Human genome sequencing in health and disease

Assessing the Accuracy of Variant Detection in Cost-Effective Gene Panel Testing by Next-Generation Sequencing

There is significant debate within the diagnostics community regarding the accuracy of variant identification by next-generation sequencing and the necessity of confirmatory testing of detected variants. Because the quality threshold to discriminate false positives depends on the workflow, no regulatory standard regarding this matter has yet been published. The goal of this study was to empirically determine the threshold to perform additional Sanger sequencing and to reduce the experimental cost to a practical level. Using 278 model genes, a hybridization capture-based protocol was examined to meet the clinical requirements of low cost, high efficiency, and high-quality data. To reduce excessive false-positive detection, filtering processes were introduced to remove mismapped reads and strand-biased detection to a published best-practices pipeline. With seven samples from the 1000 Genomes Project, 2750 single-nucleotide polymorphisms and 142 insertions/deletions were identified by our designed workflow. Compared with variants registered in the single nucleotide polymorphism database (dbSNP), a zero false-positive threshold value was determined (quality score > 1000). The variants satisfying these criteria accounted for 95.6% of single-nucleotide polymorphisms and 50.7% of insertions/deletions. Except for deletions located within the highly repeated sequences, the workflow achieved 100% sensitivity. The established threshold allowed us to discriminate between convincing variants and those requiring validation, a design that reconciles the competing objectives of cost minimization and quality maximization of clinical gene panel testing.

A theory-informed systematic review of clinicians' genetic testing practices

This systematic literature review investigates factors impacting on clinicians' decisions to offer genetic tests in their practice, and maps them to a theoretical behaviour change framework. Better understanding of these factors will inform the design of effective interventions to integrate genomics tests into clinical care. We conducted a narrative synthesis of empirical research of medical specialists' perspectives on and experiences of offering genetic tests to their patients. This review was based upon the PRISMA statement and guidelines for reviewing qualitative research. Four electronic data sources were searched-MEDLINE, EMBASE, CINAHL, PubMed. Studies were independently assessed by two authors. Content analysis was applied to map the findings of included studies to a framework validated for behaviour and implementation research, the Theoretical Domains Framework (TDF). The TDF describes 14 factors known to influence behaviour and has been applied in diverse clinical settings to understand and/or modify health professional behaviour. Thirty-four studies published in 39 articles met inclusion and quality criteria. Most studies were published after 2011 (54%), Northern American (82%), quantitative in design (68%) and addressed familial cancer genetic tests (53%). Of the 14 TDF factors, 13 were identified. The three most common factors were: Environmental Context and Resources (n = 33), Beliefs about Consequences (n = 26), and Knowledge (n = 23). To support the adoption of genomic tests beyond specialist services, nuanced interventions targeting considerations beyond clinician education are needed. For instance, interventions addressing organisational constraints which may restrict clinicians' ability to offer genomic tests are required alongside those targeting factors intrinsic to the clinician.

Gut microbiota derived metabolites in cardiovascular health and disease

Trillions of microbes inhabit the human gut, not only providing nutrients and energy to the host from the ingested food, but also producing metabolic bioactive signaling molecules to maintain health and elicit disease, such as cardiovascular disease (CVD). CVD is the leading cause of mortality worldwide. In this review, we presented gut microbiota derived metabolites involved in cardiovascular health and disease, including trimethylamine-N-oxide (TMAO), uremic toxins, short chain fatty acids (SCFAs), phytoestrogens, anthocyanins, bile acids and lipopolysaccharide. These gut microbiota derived metabolites play critical roles in maintaining a healthy cardiovascular function, and if dysregulated, potentially causally linked to CVD. A better understanding of the function and dynamics of gut microbiota derived metabolites holds great promise toward mechanistic predicative CVD biomarker discoveries and precise interventions.

Next-generation sequencing approaches for the diagnosis of skeletal muscle disorders

PURPOSE OF REVIEW

The development of next-generation sequencing (NGS) technologies is transforming the practice of medical genetics and revolutionizing the approach to heterogeneous hereditary conditions, including skeletal muscle disorders. Here, we review the different NGS approaches described in the literature so far for the characterization of myopathic patients and the results obtained from the implementation of such approaches in a clinical setting.

RECENT FINDINGS

The overall diagnostic rate of NGS strategies for patients affected by skeletal muscle disorders is higher than the success rate obtained using the traditional gene-by-gene approach. Moreover, many recent articles have been expanding the clinical phenotypes associated with already known disease genes.

SUMMARY

NGS applications will soon be the first-tier test for skeletal muscle disorders. They will improve the diagnosis in myopathic patients, promoting their inclusion into novel therapeutic trials. At the same time, they will improve our knowledge about the molecular mechanisms causing skeletal muscle disorders, favoring the development of novel therapeutic approaches.

Integration of Drosophila and Human Genetics to Understand Notch Signaling Related Diseases

Notch signaling research dates back to more than one hundred years, beginning with the identification of the Notch mutant in the fruit fly Drosophila melanogaster. Since then, research on Notch and related genes in flies has laid the foundation of what we now know as the Notch signaling pathway. In the 1990s, basic biological and biochemical studies of Notch signaling components in mammalian systems, as well as identification of rare mutations in Notch signaling pathway genes in human patients with rare Mendelian diseases or cancer, increased the significance of this pathway in human biology and medicine. In the 21st century, Drosophila and other genetic model organisms continue to play a leading role in understanding basic Notch biology. Furthermore, these model organisms can be used in a translational manner to study underlying mechanisms of Notch-related human diseases and to investigate the function of novel disease associated genes and variants. In this chapter, we first briefly review the major contributions of Drosophila to Notch signaling research, discussing the similarities and differences between the fly and human pathways. Next, we introduce several biological contexts in Drosophila in which Notch signaling has been extensively characterized. Finally, we discuss a number of genetic diseases caused by mutations in genes in the Notch signaling pathway in humans and we expand on how Drosophila can be used to study rare genetic variants associated with these and novel disorders. By combining modern genomics and state-of-the art technologies, Drosophila research is continuing to reveal exciting biology that sheds light onto mechanisms of disease.

