Genes, mutations, and human inherited disease at the dawn of the age of personalized genomics

A review of genetic variant databases and machine learning tools for predicting the pathogenicity of breast cancer

Studies continue to uncover contributing risk factors for breast cancer (BC) development including genetic variants. Advances in machine learning and big data generated from genetic sequencing can now be used for predicting BC pathogenicity. However, it is unclear which tool developed for pathogenicity prediction is most suited for predicting the impact and pathogenicity of variant effects. A significant challenge is to determine the most suitable data source for each tool since different tools can yield different prediction results with different data inputs. To this end, this work reviews genetic variant databases and tools used specifically for the prediction of BC pathogenicity. We provide a description of existing genetic variants databases and, where appropriate, the diseases for which they have been established. Through example, we illustrate how they can be used for prediction of BC pathogenicity and discuss their associated advantages and disadvantages. We conclude that the tools that are specialized by training on multiple diverse datasets from different databases for the same disease have enhanced accuracy and specificity and are thereby more helpful to the clinicians in predicting and diagnosing BC as early as possible.

Why SNP rs3755955 is associated with human bone mineral density? A molecular and cellular study in bone cells

SNP rs3755955 (major/minor allele: G/A) located in Iduronidase-Alpha-L- (IDUA) gene was reported to be significant for human bone mineral density (BMD). This follow-up study was to uncover the underlying association mechanism through molecular and cellular functional assays relevant to bone. We tested the effects of single nucleotide polymorphisms (SNP) rs3755955 (defined allele G as wild-type and allele A as variant-type) on osteoblastic and osteoclastic functions, as well as protein phosphorylation in stably transfected human fetal osteoblast (hFOB) cell and mononuclear-macrophage (RAW264.7) cell. In hFOB cells, transfection with variant-type IDUA significantly decreased osteoblastic gene expression (OPN, COL1A1 and RANKL) (p < 0.01), impeded cell proliferation (p < 0.05), stimulated cell apoptosis (p < 0.001) and decreased ALP enzyme activity, as compared with that of wild-type IDUA transfection. In RAW264.7 cells, transfection with variant-type IDUA significantly inhibited cell apoptosis (p < 0.01), promoted osteoclastic precursor cell migration (p < 0.0001), growth (p < 0.01), osteoclastic gene expression (TRAP, RANK, Inte-αv and Cath-K) (p < 0.05) and TRAP enzyme activity (p < 0.001), as compared with that of wild-type IDUA transfection. In both hFOB and RAW264.7 cells, the total protein and IDUA protein-specific phosphorylation levels were significantly reduced by variant IDUA transfection, as compared with that of wild-type IDUA transfection (p < 0.05). Variant allele A of phosSNP rs3755955 in IDUA gene regulates protein phosphorylation, inhibits osteoblast function and promotes osteoclastic activity. The SNP rs3755955 could alter IDUA protein phosphorylation, significantly regulates human osteoblastic and osteoclastic gene expression, and influences the growth, differentiation and activity of osteoblast and osteoclast, hence to affect BMD.

Biologia Futura: the importance of 3D organoids-a new approach for research on neurological and rare diseases

3D cell cultures and organoid approach are increasingly being used for basic research and drug discovery of several diseases. Recent advances in these technologies, enabling research on tissue-like structures created in vitro is very important for the value of the data produced. Application of 3D cultures will not only contribute to advancing basic research, but also help to reduce animal usage in biomedical science. The 3D organoid approach is important for research on diseases where patient tissue is difficult to obtain. Therefore, this review aims to show recent advances in the 3D organoid technology in disease modeling and potential usage in translational and personalized medicine of diseases with limited patient material such as neurological diseases and rare diseases.

Common polymorphic OTC variants can act as genetic modifiers of enzymatic activity

Understanding the role of common polymorphisms in modulating the clinical phenotype when they co‐occur with a disease‐causing lesion is of critical importance in medical genetics. We explored the impact of apparently neutral common polymorphisms, using the gene encoding the urea cycle enzyme, ornithine transcarbamylase (OTC), as a model system. Distinct combinations of genetic backgrounds embracing two missense polymorphisms were created in cis with the pathogenic p.Arg40His replacement. In vitro enzymatic assays revealed that the polymorphic variants were able to modulate OTC activity both in the presence or absence of the pathogenic lesion. First, we found that the combination of the minor alleles of polymorphisms p.Lys46Arg and p.Gln270Arg significantly enhanced enzymatic activity in the wild‐type protein. Second, enzymatic assays revealed that the minor allele of the p.Gln270Arg polymorphism was capable of ameliorating OTC activity when combined in cis with the pathogenic p.Arg40His replacement. Structural analysis predicted that the minor allele of the p.Gln270Arg polymorphism would serve to stabilize the OTC wild‐type protein, thereby corroborating the results of the experimental assays. Our findings demonstrate the potential importance of cis‐interactions between common polymorphic variants and pathogenic missense mutations and illustrate how standing genetic variation can modulate protein function.

