glycogen storage disease type IIIa and confirms a founder effect.

Next generation sequencing of acute myeloid leukemia: influencing prognosis

Acute myeloid leukemia (AML) is a clonal disorder of the blood forming cells characterized by accumulation of immature blast cells in the bone marrow and peripheral blood. Being a heterogeneous disease, AML has been the subject of numerous studies that focus on unraveling the clinical, cellular and molecular variations with the aim to better understand and treat the disease. Cytogenetic-risk stratification of AML is well established and commonly used by clinicians in therapeutic management of cases with chromosomal abnormalities. Successive inclusion of novel molecular abnormalities has substantially modified the classification and understanding of AML in the past decade. With the advent of next generation sequencing (NGS) technologies the discovery of novel molecular abnormalities has accelerated. NGS has been successfully used in several studies and has provided an unprecedented overview of molecular aberrations as well as the underlying clonal evolution in AML. The extended spectrum of abnormalities discovered by NGS is currently under extensive validation for their prognostic and therapeutic values. In this review we highlight the recent advances in the understanding of AML in the NGS era.

Exome sequencing of three cases of familial exceptional longevity

Exceptional longevity (EL) is a rare phenotype that can cluster in families, and co-segregation of genetic variation in these families may point to candidate genes that could contribute to extended lifespan. In this study, for the first time, we have sequenced a total of seven exomes from exceptionally long-lived siblings (probands ≥ 103 years and at least one sibling ≥ 97 years) that come from three separate families. We have focused on rare functional variants (RFVs) which have ≤ 1% minor allele frequency according to databases and that are likely to alter gene product function. Based on this, we have identified one candidate longevity gene carrying RFVs in all three families, APOB. Interestingly, APOB is a component of lipoprotein particles together with APOE, and variants in the genes encoding these two proteins have been previously associated with human longevity. Analysis of nonfamilial EL cases showed a trend, without reaching statistical significance, toward enrichment of APOB RFVs. We have also identified candidate longevity genes shared between two families (5–13) or within individual families (66–156 genes). Some of these genes have been previously linked to longevity in model organisms, such as PPARGC1A,NRG1,RAD52, RAD51, NCOR1, and ADCY5 genes. This work provides an initial catalog of genes that could contribute to exceptional familial longevity.

A phylogeny-based sampling strategy and power calculator informs genome-wide associations study design for microbial pathogens

Whole genome sequencing is increasingly used to study phenotypic variation among infectious pathogens and to evaluate their relative transmissibility, virulence, and immunogenicity. To date, relatively little has been published on how and how many pathogen strains should be selected for studies associating phenotype and genotype. There are specific challenges when identifying genetic associations in bacteria which often comprise highly structured populations. Here we consider general methodological questions related to sampling and analysis focusing on clonal to moderately recombining pathogens. We propose that a matched sampling scheme constitutes an efficient study design, and provide a power calculator based on phylogenetic convergence. We demonstrate this approach by applying it to genomic datasets for two microbial pathogens: Mycobacterium tuberculosis and Campylobacter species.

Identification of rare variants in Alzheimer's disease

Much progress has been made in recent years in identifying genes involved in the risk of developing Alzheimer's disease (AD), the most common form of dementia. Yet despite the identification of over 20 disease associated loci, mainly through genome wide association studies (GWAS), a large proportion of the genetic component of the disorder remains unexplained. Recent evidence from the AD field, as with other complex diseases, suggests a large proportion of this "missing heritability" may be due to rare variants of moderate to large effect size, but the methodologies to detect such variants are still in their infancy. The latest studies in the field have been focused on the identification of coding variation associated with AD risk, through whole-exome or whole-genome sequencing. Such variants are expected to have larger effect sizes than GWAS loci, and are easier to functionally characterize, and develop cellular and animal models for. This review explores the issues involved in detecting rare variant associations in the context of AD, highlighting some successful approaches utilized to date.