Elucidating the major hidden genomic components of the A, C, and AC genomes and their influence on Brassica evolution

Decoding complete genome sequences is prerequisite for comprehensive genomics studies. However, the currently available reference genome sequences of Brassica rapa (A genome), B. oleracea (C) and B. napus (AC) cover 391, 540, and 850 Mbp and represent 80.6, 85.7, and 75.2% of the estimated genome size, respectively, while remained are hidden or unassembled due to highly repetitive nature of these genome components. Here, we performed the first comprehensive genome-wide analysis using low-coverage whole-genome sequences to explore the hidden genome components based on characterization of major repeat families in the B. rapa and B. oleracea genomes. Our analysis revealed 10 major repeats (MRs) including a new family comprising about 18.8, 10.8, and 11.5% of the A, C and AC genomes, respectively. Nevertheless, these 10 MRs represented less than 0.7% of each assembled reference genome. Genomic survey and molecular cytogenetic analyses validates our insilico analysis and also pointed to diversity, differential distribution, and evolutionary dynamics in the three Brassica species. Overall, our work elucidates hidden portions of three Brassica genomes, thus providing a resource for understanding the complete genome structures. Furthermore, we observed that asymmetrical accumulation of the major repeats might be a cause of diversification between the A and C genomes.

The landscape of human mutually exclusive splicing

Mutually exclusive splicing of exons is a mechanism of functional gene and protein diversification with pivotal roles in organismal development and diseases such as Timothy syndrome, cardiomyopathy and cancer in humans. In order to obtain a first genomewide estimate of the extent and biological role of mutually exclusive splicing in humans, we predicted and subsequently validated mutually exclusive exons (MXEs) using 515 publically available RNA‐Seq datasets. Here, we provide evidence for the expression of over 855 MXEs, 42% of which represent novel exons, increasing the annotated human mutually exclusive exome more than fivefold. The data provide strong evidence for the existence of large and multi‐cluster MXEs in higher vertebrates and offer new insights into MXE evolution. More than 82% of the MXE clusters are conserved in mammals, and five clusters have homologous clusters in Drosophila. Finally, MXEs are significantly enriched in pathogenic mutations and their spatio‐temporal expression might predict human disease pathology.

Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes

Neurometabolic disorders are markedly heterogeneous, both clinically and genetically, and are characterized by variable neurological dysfunction accompanied by suggestive neuroimaging or biochemical abnormalities. Despite early specialist input, delays in diagnosis and appropriate treatment initiation are common. Next-generation sequencing approaches still have limitations but are already enabling earlier and more efficient diagnoses in these patients. We designed a gene panel targeting 614 genes causing inborn errors of metabolism and tested its diagnostic efficacy in a paediatric cohort of 30 undiagnosed patients presenting with variable neurometabolic phenotypes. Genetic defects that could, at least partially, explain observed phenotypes were identified in 53% of cases. Where biochemical abnormalities pointing towards a particular gene defect were present, our panel identified diagnoses in 89% of patients. Phenotypes attributable to defects in more than one gene were seen in 13% of cases. The ability of in silico tools, including structure-guided prediction programmes to characterize novel missense variants were also interrogated. Our study expands the genetic, clinical and biochemical phenotypes of well-characterized (POMGNT1, TPP1) and recently identified disorders (PGAP2, ACSF3, SERAC1, AFG3L2, DPYS). Overall, our panel was accurate and efficient, demonstrating good potential for applying similar approaches to clinically and biochemically diverse neurometabolic disease cohorts.

Bayesian state space models for dynamic genetic network construction across multiple tissues

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Analysis and Annotation of Whole-Genome or Whole-Exome Sequencing Derived Variants for Clinical Diagnosis

Over the last 10 years, next-generation sequencing (NGS) has transformed genomic research through substantial advances in technology and reduction in the cost of sequencing, and also in the systems required for analysis of these large volumes of data. This technology is now being used as a standard molecular diagnostic test in some clinical settings. The advances in sequencing have come so rapidly that the major bottleneck in identification of causal variants is no longer the sequencing or analysis (given access to appropriate tools), but rather clinical interpretation. Interpretation of genetic findings in a complex and ever changing clinical setting is scarcely a new challenge, but the task is increasingly complex in clinical genome-wide sequencing given the dramatic increase in dataset size and complexity. This increase requires application of appropriate interpretation tools, as well as development and application of appropriate methodologies and standard procedures. This unit provides an overview of these items. Specific challenges related to implementation of genome-wide sequencing in a clinical setting are discussed. © 2017 by John Wiley & Sons, Inc.

Diversifying Food Systems in the Pursuit of Sustainable Food Production and Healthy Diets

Increasing demand for nutritious, safe, and healthy food because of a growing population, and the pledge to maintain biodiversity and other resources, pose a major challenge to agriculture that is already threatened by a changing climate. Diverse and healthy diets, largely based on plant-derived food, may reduce diet-related illnesses. Investments in plant sciences will be necessary to design diverse cropping systems balancing productivity, sustainability, and nutritional quality. Cultivar diversity and nutritional quality are crucial. We call for better cooperation between food and medical scientists, food sector industries, breeders, and farmers to develop diversified and nutritious cultivars that reduce soil degradation and dependence on external inputs, such as fertilizers and pesticides, and to increase adaptation to climate change and resistance to emerging pests.

Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research

Efforts to identify the genetic underpinnings of rare undiagnosed diseases increasingly involve the use of next-generation sequencing and comparative genomic hybridization methods. These efforts are limited by a lack of knowledge regarding gene function, and an inability to predict the impact of genetic variation on the encoded protein function. Diagnostic challenges posed by undiagnosed diseases have solutions in model organism research, which provides a wealth of detailed biological information. Model organism geneticists are by necessity experts in particular genes, gene families, specific organs, and biological functions. Here, we review the current state of research into undiagnosed diseases, highlighting large efforts in North America and internationally, including the Undiagnosed Diseases Network (UDN) (Supplemental Material, File S1) and UDN International (UDNI), the Centers for Mendelian Genomics (CMG), and the Canadian Rare Diseases Models and Mechanisms Network (RDMM). We discuss how merging human genetics with model organism research guides experimental studies to solve these medical mysteries, gain new insights into disease pathogenesis, and uncover new therapeutic strategies.