Leveraging proteomics in orphan disease research: pitfalls and potential

Introduction: The term 'orphan diseases' includes conditions meeting prevalence-based or commercial viability criteria: they affect a small number of individuals and are considered an unviable market for drug development. Proteomics is an important technology to study them, providing information on mechanisms and evolution, biomarkers, and effects of therapeutic interventions.Areas covered: Herein, we review how proteomics and bioinformatic tools could be applied to the study of rare diseases and discuss pitfalls and potential.Expert opinion: Research in the field of rare diseases has to face many challenges, and implementation plans should foresee highly specialized collaborative consortia to create multidisciplinary frameworks for data sharing, advancing research, supporting clinical studies, and accelerating drug development. The integration of different technologies will allow better knowledge of disease pathophysiology, and the inclusion of proteomics and other omics technologies in this context will be pivotal to this aim.Several aspects of rare diseases, often perceived as limiting factors, might actually be advantages for a precision medicine approach: the limited number of patients, the collaboration with patient societies, and the availability of curated clinical registries could allow the development of homogeneous clinical databases and ultimately a better control over the data to be analyzed.

The Impact of Next-Generation Sequencing on the Diagnosis, Treatment, and Prevention of Hereditary Neuromuscular Disorders

The impact of high-throughput sequencing in genetic neuromuscular disorders cannot be overstated. The ability to rapidly and affordably sequence multiple genes simultaneously has enabled a second golden age of Mendelian disease gene discovery, with flow-on impacts for rapid genetic diagnosis, evidence-based treatment, tailored therapy development, carrier-screening, and prevention of disease recurrence in families. However, there are likely many more neuromuscular disease genes and mechanisms to be discovered. Many patients and families remain without a molecular diagnosis following targeted panel sequencing, clinical exome sequencing, or even genome sequencing. Here we review how massively parallel, or next-generation, sequencing has changed the field of genetic neuromuscular disorders, and anticipate future benefits of recent technological innovations such as RNA-seq implementation and detection of tandem repeat expansions from short-read sequencing.

The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting

The Human Gene Mutation Database (HGMD^®) constitutes a comprehensive collection of published germline mutations in nuclear genes that are thought to underlie, or are closely associated with human inherited disease. At the time of writing (June 2020), the database contains in excess of 289,000 different gene lesions identified in over 11,100 genes manually curated from 72,987 articles published in over 3100 peer-reviewed journals. There are primarily two main groups of users who utilise HGMD on a regular basis; research scientists and clinical diagnosticians. This review aims to highlight how to make the most out of HGMD data in each setting.

Family-based whole-genome sequencing identifies compound heterozygous protein-coding and noncoding mutations in tetralogy of Fallot

Tetralogy of Fallot (TOF) is one of most serious cyanotic congenital heart disease (CHD) and the prevalence is estimated to be 1 in 3000 live births worldwide. Though multiple studies have found genetic variants as risk factors for TOF, they could only explain a small fraction of the pathogenesis. Here, we performed whole genome sequencing (WGS) for 6 individuals derived from 2 families to evaluate pathogenic mutations located in both coding and noncoding regions. We characterized the annotated deleterious coding mutations and impaired noncoding mutations in regulatory elements by various data analysis. Additionally, functional assays were conducted to validate function regulatory elements and noncoding mutations. Interestingly, a compound heterozygous pattern with pathogenic coding and noncoding mutations was identified in probands. In proband 1, biallelic mutations (g.139409115A > T, encoding p.Asn685Ile; g.139444949C > A) in NOTCH1 exon and its regulatory element were detected. In vitro experiments revealed that the regulatory element acted as a silencer and the noncoding mutation decreased the expression of NOTCH1. In proband 2, we also found compound heterozygous mutations (g. 216235029C > T, encoding p.Val2281Met; g. 216525154A > C) which potentially regulated the function of FN1 gene. In summary, our study firstly reported an instance of newly identified noncoding mutation in regulatory element within the compound heterozygous pattern in TOF. The results provided a deeper understanding of TOF genetic architectures.

The clinical and genetic characteristics of permanent neonatal diabetes (PNDM) in the state of Qatar

Background

Neonatal diabetes mellitus (NDM) is a rare condition that occurs within the first six months of life. Permanent NDM (PNDM) is caused by mutations in specific genes that are known for their expression at early and/or late stages of pancreatic beta‐ cell development, and are either involved in beta‐cell survival, insulin processing, regulation, and release. The native population in Qatar continues to practice consanguineous marriages that lead to a high level of homozygosity. To our knowledge, there is no previous report on the genomics of NDM among the Qatari population. The aims of the current study are to identify patients with NDM diagnosed between 2001 and 2016, and examine their clinical and genetic characteristics.

Methods

To calculate the incidence of PNDM, all patients with PNDM diagnosed between 2001 and 2016 were compared to the total number of live births over the 16‐year‐period. Whole Genome Sequencing (WGS) was used to investigate the genetic etiology in the PNDM cohort.