An efficient and tunable parameter to improve variant calling for whole genome and exome sequencing data

Next generation sequencing (NGS) has traditionally been performed in various fields including agricultural to clinical and there are so many sequencing platforms available in order to obtain accurate and consistent results. However, these platforms showed amplification bias when facilitating variant calls in personal genomes. Here, we sequenced whole genomes and whole exomes from ten Korean individuals using Illumina and Ion Proton, respectively to find the vulnerability and accuracy of NGS platform in the GC rich/poor area. Overall, a total of 1013 Gb reads from Illumina and ~39.1 Gb reads from Ion Proton were analyzed using BWA-GATK variant calling pipeline. Furthermore, conjunction with the VQSR tool and detailed filtering strategies, we achieved high-quality variants. Finally, each of the ten variants from Illumina only, Ion Proton only, and intersection was selected for Sanger validation. The validation results revealed that Illumina platform showed higher accuracy than Ion Proton. The described filtering methods are advantageous for large population-based whole genome studies designed to identify common and rare variations associated with complex diseases.

Genomic sequencing in clinical practice: applications, challenges, and opportunities

The development of massively parallel sequencing (or next-generation sequencing) has facilitated a rapid implementation of genomic sequencing in clinical medicine. Genomic sequencing (GS) is now an essential tool for evaluating rare disorders, identifying therapeutic targets in neoplasms, and screening for prenatal aneuploidy. Emerging applications, such as GS for preconception carrier screening and predisposition screening in healthy individuals, are being explored in research settings and utilized by members of the public eager to incorporate genomic information into their health management. The rapid pace of adoption has created challenges for all stakeholders in clinical GS, from standardizing variant interpretation approaches in clinical molecular laboratories to ensuring that nongeneticist clinicians are prepared for new types of clinical information. Clinical GS faces a pivotal moment, as the vast potential of new quantities and types of data enable further clinical innovation and complicated implementation questions continue to be resolved.

Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data

Insertion and deletion (INDEL) mutations, the most common type of structural variance, are associated with several human diseases. The detection of INDELs through next-generation sequencing (NGS) is becoming more common due to the decrease in costs, the increase in efficiency, and sensitivity improvements demonstrated by the various sequencing platforms and analytical tools. However, there are still many errors associated with INDEL variant calling, and distinguishing INDELs from errors in NGS remains challenging. To evaluate INDEL calling from whole-exome sequencing (WES) data, we performed Sanger sequencing for all INDELs called from the several calling algorithm. We compared the performance of the four algorithms (i.e. GATK, SAMtools, Dindel, and Freebayes) for INDEL detection from the same sample. We examined the sensitivity and PPV of GATK (90.2 and 89.5%, respectively), SAMtools (75.3 and 94.4%, respectively), Dindel (90.1 and 88.6%, respectively), and Freebayes (80.1 and 94.4%, respectively). GATK had the highest sensitivity. Furthermore, we identified INDELs with high PPV (4 algorithms intersection: 98.7%, 3 algorithms intersection: 97.6%, and GATK and SAMtools intersection INDELs: 97.6%). We presented two key sources of difficulties in accurate INDEL detection: 1) the presence of repeat, and 2) heterozygous INDELs. Herein we could suggest the accessible algorithms that selectively reduce error rates and thereby facilitate INDEL detection. Our study may also serve as a basis for understanding the accuracy and completeness of INDEL detection.

Inflammatory bowel disease caused by primary immunodeficiencies-Clinical presentations, review of literature, and proposal of a rational diagnostic algorithm

Inflammatory bowel diseases (IBD) including Crohn's disease (CD) and ulcerative colitis have a multifactorial pathogenesis with complex interactions between polygenetic predispositions and environmental factors. However, IBD can also be caused by monogenic diseases, such as primary immunodeficiencies (PID). Recently, an increasing number of these altogether rare diseases have been described to present often primarily, or solely, as IBD. Early recognition of these conditions enables adaption of therapies and thus directly benefits the course of IBDs. Here, we discuss the different clinical presentations in IBD and characteristic features of patient's history, clinical findings, and diagnostic results indicative for a causative PID. Possible predictors are early onset of disease, necessity of parenteral nutrition, failure to respond to standard immunosuppressive therapy, parental consanguinity, increased susceptibility for infections, certain histopathologic findings, and blood tests that are atypical for classic IBD. We illustrate this with exemplary case studies of IBD due to NEMO deficiency, chronic granulomatous disease, common variable immunodeficiency, CTLA-4 and LRBA deficiency. Taking these factors into account, we propose a diagnostic pathway to enable early diagnosis of IBD due to PID.

Frequency of Alu insertions within the ACE and PR loci in Northwestern Mexicans

OBJECTIVE

Presently, non-LTR retrotransposons are the most active mobile elements in the human genome. Among these, Alu elements are highly represented in the modern population. Worldwide, distribution of Alu polymorphisms (insertion/deletion; I/D) shows variability between different populations. Two Alu insertion loci, ACE and PR, are significant biomarkers that have served in several genotype-phenotype association studies. In Mexico, studies concerning the frequency of these biomarkers have been conducted mainly in subpopulations from central and southern regions. Here, we screened a population sample of the northwestern region to gain further knowledge regarding the prevalence of Alu polymorphisms within ACE and PR loci.

RESULTS

For ACE locus, the observed genotype frequencies were 26.5, 51.0 and 22.5% for II, ID, and DD, respectively; and allelic frequencies for I and D were 52 and 48%. Whereas respective genotype frequencies for PR locus were 2.7, 26.5 and 70.8%, and the corresponding allele frequencies were 16 and 84%. Furthermore, the insertion frequency within ACE locus was similar between central, western and northwestern subpopulations, and rather higher in southeastern subpopulation (p < 0.05). Although the occurrence of Alu polymorphisms within PR locus has not been widely examined, the insertion frequency was higher in northwestern subpopulation, as compared with western and southeastern subpopulations (p < 0.05). Based on the frequency of Alu insertions found in ACE and PR loci, subpopulations from the northwestern, western and central regions share a common genetic origin, but apparently not with the subpopulation from the southeastern region, in accordance with the notion that assumes the existence of a broad genomic diversity in the Mexican population. In addition, the high prevalence of Alu insertions reveals their potential application as biomarkers with prognostic value for the associated diseases; e.g., as part of the standard protocols for clinical diagnosis.

Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children

OBJECTIVE

To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.

METHODS

Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level.

RESULTS

(1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated.

CONCLUSIONS

Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.

ISOWN: accurate somatic mutation identification in the absence of normal tissue controls

Background

A key step in cancer genome analysis is the identification of somatic mutations in the tumor. This is typically done by comparing the genome of the tumor to the reference genome sequence derived from a normal tissue taken from the same donor. However, there are a variety of common scenarios in which matched normal tissue is not available for comparison.

Results

In this work, we describe an algorithm to distinguish somatic single nucleotide variants (SNVs) in next-generation sequencing data from germline polymorphisms in the absence of normal samples using a machine learning approach. Our algorithm was evaluated using a family of supervised learning classifications across six different cancer types and ~1600 samples, including cell lines, fresh frozen tissues, and formalin-fixed paraffin-embedded tissues; we tested our algorithm with both deep targeted and whole-exome sequencing data. Our algorithm correctly classified between 95 and 98% of somatic mutations with F1-measure ranges from 75.9 to 98.6% depending on the tumor type. We have released the algorithm as a software package called ISOWN (Identification of SOmatic mutations Without matching Normal tissues).

Conclusions

In this work, we describe the development, implementation, and validation of ISOWN, an accurate algorithm for predicting somatic mutations in cancer tissues in the absence of matching normal tissues. ISOWN is available as Open Source under Apache License 2.0 from https://github.com/ikalatskaya/ISOWN.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0446-9) contains supplementary material, which is available to authorized users.

Antibiotics/antimicrobials: systemic and local administration in the therapy of mild to moderately advanced periodontitis

This review gives an update of the current scientific evidence on the efficacy of the adjunctive use of systemic and local antibiotics/antimicrobials in the treatment of periodontitis. In particular, it addresses whether their use can improve the results of nonsurgical mechanical therapy in mild-to-moderate forms of the disease. Large numbers of randomized clinical trials and systematic reviews with meta-analyses have clearly established that adjunctive systemic antibiotics, combined with mechanical debridement, offer clinical improvements additional to those obtained with scaling and root planing alone. These effects are more pronounced in aggressive periodontitis and in initially deep pockets, whereas more limited additional improvements, of 0.3 mm for additional pocket reduction and 0.2 mm for additional clinical attachment gain, have been documented for moderately deep sites (4-6 mm) in patients with chronic periodontitis. The marginal clinical benefit in patients with moderate disease has to be balanced against possible side effects. Notably, it has to be realized that an increasing number of warnings have been articulated against the unrestricted use of antibiotics in treating periodontal diseases because of the emerging global public health issue of bacterial resistance. The effects of the adjunctive local administration of antimicrobials have also been very well documented in several systematic reviews. Overall, in persistent or recurrent localized deep sites, the application of antimicrobials by sustained-delivery devices may offer a benefit of an additional 0.4 mm in pocket depth reduction and 0.3 mm in clinical attachment level gain. In conclusion, the slight additional benefits of adjunctive antimicrobials, which were shown for moderate forms of periodontitis, have to be balanced against their side effects and therefore their prescription should be limited as much as possible.

A decade of progress on the genetic basis of coronary artery disease. Practical insights for the internist

Clinicians are well aware of the importance of a positive family history for coronary artery disease (CAD). Nonetheless, elucidation of the genetic basis of CAD has long proven difficult. The scenario changed in the last decade through the application of modern genomic technologies, like genome-wide association studies (GWAS) and next generation sequencing (NGS). GWAS have discovered over 60 common variants highly associated with CAD. For predictive purposes, such variants have been used to build up Genetic Risk Scores (GRSs), but their incorporation into classical prediction models does not appear substantially outperform the simple addition of family history. To date, the only strong case for the utility of incorporating genetic testing into clinical practice is represented by the diagnosis of Familial Hypercholesterolemia (FH). On the other hand, utilization of genomic techniques has driven formidable advances into the knowledge of CAD pathophysiology, particularly by addressing controversies on the causality of some lipid fractions that had long remained unsolved because of limitations of observational epidemiology. For example, NGS-derived rare variants with strong functional effects on key-genes like ANGPTL4, APOA5, APOC3, LPL, and SCARB1, have proven useful as proxies to demonstrate the causality of triglyceride-rich lipoproteins (TRLs) at variance with HDL-cholesterol concentration, thus contributing to tear down a dogma from classical epidemiology. Moreover, such variants have paved the way for the development of new biologic drugs (i.e. monoclonal antibodies or antisense oligonucleotides) targeting key proteins like PCSK9, Lipoprotein_(a), and apolipoprotein C3. Such drugs are currently under active investigation, with first results being extremely promising.

An evaluation of copy number variation detection tools for cancer using whole exome sequencing data

BACKGROUND

Recently copy number variation (CNV) has gained considerable interest as a type of genomic/genetic variation that plays an important role in disease susceptibility. Advances in sequencing technology have created an opportunity for detecting CNVs more accurately. Recently whole exome sequencing (WES) has become primary strategy for sequencing patient samples and study their genomics aberrations. However, compared to whole genome sequencing, WES introduces more biases and noise that make CNV detection very challenging. Additionally, tumors' complexity makes the detection of cancer specific CNVs even more difficult. Although many CNV detection tools have been developed since introducing NGS data, there are few tools for somatic CNV detection for WES data in cancer.

RESULTS

In this study, we evaluated the performance of the most recent and commonly used CNV detection tools for WES data in cancer to address their limitations and provide guidelines for developing new ones. We focused on the tools that have been designed or have the ability to detect cancer somatic aberrations. We compared the performance of the tools in terms of sensitivity and false discovery rate (FDR) using real data and simulated data. Comparative analysis of the results of the tools showed that there is a low consensus among the tools in calling CNVs. Using real data, tools show moderate sensitivity (~50% - ~80%), fair specificity (~70% - ~94%) and poor FDRs (~27% - ~60%). Also, using simulated data we observed that increasing the coverage more than 10× in exonic regions does not improve the detection power of the tools significantly.