Results

PNDM was diagnosed in nine (n = 9) patients with an estimated incidence rate of 1:22,938 live births among the indigenous Qatari. Seven different mutations in six genes (PTF1A, GCK, SLC2A2, EIF2AK3, INS, and HNF1B) were identified. In the majority of cases, the genetic etiology was part of a previously identified autosomal recessive disorder. Two novel de novo mutations were identified in INS and HNF1B.

Conclusion

Qatar has the second highest reported incidence of PNDM worldwide. A majority of PNDM cases present as rare familial autosomal recessive disorders. Pancreas associated transcription factor 1a (PTF1A) enhancer deletions are the most common cause of PNDM in Qatar, with only a few previous cases reported in the literature.

Precision Medicine in Internal Medicine

Medicine has long sought to match diagnostic and treatment approaches to the particular needs and risks of individual patients. The decreasing cost and increasing ease of genetic sequencing have propelled the rise of precision medicine. Precision medicine aims to use genetic and other information to provide care tailored to the individual patient, with the goal of improving clinical outcomes and minimizing unnecessary diagnostic and therapeutic interventions. Although developments in genetic sequencing have the potential to transform clinical care, there are important limitations, including uncertainty in the clinical interpretation of many genetic variants and concerns about privacy, discrimination, and cost. To help clinicians understand the basics of genetic sequencing and how to apply it in clinical practice, Annals of Internal Medicine is launching a new "Precision Medicine" series. This introduction provides a general overview of clinical sequencing, with a focus on germline variation. Subsequent articles will use a case-based format to provide concise summaries of specific clinical precision medicine scenarios that are relevant to the practice of internal medicine. These cases will highlight specific clinical indications; interpretation of genetic test results; and ethical, legal, cost, and privacy issues related to genetic testing. The goal is to provide practical information on the appropriate application and interpretation of genomics in routine clinical practice.

Practical Aspects in Genetic Testing for Cardiomyopathies and Channelopathies

Genetic testing has an increasingly important role in the diagnosis and management of cardiac disorders, where it confirms the diagnosis, aids prognostication and risk stratification and guides treatment. A genetic diagnosis in the proband also enables clarification of the risk for family members by cascade testing. Genetics in cardiac disorders is complex where epigenetic and environmental factors might come into interplay. Incomplete penetrance and variable expressivity is also common. Genetic results in cardiac conditions are mostly probabilistic and should be interpreted with all available clinical information. With this complexity in cardiac genetics, testing is only indicated in patients with a strong suspicion of an inheritable cardiac disorder after a full clinical evaluation. In this review we discuss the genetics underlying the major cardiomyopathies and channelopathies, and the practical aspects of diagnosing these conditions in the laboratory.

The classification, genetic diagnosis and modelling of monogenic autoinflammatory disorders

Monogenic autoinflammatory disorders are an increasingly heterogeneous group of conditions characterised by innate immune dysregulation. Improved genetic sequencing in recent years has led not only to the discovery of a plethora of conditions considered to be 'autoinflammatory', but also the broadening of the clinical and immunological phenotypic spectra seen in these disorders. This review outlines the classification strategies that have been employed for monogenic autoinflammatory disorders to date, including the primary innate immune pathway or the dominant cytokine implicated in disease pathogenesis, and highlights some of the advantages of these models. Furthermore, the use of the term 'autoinflammatory' is discussed in relation to disorders that cross the innate and adaptive immune divide. The utilisation of next-generation sequencing (NGS) in this population is examined, as are potential in vivo and in vitro methods of modelling to determine pathogenicity of novel genetic findings. Finally, areas where our understanding can be improved are highlighted, such as phenotypic variability and genotype-phenotype correlations, with the aim of identifying areas of future research.

An integrated clinical program and crowdsourcing strategy for genomic sequencing and Mendelian disease gene discovery

Despite major progress in defining the genetic basis of Mendelian disorders, the molecular etiology of many cases remains unknown. Patients with these undiagnosed disorders often have complex presentations and require treatment by multiple health care specialists. Here, we describe an integrated clinical diagnostic and research program using whole-exome and whole-genome sequencing (WES/WGS) for Mendelian disease gene discovery. This program employs specific case ascertainment parameters, a WES/WGS computational analysis pipeline that is optimized for Mendelian disease gene discovery with variant callers tuned to specific inheritance modes, an interdisciplinary crowdsourcing strategy for genomic sequence analysis, matchmaking for additional cases, and integration of the findings regarding gene causality with the clinical management plan. The interdisciplinary gene discovery team includes clinical, computational, and experimental biomedical specialists who interact to identify the genetic etiology of the disease, and when so warranted, to devise improved or novel treatments for affected patients. This program effectively integrates the clinical and research missions of an academic medical center and affords both diagnostic and therapeutic options for patients suffering from genetic disease. It may therefore be germane to other academic medical institutions engaged in implementing genomic medicine programs.