CONCLUSIONS

The limited performance of the current CNV detection tools for WES data in cancer indicates the need for developing more efficient and precise CNV detection methods. Due to the complexity of tumors and high level of noise and biases in WES data, employing advanced novel segmentation, normalization and de-noising techniques that are designed specifically for cancer data is necessary. Also, CNV detection development suffers from the lack of a gold standard for performance evaluation. Finally, developing tools with user-friendly user interfaces and visualization features can enhance CNV studies for a broader range of users.

Targeted Disruption of V600E-Mutant BRAF Gene by CRISPR-Cpf1

BRAF-V600E (1799T > A) is one of the most frequently reported driver mutations in multiple types of cancers, and patients with such mutations could benefit from selectively inactivating the mutant allele. Near this mutation site, there are two TTTN and one NGG protospacer-adjacent motifs (PAMs) for Cpf1 and Cas9 CRISPR nucleases, respectively. The 1799T > A substitution also leads to the occurrence of a novel NGNG PAM for the EQR variant of Cas9. We examined the editing efficacy and selectivity of Cpf1, Cas9, and EQR variant to this mutation site. Only Cpf1 demonstrated robust activity to induce specific disruption of only mutant BRAF, not wild-type sequence. Cas9 recognized and cut both normal and mutant alleles, and no obvious gene editing events were observed using EQR variant. Our results support the potential applicability of Cpf1 in precision medicine through highly specific inactivation of many other gain-of-function mutations.

Lessons learned from additional research analyses of unsolved clinical exome cases

BACKGROUND

Given the rarity of most single-gene Mendelian disorders, concerted efforts of data exchange between clinical and scientific communities are critical to optimize molecular diagnosis and novel disease gene discovery.

METHODS

We designed and implemented protocols for the study of cases for which a plausible molecular diagnosis was not achieved in a clinical genomics diagnostic laboratory (i.e. unsolved clinical exomes). Such cases were recruited to a research laboratory for further analyses, in order to potentially: (1) accelerate novel disease gene discovery; (2) increase the molecular diagnostic yield of whole exome sequencing (WES); and (3) gain insight into the genetic mechanisms of disease. Pilot project data included 74 families, consisting mostly of parent-offspring trios. Analyses performed on a research basis employed both WES from additional family members and complementary bioinformatics approaches and protocols.

RESULTS

Analysis of all possible modes of Mendelian inheritance, focusing on both single nucleotide variants (SNV) and copy number variant (CNV) alleles, yielded a likely contributory variant in 36% (27/74) of cases. If one includes candidate genes with variants identified within a single family, a potential contributory variant was identified in a total of ~51% (38/74) of cases enrolled in this pilot study. The molecular diagnosis was achieved in 30/63 trios (47.6%). Besides this, the analysis workflow yielded evidence for pathogenic variants in disease-associated genes in 4/6 singleton cases (66.6%), 1/1 multiplex family involving three affected siblings, and 3/4 (75%) quartet families. Both the analytical pipeline and the collaborative efforts between the diagnostic and research laboratories provided insights that allowed recent disease gene discoveries (PURA, TANGO2, EMC1, GNB5, ATAD3A, and MIPEP) and increased the number of novel genes, defined in this study as genes identified in more than one family (DHX30 and EBF3).

CONCLUSION

An efficient genomics pipeline in which clinical sequencing in a diagnostic laboratory is followed by the detailed reanalysis of unsolved cases in a research environment, supplemented with WES data from additional family members, and subject to adjuvant bioinformatics analyses including relaxed variant filtering parameters in informatics pipelines, can enhance the molecular diagnostic yield and provide mechanistic insights into Mendelian disorders. Implementing these approaches requires collaborative clinical molecular diagnostic and research efforts.

Diversity and regulatory impact of copy number variation in the primate Macaca fascicularis

BACKGROUND

Copy number variations (CNVs) are a significant source of genetic diversity and commonly found in mammalian genomes. We have generated a genome-wide CNV map for Cynomolgus monkeys (Macaca fascicularis). This crab-eating macaque is the closest animal model to humans that is used in biomedical research.

RESULTS

We show that Cynomolgus monkey CNVs are in general much smaller in size than gene loci and are specific to the population of origin. Genome-wide expression data from five vitally important organs demonstrates that CNVs in close proximity to transcription start sites associate strongly with expression changes. Among these eQTL genes we find an overrepresentation of genes involved in metabolism, receptor activity, and transcription.

CONCLUSION

These results provide evidence that CNVs shape tissue transcriptomes in monkey populations, potentially offering an adaptive advantage. We suggest that this genetic diversity should be taken into account when using Cynomolgus macaques as models.

A Recurrent De Novo Variant in NACC1 Causes a Syndrome Characterized by Infantile Epilepsy, Cataracts, and Profound Developmental Delay

Whole-exome sequencing (WES) has increasingly enabled new pathogenic gene variant identification for undiagnosed neurodevelopmental disorders and provided insights into both gene function and disease biology. Here, we describe seven children with a neurodevelopmental disorder characterized by microcephaly, profound developmental delays and/or intellectual disability, cataracts, severe epilepsy including infantile spasms, irritability, failure to thrive, and stereotypic hand movements. Brain imaging in these individuals reveals delay in myelination and cerebral atrophy. We observe an identical recurrent de novo heterozygous c.892C>T (p.Arg298Trp) variant in the nucleus accumbens associated 1 (NACC1) gene in seven affected individuals. One of the seven individuals is mosaic for this variant. NACC1 encodes a transcriptional repressor implicated in gene expression and has not previously been associated with germline disorders. The probability of finding the same missense NACC1 variant by chance in 7 out of 17,228 individuals who underwent WES for diagnoses of neurodevelopmental phenotypes is extremely small and achieves genome-wide significance (p = 1.25 × 10-14). Selective constraint against missense variants in NACC1 makes this excess of an identical missense variant in all seven individuals more remarkable. Our findings are consistent with a germline recurrent mutational hotspot associated with an allele-specific neurodevelopmental phenotype in NACC1.