Genomic medicine for kidney disease

Technologies such as next-generation sequencing and chromosomal microarray have advanced the understanding of the molecular pathogenesis of a variety of renal disorders. Genetic findings are increasingly used to inform the clinical management of many nephropathies, enabling targeted disease surveillance, choice of therapy, and family counselling. Genetic analysis has excellent diagnostic utility in paediatric nephrology, as illustrated by sequencing studies of patients with congenital anomalies of the kidney and urinary tract and steroid-resistant nephrotic syndrome. Although additional investigation is needed, pilot studies suggest that genetic testing can also provide similar diagnostic insight among adult patients. Reaching a genetic diagnosis first involves choosing the appropriate testing modality, as guided by the clinical presentation of the patient and the number of potential genes associated with the suspected nephropathy. Genome-wide sequencing increases diagnostic sensitivity relative to targeted panels, but holds the challenges of identifying causal variants in the vast amount of data generated and interpreting secondary findings. In order to realize the promise of genomic medicine for kidney disease, many technical, logistical, and ethical questions that accompany the implementation of genetic testing in nephrology must be addressed. The creation of evidence-based guidelines for the utilization and implementation of genetic testing in nephrology will help to translate genetic knowledge into improved clinical outcomes for patients with kidney disease.

Rare Disease Mechanisms Identified by Genealogical Proteomics of Copper Homeostasis Mutant Pedigrees

Rare neurological diseases shed light onto universal neurobiological processes. However, molecular mechanisms connecting genetic defects to their disease phenotypes are elusive. Here, we obtain mechanistic information by comparing proteomes of cells from individuals with rare disorders with proteomes from their disease-free consanguineous relatives. We use triple-SILAC mass spectrometry to quantify proteomes from human pedigrees affected by mutations in ATP7A, which cause Menkes disease, a rare neurodegenerative and neurodevelopmental disorder stemming from systemic copper depletion. We identified 214 proteins whose expression was altered in ATP7A^-/y fibroblasts. Bioinformatic analysis of ATP7A-mutant proteomes identified known phenotypes and processes affected in rare genetic diseases causing copper dyshomeostasis, including altered mitochondrial function. We found connections between copper dyshomeostasis and the UCHL1/PARK5 pathway of Parkinson disease, which we validated with mitochondrial respiration and Drosophila genetics assays. We propose that our genealogical "omics" strategy can be broadly applied to identify mechanisms linking a genomic locus to its phenotypes.

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.

Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes

Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes.Variants causing loss of function (LoF) of human genes have clinical implications. Here, the authors present a method to predict disease-causing potential of LoF variants, ALoFT (annotation of Loss-of-Function Transcripts) and show its application to interpreting LoF variants in different contexts.

Systematic screening for skin, hair, and nail abnormalities in a large-scale knockout mouse program

The International Knockout Mouse Consortium was formed in 2007 to inactivate (“knockout”) all protein-coding genes in the mouse genome in embryonic stem cells. Production and characterization of these mice, now underway, has generated and phenotyped 3,100 strains with knockout alleles. Skin and adnexa diseases are best defined at the gross clinical level and by histopathology. Representative retired breeders had skin collected from the back, abdomen, eyelids, muzzle, ears, tail, and lower limbs including the nails. To date, 169 novel mutant lines were reviewed and of these, only one was found to have a relatively minor sebaceous gland abnormality associated with follicular dystrophy. The B6N(Cg)-Far2^{tm2b(KOMP)Wtsi}/2J strain, had lesions affecting sebaceous glands with what appeared to be a secondary follicular dystrophy. A second line, B6N(Cg)-Ppp1r9b^{tm1.1(KOMP)Vlcg}/J, had follicular dystrophy limited to many but not all mystacial vibrissae in heterozygous but not homozygous mutant mice, suggesting that this was a nonspecific background lesion. We discuss potential reasons for the low frequency of skin and adnexal phenotypes in mice from this project in comparison to those seen in human Mendelian diseases, and suggest alternative approaches to identification of human disease-relevant models.

Molecular and functional characterization of the BMPR2 gene in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension is a progressive disease that causes the obstruction of precapillary pulmonary arteries and a sustained increase in pulmonary vascular resistance. The aim was to analyze functionally the variants found in the BMPR2 gene and to establish a genotype-phenotype correlation. mRNA expression studies were performed using pSPL3 vector, studies of subcellular localization were performed using pEGFP-N1 vector and luciferase assays were performed using pGL3-Basic vector. We have identified 30 variants in the BMPR2 gene in 27 of 55 patients. In 16 patients we detected pathogenic mutations. Minigene assays revealed that 6 variants (synonymous, missense) result in splicing defect. By immunofluorescence assay, we observed that 4 mutations affect the protein localization. Finally, 4 mutations located in the 5'UTR region showed a decreased transcriptional activity in luciferase assays. Genotype-phenotype correlation, revealed that patients with pathogenic mutations have a more severe phenotype (sPaP p = 0.042, 6MWT p = 0.041), a lower age at diagnosis (p = 0.040) and seemed to have worse response to phosphodiesterase-5-inhibitors (p = 0.010). Our study confirms that in vitro expression analysis is a suitable approach in order to investigate the phenotypic consequences of the nucleotide variants, especially in cases where the involved genes have a pattern of expression in tissues of difficult access.

Molecular defects identified by whole exome sequencing in a child with atypical mucopolysaccharidosis IIIB

BACKGROUND

Mucopolysaccharidosis IIIB (MPS IIIB) is a genetic disease characterized by mutations in the NAGLU gene, deficiency of α-N-acetylglucosaminidase, multiple congenital malformations and an increased susceptibility to malignancy. Because of the slow progressive nature of this disease and its atypical symptoms, the misdiagnosis of MPS IIIB is not rare in clinical practice. This misdiagnosis could be avoided by using next-generation sequencing (NGS) techniques, which have been shown to have superior performance for detecting mutations underlying rare inherited disorders in previous studies.

CASE PRESENTATION

Whole exome sequencing (WES) was conducted and the putative pathogenic variants were validated by Sanger sequencing. The activity of MPS IIIB related enzyme in the patient's blood serum was assayed. A heterozygous, non-synonymous mutation (c.1562C>T, p.P521L) as well as a novel mutation (c.1705C>A, p.Q569K) were found in the NAGLU gene of the patient. The two mutations were validated by Sanger sequencing. Our data showed that this patient's c.1562C>T, p.P521L mutation in the NAGLU gene was inherited from his father and c.1705C>A, p.Q569K was from his mother. The diagnosis was further confirmed by an enzymatic activity assay after patient recall and follow-up.

CONCLUSIONS

Our results describe an atypical form of MPS IIIB and illustrate the diagnostic potential of targeted WES in Mendelian disease with unknown etiology. WES could become a powerful tool for molecular diagnosis of MPS IIIB in clinical setting.

The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

The Human Gene Mutation Database (HGMD^®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD ( http://www.hgmd.org ) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.

The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

The Human Gene Mutation Database (HGMD^®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.

Classification of Genes: Standardized Clinical Validity Assessment of Gene-Disease Associations Aids Diagnostic Exome Analysis and Reclassifications

Ascertaining a diagnosis through exome sequencing can provide potential benefits to patients, insurance companies, and the healthcare system. Yet, as diagnostic sequencing is increasingly employed, vast amounts of human genetic data are produced that need careful curation. We discuss methods for accurately assessing the clinical validity of gene-disease relationships to interpret new research findings in a clinical context and increase the diagnostic rate. The specifics of a gene-disease scoring system adapted for use in a clinical laboratory are described. In turn, clinical validity scoring of gene-disease relationships can inform exome reporting for the identification of new or the upgrade of previous, clinically relevant gene findings. Our retrospective analysis of all reclassification reports from the first 4 years of diagnostic exome sequencing showed that 78% were due to new gene-disease discoveries published in the literature. Among all exome positive/likely positive findings in characterized genes, 32% were in genetic etiologies that were discovered after 2010. Our data underscore the importance and benefits of active and up-to-date curation of a gene-disease database combined with critical clinical validity scoring and proactive reanalysis in the clinical genomics era.

A Novel Single Nucleotide T980C Polymorphism in the Human Carboxypeptidase E Gene Results in Loss of Neuroprotective Function

Report of a human with a homozygous truncating null mutation of the Carboxypeptidase E (CPE) gene with endocrinological and neurological deficits prompted us to search for other mutations in the human CPE gene that might be linked to disease. We searched an EST database and identified from a small population of patients, a novel T to C single nucleotide polymorphism (SNP) in the CPE gene at bp980 of exon 4, herein called TC-CPE. This introduces a tryptophan to arginine (W235R) mutation in the catalytic domain of human CPE protein. Over-expression of TC-CPE in N2A cells, a neuroendocrine cell line, showed that it was synthesized, but was found in lesser amounts compared to over-expressed WT-CPE in these cells. Furthermore, TC-CPE was secreted poorly from these N2A cells. The levels of TC-CPE were significantly increased after the N2A cells were treated with MG132 (a proteasome inhibitor), suggesting that TC-CPE was targeted to proteasomes for degradation in N2A cells. In addition, TC-CPE induced ER stress as demonstrated by the increased expression of CHOP in N2A cells. Double labeling of CPE and calnexin (and ER marker) suggested the accumulation of TC-CPE in the ER, and the accumulation appears to be enhanced by the treatment of MG132 in the cells. Moreover, the secreted levels of TC-CPE were not affected by the treatment of MG132 in the cells. Over-expression studies revealed that while N2A cells transfected with WT-CPE showed reduced cytotoxicity when challenged with H₂O₂ compared to cells expressing an empty vector, cells transfected with TC-CPE had no effect. Furthermore, WT-CPE condition medium showed protective effect against oxidative stress, but not TC-CPE condition medium. Although co-expression of WT-CPE and TC-CPE in N2A cells resulted in the reduction in secretion of WT-CPE, co-expression of WT-CPE and TC-CPE did not significantly affect the protective effect of WT-CPE. Taken together, we have identified a novel SNP in the CPE gene which results in the loss of its neuroprotective function in cells and may confer neurological disorders in humans.