Psychological and behavioural impact of returning personal results from whole-genome sequencing: the HealthSeq project

Providing ostensibly healthy individuals with personal results from whole-genome sequencing could lead to improved health and well-being via enhanced disease risk prediction, prevention, and diagnosis, but also poses practical and ethical challenges. Understanding how individuals react psychologically and behaviourally will be key in assessing the potential utility of personal whole-genome sequencing. We conducted an exploratory longitudinal cohort study in which quantitative surveys and in-depth qualitative interviews were conducted before and after personal results were returned to individuals who underwent whole-genome sequencing. The participants were offered a range of interpreted results, including Alzheimer's disease, type 2 diabetes, pharmacogenomics, rare disease-associated variants, and ancestry. They were also offered their raw data. Of the 35 participants at baseline, 29 (82.9%) completed the 6-month follow-up. In the quantitative surveys, test-related distress was low, although it was higher at 1-week than 6-month follow-up (Z=2.68, P=0.007). In the 6-month qualitative interviews, most participants felt happy or relieved about their results. A few were concerned, particularly about rare disease-associated variants and Alzheimer's disease results. Two of the 29 participants had sought clinical follow-up as a direct or indirect consequence of rare disease-associated variants results. Several had mentioned their results to their doctors. Some participants felt having their raw data might be medically useful to them in the future. The majority reported positive reactions to having their genomes sequenced, but there were notable exceptions to this. The impact and value of returning personal results from whole-genome sequencing when implemented on a larger scale remains to be seen.

Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing efficiency against treatment.

Synthetic combinations of missense polymorphic genetic changes underlying Down syndrome susceptibility

Single nucleotide polymorphisms (SNPs) are important biomolecular markers in health and disease. Down syndrome, or Trisomy 21, is the most frequently occurring chromosomal abnormality in live-born children. Here, we highlight associations between SNPs in several important enzymes involved in the one-carbon folate metabolic pathway and the elevated maternal risk of having a child with Down syndrome. Our survey highlights that the combination of SNPs may be a more reliable predictor of the Down syndrome phenotype than single SNPs alone. We also describe recent links between SNPs in p53 and its related pathway proteins and Down syndrome, as well as highlight several proteins that help to associate apoptosis and p53 signaling with the Down syndrome phenotype. In addition to a comprehensive review of the literature, we also demonstrate that several SNPs reside within the same regions as these Down syndrome-linked SNPs, and propose that these closely located nucleotide changes may provide new candidates for future exploration.

Whole-exome sequencing in the molecular diagnosis of individuals with congenital anomalies of the kidney and urinary tract and identification of a new causative gene

Purpose

To investigate the utility of whole-exome sequencing (WES) to define a molecular diagnosis in patients clinically diagnosed with congenital anomalies of kidney and urinary tract (CAKUT).

Methods

WES was performed in 62 families with CAKUT. WES data were analyzed for Single Nucleotide Variants (SNVs) in 35 known CAKUT genes, putatively deleterious sequence changes in new candidate genes, and potentially disease-associated copy-number variants (CNVs).

Results

In approximately 5% of families, pathogenic SNVs were identified in PAX2, HNF1B, and EYA1. Observed phenotypes in these families expand the current understanding about the role of these genes in CAKUT. Four pathogenic CNVs were also identified using two CNV detection tools. In addition, we found one deleterious de novo SNV in FOXP1 among the 62 families with CAKUT. Database of clinical BMGL laboratory was queried and seven additional unrelated individuals with novel de novo SNVs in FOXP1 were identified. Six of these 8 individuals with FOXP1 SNVs, have syndromic urinary tract defects, implicating this gene in urinary tract development.

Conclusion

We conclude that WES can be used to identify the molecular etiology (SNVs, CNVs) in a subset of individuals with CAKUT. WES can also help identify novel CAKUT genes.

The New Role of Biomedical Informatics in the Age of Digital Medicine

OBJECTIVES

To reflect on the recent rise of Digital Medicine, as well as to analyse main research opportunities in this area. Through the use of several examples, this article aims to highlight the new role that Biomedical Informatics (BMI) can play to facilitate progress in research fields such as participatory and precision medicine. This paper also examines the potential impact and associated risks for BMI due to the development of digital medicine and other recent trends. Lastly, possible strategies to place BMI in a better position to face these challenges are suggested.

METHODS

The core content of this article is based on a recent invited keynote lecture delivered by one of the authors (Martin-Sanchez) at the Medical Informatics Europe conference (MIE 2015) held in Madrid in May 2015. Both authors (Lopez-Campos and Martin-Sanchez) have collaborated during the last four years in projects such as the ones described in section 3 and have also worked in reviewing relevant articles and initiatives to prepare this talk.

RESULTS AND CONCLUSIONS

Challenges for BMI posed by the rise of technologically driven fields such as Digital Medicine are explored. New opportunities for BMI, in the context of two main avenues for biomedical and clinical research (participatory and precision medicine) are also emphasised. Several examples of current research illustrate that BMI plays a key role in the new area of Digital Medicine. Embracing these opportunities will allow academic groups in BMI to maintain their leadership, identify new research funding opportunities and design new educational programs to train the next generation of BMI scientists.