European healthcare systems readiness to shift from ‘one-size fits all’ to personalized medicine

Personalized medicine (PM) is no longer an abstract healthcare approach. It has become a reality over the last years and is already successfully applied in the various medical fields. Although there are success stories of implementing PM, there are still many more opportunities to further implement and make full use of the potential of PM. We assessed the system readiness of healthcare systems in Europe to shift from the predominant ‘one size fits all’ healthcare approach to PM. We conclude that European healthcare systems are only partially ready for PM. Key challenges such as integration of big data, health literacy, reimbursement and regulatory issues need to be overcome in order to strengthen the implementation and uptake of PM.

Regulatory single nucleotide polymorphisms (rSNPs) at the promoters 1A and 1B of the human APC gene

Background

Germline mutations in the coding sequence of the tumour suppressor APC gene give rise to familial adenomatous polyposis (which leads to colorectal cancer) and are associated with many other oncopathologies. The loss of APC function because of deletion of putative promoter 1A or 1B also results in the development of colorectal cancer. Since the regions of promoters 1A and 1B contain many single nucleotide polymorphisms (SNPs), the aim of this study was to perform functional analysis of some of these SNPs by means of an electrophoretic mobility shift assay (EMSA) and a luciferase reporter assay.

Results

First, it was shown that both putative promoters of APC (1A and 1B) drive transcription in an in vitro reporter experiment. From eleven randomly selected SNPs of promoter 1A and four SNPs of promoter 1B, nine and two respectively showed differential patterns of binding of nuclear proteins to oligonucleotide probes corresponding to alternative alleles. The luciferase reporter assay showed that among the six SNPs tested, the rs75612255 C allele and rs113017087 C allele in promoter 1A as well as the rs138386816 T allele and rs115658307 T allele in promoter 1B significantly increased luciferase activity in the human erythromyeloblastoid leukaemia cell line K562. In human colorectal cancer HCT-116 cells, none of the substitutions under study had any effect, with the exception of minor allele G of rs79896135 in promoter 1B. This allele significantly decreased the luciferase reporter’s activity

Conclusion

Our results indicate that many SNPs in APC promoters 1A and 1B are functionally relevant and that allele G of rs79896135 may be associated with the predisposition to colorectal cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0460-8) contains supplementary material, which is available to authorized users.

Regulatory single nucleotide polymorphisms at the beginning of intron 2 of the human KRAS gene

There are two regulatory single nucleotide polymorphisms (rSNPs) at the beginning of the second intron of the mouse K-ras gene that are strongly associated with lung cancer susceptibility. We performed functional analysis of three SNPs (rs12228277: T greater than A, rs12226937: G greater than A, and rs61761074: T greater than G) located in the same region of human KRAS. We found that rs12228277 and rs61761074 result in differential binding patterns of lung nuclear proteins to oligonucleotide probes corresponding two alternative alleles; in both cases, the transcription factor NF-Y is involved. G greater than A substitution (rs12226937) had no effect on the binding of lung nuclear proteins. However, all the nucleotide substitutions under study showed functional effects in a luciferase reporter assay. Among them, rs61761074 demonstrated a significant correlation with allele frequency in non-small-cell lung cancer (NSCLC). Taken together, the results of our study suggest that a T greater than G substitution at nucleotide position 615 in the second intron of the KRAS gene (rs61761074) may represent a promising genetic marker of NSCLC.

The Role of Deleterious Substitutions in Crop Genomes

Populations continually incur new mutations with fitness effects ranging from lethal to adaptive. While the distribution of fitness effects of new mutations is not directly observable, many mutations likely either have no effect on organismal fitness or are deleterious. Historically, it has been hypothesized that a population may carry many mildly deleterious variants as segregating variation, which reduces the mean absolute fitness of the population. Recent advances in sequencing technology and sequence conservation-based metrics for inferring the functional effect of a variant permit examination of the persistence of deleterious variants in populations. The issue of segregating deleterious variation is particularly important for crop improvement, because the demographic history of domestication and breeding allows deleterious variants to persist and reach moderate frequency, potentially reducing crop productivity. In this study, we use exome resequencing of 15 barley accessions and genome resequencing of 8 soybean accessions to investigate the prevalence of deleterious single nucleotide polymorphisms (SNPs) in the protein-coding regions of the genomes of two crops. We conclude that individual cultivars carry hundreds of deleterious SNPs on average, and that nonsense variants make up a minority of deleterious SNPs. Our approach identifies known phenotype-altering variants as deleterious more frequently than the genome-wide average, suggesting that putatively deleterious variants are likely to affect phenotypic variation. We also report the implementation of a SNP annotation tool BAD_Mutations that makes use of a likelihood ratio test based on alignment of all currently publicly available Angiosperm genomes.

Opportunities and technical challenges in next-generation sequencing for diagnosis of rare pediatric diseases

INTRODUCTION

Rare pediatric diseases are clinically severe with high rates of mortality and morbidity. This paper outlines how next-generation sequencing (NGS) can be used to greatly advance identification of the underlying genetic causes. Areas covered: This manuscript is a blend of evidence obtained from literature searches from PubMed and rare disease related websites, laboratory experience and the author's opinions. The paper covers the current state of the field and identifies where the challenges lie and how they are being overcome, using up-to-date references. Expert commentary: The field of NGS is still relatively new but it has already transformed the field of rare disease research. Technological advances in instrumentation, computational hardware and software have resulted in the identification of many causative genes, but as sequencing moves into population-scale initiatives standardisation and data sharing is going to be of paramount importance to ensure we derive the maximum benefit for patients.

Candidate-gene criteria for clinical reporting: diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases

Purpose:

Diagnostic exome sequencing (DES) is now a commonly ordered test for individuals with undiagnosed genetic disorders. In addition to providing a diagnosis for characterized diseases, exome sequencing has the capacity to uncover novel candidate genes for disease.

Methods:

Family-based DES included analysis of both characterized and novel genetic etiologies. To evaluate candidate genes for disease in the clinical setting, we developed a systematic, rule-based classification schema.

Results:

Testing identified a candidate gene among 7.7% (72/934) of patients referred for DES; 37 (4.0%) and 35 (3.7%) of the genes received evidence scores of “candidate” and “suspected candidate,” respectively. A total of 71 independent candidate genes were reported among the 72 patients, and 38% (27/71) were subsequently corroborated in the peer-reviewed literature. This rate of corroboration increased to 51.9% (27/52) among patients whose gene was reported at least 12 months previously.

Conclusions:

Herein, we provide transparent, comprehensive, and standardized scoring criteria for the clinical reporting of candidate genes. These results demonstrate that DES is an integral tool for genetic diagnosis, especially for elucidating the molecular basis for both characterized and novel candidate genetic etiologies. Gene discoveries also advance the understanding of normal human biology and more common diseases.

Genet Med19 2, 224–235.

Insight into GATA1 transcriptional activity through interrogation of cis elements disrupted in human erythroid disorders

Whole-exome sequencing has been incredibly successful in identifying causal genetic variants and has revealed a number of novel genes associated with blood and other diseases. One limitation of this approach is that it overlooks mutations in noncoding regulatory elements. Furthermore, the mechanisms by which mutations in transcriptionalcis-regulatory elements result in disease remain poorly understood. Here we used CRISPR/Cas9 genome editing to interrogate three such elements harboring mutations in human erythroid disorders, which in all cases are predicted to disrupt a canonical binding motif for the hematopoietic transcription factor GATA1. Deletions of as few as two to four nucleotides resulted in a substantial decrease (>80%) in target gene expression. Isolated deletions of the canonical GATA1 binding motif completely abrogated binding of the cofactor TAL1, which binds to a separate motif. Having verified the functionality of these three GATA1 motifs, we demonstrate strong evolutionary conservation of GATA1 motifs in regulatory elements proximal to other genes implicated in erythroid disorders, and show that targeted disruption of such elements results in altered gene expression. By modeling transcription factor binding patterns, we show that multiple transcription factors are associated with erythroid gene expression, and have created predictive maps modeling putative disruptions of their binding sites at key regulatory elements. Our study provides insight into GATA1 transcriptional activity and may prove a useful resource for investigating the pathogenicity of noncoding variants in human erythroid disorders.

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.

Targeted resequencing and variant validation using pxlence PCR assays

The advent of next-generation sequencing technologies had a profound impact on molecular diagnostics. PCR is a popular method for target enrichment of disease gene panels. Using our proprietary primer-design pipeline, primerXL, we have created almost one million assays covering over 98% of the human exome. Here we describe the assay specification and both in silico and wet-lab validation of a selected set of 2294 assays using both next-generation sequencing and Sanger sequencing. Using a universal PCR protocol without optimization, these assays result in high coverage uniformity and limited non-specific coverage. In addition, data indicates a positive correlation between the predictive in silico specificity score and the amount of assay non-specific coverage.