Clinical detection of deletion structural variants in whole-genome sequences

Optimal management of acutely ill infants with monogenetic diseases requires rapid identification of causative haplotypes. Whole-genome sequencing (WGS) has been shown to identify pathogenic nucleotide variants in such infants. Deletion structural variants (DSVs, >50 nt) are implicated in many genetic diseases, and tools have been designed to identify DSVs using short-read WGS. Optimisation and integration of these tools into a WGS pipeline could improve diagnostic sensitivity and specificity of WGS. In addition, it may improve turnaround time when compared with current CNV assays, enhancing utility in acute settings. Here we describe DSV detection methods for use in WGS for rapid diagnosis in acutely ill infants: SKALD (Screening Konsensus and Annotation of Large Deletions) combines calls from two tools (Breakdancer and GenomeStrip) with calibrated filters and clinical interpretation rules. In four WGS runs, the average analytic precision (positive predictive value) of SKALD was 78%, and recall (sensitivity) was 27%, when compared with validated reference DSV calls. When retrospectively applied to a cohort of 36 families with acutely ill infants SKALD identified causative DSVs in two. The first was heterozygous deletion of exons 1–3 of MMP21 in trans with a heterozygous frame-shift deletion in two siblings with transposition of the great arteries and heterotaxy. In a newborn female with dysmorphic features, ventricular septal defect and persistent pulmonary hypertension, SKALD identified the breakpoints of a heterozygous, de novo 1p36.32p36.13 deletion. In summary, consensus DSV calling, implemented in an 8-h computational pipeline with parameterised filtering, has the potential to increase the diagnostic yield of WGS in acutely ill neonates and discover novel disease genes.

PiggyBac transposon-based polyadenylation-signal trap for genome-wide mutagenesis in mice

We designed a new type of polyadenylation-signal (PAS) trap vector system in living mice, the piggyBac (PB) (PAS-trapping (EGFP)) gene trapping vector, which takes advantage of the efficient transposition ability of PB and efficient gene trap and insertional mutagenesis of PAS-trapping. The reporter gene of PB(PAS-trapping (EGFP)) is an EGFP gene with its own promoter, but lacking a poly(A) signal. Transgenic mouse lines carrying PB(PAS-trapping (EGFP)) and protamine 1 (Prm1) promoter-driven PB transposase transgenes (Prm1-PBase) were generated by microinjection. Male mice doubly positive for PB(PAS-trapping (EGFP)) and Prm1-PBase were crossed with WT females, generating offspring with various insertion mutations. We found that 44.8% (26/58) of pups were transposon-positive progenies. New transposon integrations comprised 26.9% (7/26) of the transposon-positive progenies. We found that 100% (5/5) of the EGFP fluorescence-positive mice had new trap insertions mediated by a PB transposon in transcriptional units. The direction of the EGFP gene in the vector was consistent with the direction of the endogenous gene reading frame. Furthermore, mice that were EGFP-PCR positive, but EGFP fluorescent negative, did not show successful gene trapping. Thus, the novel PB(PAS-trapping (EGFP)) system is an efficient genome-wide gene-trap mutagenesis in mice.

The Ensembl Variant Effect Predictor

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

The Ensembl Variant Effect Predictor

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

Identification of novel SNPs in differentially expressed genes and its association with horn cancer of Bos indicus bullocks by next-generation sequencing

The use of polymorphic markers like SNPs promises to provide comprehensive tool for analysing genome and identifying genomic regions that contribute to cancer phenotype. Horn cancer is the most common cancer among Bos indicus animals. Increased expression of some genes due to polymorphisms increases risk of HC incidence. We successfully amplified 91 SNPs located in 69 genes in 52 samples, each of HC and HN. Equimolar concentration of amplicons from 69 PCR products of each sample was pooled and subjected to sequencing using Ion Torrent PGM. Data obtained were analysed using DNASTAR software package and case control analysis using SAS software. We found SNP present in BPIFA1 gene of B. indicus shows association with event of HC which reflects its potential to be a genetic marker. Bioinformatic analysis to detect structural and functional impact nsSNP of BPIFA1 added another layer of confirmation to our result. We successfully identified SNP associated with HC as well as demonstrated efficient approach for limited number of SNP discovery and validation in targeted genomics regions in large number of samples combining PCR amplification and Ion Torrent PGM sequencing which suits small-scale laboratories with limited budget.

Clinical genomics: from a truly personal genome viewpoint

The path to Clinical Genomics is punctuated by our understanding of what types of DNA structural and sequence variation contribute to disease, the many technical challenges to detect such variation genome-wide, and the initial struggles to interpret personal genome variation in the context of disease. This review describes one perspective of the development of clinical genomics; whereas the experimental challenges, and hurdles to overcoming them, might be deemed readily apparent, the non-technical issues for clinical implementation may be less obvious. Some of these latter challenges, including: (1) informed consent, (2) privacy, (3) what constitutes potentially pathogenic variation contributing to disease, (4) disease penetrance in populations, and (5) the genetic architecture of disease, and the struggles sometimes faced for solutions, are highlighted using illustrative examples.

Targeted Sequencing and Meta-Analysis of Preterm Birth

Understanding the genetic contribution(s) to the risk of preterm birth may lead to the development of interventions for treatment, prediction and prevention. Twin studies suggest heritability of preterm birth is 36-40%. Large epidemiological analyses support a primary maternal origin for recurrence of preterm birth, with little effect of paternal or fetal genetic factors. We exploited an "extreme phenotype" of preterm birth to leverage the likelihood of genetic discovery. We compared variants identified by targeted sequencing of women with 2-3 generations of preterm birth with term controls without history of preterm birth. We used a meta-genomic, bi-clustering algorithm to identify gene sets coordinately associated with preterm birth. We identified 33 genes including 217 variants from 5 modules that were significantly different between cases and controls. The most frequently identified and connected genes in the exome library were IGF1, ATM and IQGAP2. Likewise, SOS1, RAF1 and AKT3 were most frequent in the haplotype library. Additionally, SERPINB8, AZU1 and WASF3 showed significant differences in abundance of variants in the univariate comparison of cases and controls. The biological processes impacted by these gene sets included: cell motility, migration and locomotion; response to glucocorticoid stimulus; signal transduction; metabolic regulation and control of apoptosis.

Whole exome sequencing reveals de novo pathogenic variants in KAT6A as a cause of a neurodevelopmental disorder

Neurodevelopmental disorders (NDD) are common, with 1-3% of general population being affected, but the etiology is unknown in most individuals. Clinical whole-exome sequencing (WES) has proven to be a powerful tool for the identification of pathogenic variants leading to Mendelian disorders, among which NDD represent a significant percentage. Performing WES with a trio-approach has proven to be extremely effective in identifying de novo pathogenic variants as a common cause of NDD. Here we report six unrelated individuals with a common phenotype consisting of NDD with severe speech delay, hypotonia, and facial dysmorphism. These patients underwent WES with a trio approach and de novo heterozygous predicted pathogenic novel variants in the KAT6A gene were identified. The KAT6A gene encodes a histone acetyltransfrease protein and it has long been known for its structural involvement in acute myeloid leukemia; however, it has not previously been associated with any congenital disorder. In animal models the KAT6A ortholog is involved in transcriptional regulation during development. Given the similar findings in animal models and our patient's phenotypes, we hypothesize that KAT6A could play a role in development of the brain, face, and heart in humans. © 2016 Wiley Periodicals, Inc.

Medical implications of technical accuracy in genome sequencing

Background

As whole exome sequencing (WES) and whole genome sequencing (WGS) transition from research tools to clinical diagnostic tests, it is increasingly critical for sequencing methods and analysis pipelines to be technically accurate. The Genome in a Bottle Consortium has recently published a set of benchmark SNV, indel, and homozygous reference genotypes for the pilot whole genome NIST Reference Material based on the NA12878 genome.

Methods

We examine the relationship between human genome complexity and genes/variants reported to be associated with human disease. Specifically, we map regions of medical relevance to benchmark regions of high or low confidence. We use benchmark data to assess the sensitivity and positive predictive value of two representative sequencing pipelines for specific classes of variation.

Results

We observe that the accuracy of a variant call depends on the genomic region, variant type, and read depth, and varies by analytical pipeline. We find that most false negative WGS calls result from filtering while most false negative WES variants relate to poor coverage. We find that only 74.6 % of the exonic bases in ClinVar and OMIM genes and 82.1 % of the exonic bases in ACMG-reportable genes are found in high-confidence regions. Only 990 genes in the genome are found entirely within high-confidence regions while 593 of 3,300 ClinVar/OMIM genes have less than 50 % of their total exonic base pairs in high-confidence regions. We find greater than 77 % of the pathogenic or likely pathogenic SNVs currently in ClinVar fall within high-confidence regions. We identify sites that are prone to sequencing errors, including thousands present in publicly available variant databases. Finally, we examine the clinical impact of mandatory reporting of secondary findings, highlighting a false positive variant found in BRCA2.

Conclusions

Together, these data illustrate the importance of appropriate use and continued improvement of technical benchmarks to ensure accurate and judicious interpretation of next-generation DNA sequencing results in the clinical setting.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0269-0) contains supplementary material, which is available to authorized users.

High-Throughput DNA Sequencing Analysis of Antibody Repertoires

New high-throughput DNA sequencing (HTS) technologies developed in the past decade have begun to be applied to the study of the complex gene rearrangements that encode human antibodies. This article first reviews the genetic features of Ig loci and the HTS technologies that have been applied to human repertoire studies, then discusses key choices for experimental design and data analysis in these experiments and the insights gained in immunological and infectious disease studies with the use of these approaches.

Erosion of Conserved Binding Sites in Personal Genomes Points to Medical Histories

Although many human diseases have a genetic component involving many loci, the majority of studies are statistically underpowered to isolate the many contributing variants, raising the question of the existence of alternate processes to identify disease mutations. To address this question, we collect ancestral transcription factor binding sites disrupted by an individual's variants and then look for their most significant congregation next to a group of functionally related genes. Strikingly, when the method is applied to five different full human genomes, the top enriched function for each is invariably reflective of their very different medical histories. For example, our method implicates "abnormal cardiac output" for a patient with a longstanding family history of heart disease, "decreased circulating sodium level" for an individual with hypertension, and other biologically appealing links for medical histories spanning narcolepsy to axonal neuropathy. Our results suggest that erosion of gene regulation by mutation load significantly contributes to observed heritable phenotypes that manifest in the medical history. The test we developed exposes a hitherto hidden layer of personal variants that promise to shed new light on human disease penetrance, expressivity and the sensitivity with which we can detect them.

Ethical Considerations for the Return of Incidental Findings in Ophthalmic Genomic Research

Whole genome and whole exome sequencing technologies are being increasingly used in research. However, they have the potential to identify incidental findings (IF), findings not related to the indication of the test, raising questions regarding researchers' responsibilities toward the return of this information to participants. In this study we discuss the ethical considerations related to the return of IF to research participants, emphasizing that the type of the study matters and describing the current practice standards. There are currently no legal obligations for researchers to return IF to participants, but some viewpoints consider that researchers might have an ethical one to return IF of clinical validity and clinical utility and that are actionable. The reality is that most IF are complex to interpret, especially since they were not the indication of the test. The clinical utility often depends on the participants' preferences, which can be challenging to conciliate and relies on participants' understanding. In summary, in the context of a lack of clear guidance, researchers need to have a clear plan for the disclosure or nondisclosure of IF from genomic research, balancing their research goals and resources with the participants' rights and their duty not to harm.

POGZ truncating alleles cause syndromic intellectual disability

BACKGROUND

Large-scale cohort-based whole exome sequencing of individuals with neurodevelopmental disorders (NDDs) has identified numerous novel candidate disease genes; however, detailed phenotypic information is often lacking in such studies. De novo mutations in pogo transposable element with zinc finger domain (POGZ) have been identified in six independent and diverse cohorts of individuals with NDDs ranging from autism spectrum disorder to developmental delay.

METHODS

Whole exome sequencing was performed on five unrelated individuals. Sanger sequencing was used to validate variants and segregate mutations with the phenotype in available family members.

RESULTS

We identified heterozygous truncating mutations in POGZ in five unrelated individuals, which were confirmed to be de novo or not present in available parental samples. Careful review of the phenotypes revealed shared features that included developmental delay, intellectual disability, hypotonia, behavioral abnormalities, and similar facial characteristics. Variable features included short stature, microcephaly, strabismus and hearing loss.

CONCLUSIONS

While POGZ has been associated with neurodevelopmental disorders in large cohort studies, our data suggest that loss of function variants in POGZ lead to an identifiable syndrome of NDD with specific phenotypic traits. This study exemplifies the era of human reverse clinical genomics ushered in by large disease-directed cohort studies; first defining a new syndrome molecularly and, only subsequently, phenotypically.