Correction of a Cystic Fibrosis Splicing Mutation by Antisense Oligonucleotides

Cystic fibrosis (CF), the most common life-threatening genetic disease in Caucasians, is caused by ∼2,000 different mutations in the CF transmembrane conductance regulator (CFTR) gene. A significant fraction of these (∼13%) affect pre-mRNA splicing for which novel therapies have been somewhat neglected. We have previously described the effect of the CFTR splicing mutation c.2657+5G>A in IVS16, showing that it originates transcripts lacking exon 16 as well as wild-type transcripts. Here, we tested an RNA-based antisense oligonucleotide (AON) strategy to correct the aberrant splicing caused by this mutation. Two AONs (AON1/2) complementary to the pre-mRNA IVS16 mutant region were designed and their effect on splicing was assessed at the RNA and protein levels, on intracellular protein localization and function. To this end, we used the 2657+5G>A mutant CFTR minigene stably expressed in HEK293 Flp-In cells that express a single copy of the transgene. RNA data from AON1-treated mutant cells show that exon 16 inclusion was almost completely restored (to 95%), also resulting in increased levels of correctly localized CFTR protein at the plasma membrane (PM) and with increased function. A novel two-color CFTR splicing reporter minigene developed here allowed the quantitative monitoring of splicing by automated microscopy localization of CFTR at the PM. The AON strategy is thus a promising therapeutic approach for the specific correction of alternative splicing.

Genetic studies in intellectual disability and related disorders

Genetic factors play a major part in intellectual disability (ID), but genetic studies have been complicated for a long time by the extreme clinical and genetic heterogeneity. Recently, progress has been made using different next-generation sequencing approaches in combination with new functional readout systems. This approach has provided novel insights into the biological pathways underlying ID, improved the diagnostic process and offered new targets for therapy. In this Review, we highlight the insights obtained from recent studies on the role of genetics in ID and its impact on diagnosis, prognosis and therapy. We also discuss the future directions of genetics research for ID and related neurodevelopmental disorders.

Participant-driven matchmaking in the genomic era

Whole-genome and whole-exome sequencing are increasingly useful diagnostic tools for novel monogenic conditions. In order to confirm diagnoses made using these technologies, genomic matchmaking-the matching of cases with similar phenotypic and/or genotypic profiles, to narrow the number of candidate genes or ascertain a condition's etiology with greater certainty-is essential. Yet, due to current limitations on the size of matchmaking networks and data sets available to support them, identifying a match can be difficult. We argue that matchmaking efforts led by affected individuals and their families-participant-led efforts-offer a twofold solution to this need, in that participants both have the capacity to access larger networks and to provide more detailed sets of phenotypic and genotypic data. These features of participant-led efforts have the potential to increase the value of matchmaking networks, both in terms of number of matches and in terms of the overall energy of the network. We provide two examples of participant-led matchmaking, and propose a model for scaling these efforts.

The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

Linkage Analysis of Urine Arsenic Species Patterns in the Strong Heart Family Study

Arsenic toxicokinetics are important for disease risks in exposed populations, but genetic determinants are not fully understood. We examined urine arsenic species patterns measured by HPLC-ICPMS among 2189 Strong Heart Study participants 18 years of age and older with data on ~400 genome-wide microsatellite markers spaced ~10 cM and arsenic speciation (683 participants from Arizona, 684 from Oklahoma, and 822 from North and South Dakota). We logit-transformed % arsenic species (% inorganic arsenic, %MMA, and %DMA) and also conducted principal component analyses of the logit % arsenic species. We used inverse-normalized residuals from multivariable-adjusted polygenic heritability analysis for multipoint variance components linkage analysis. We also examined the contribution of polymorphisms in the arsenic metabolism gene AS3MT via conditional linkage analysis. We localized a quantitative trait locus (QTL) on chromosome 10 (LOD 4.12 for %MMA, 4.65 for %DMA, and 4.84 for the first principal component of logit % arsenic species). This peak was partially but not fully explained by measured AS3MT variants. We also localized a QTL for the second principal component of logit % arsenic species on chromosome 5 (LOD 4.21) that was not evident from considering % arsenic species individually. Some other loci were suggestive or significant for 1 geographical area but not overall across all areas, indicating possible locus heterogeneity. This genome-wide linkage scan suggests genetic determinants of arsenic toxicokinetics to be identified by future fine-mapping, and illustrates the utility of principal component analysis as a novel approach that considers % arsenic species jointly.

Disease-associated variants in different categories of disease located in distinct regulatory elements

Background

The invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases. Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome. These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Identifying these diseased-related regulatory elements will shed light on understanding the mechanisms of how these variants regulate gene expression and ultimately result in disease formation and progression.

Results

In this study, we curated and categorized 27,558 Mendelian disease variants, 20,964 complex disease variants, 5,809 cancer predisposing germline variants, and 43,364 recurrent cancer somatic mutations. Compared against nine different types of regulatory regions from FANTOM5 and ENCODE projects, we found that different types of disease variants show distinctive propensity for particular regulatory elements. Mendelian disease variants and recurrent cancer somatic mutations are 22-fold and 10- fold significantly enriched in promoter regions respectively (q<0.001), compared with allele-frequency-matched genomic background. Separate from these two categories, cancer predisposing germline variants are 27-fold enriched in histone modification regions (q<0.001), 10-fold enriched in chromatin physical interaction regions (q<0.001), and 6-fold enriched in transcription promoters (q<0.001). Furthermore, Mendelian disease variants and recurrent cancer somatic mutations share very similar distribution across types of functional effects.

We further found that regulatory regions are located within over 50% coding exon regions. Transcription promoters, methylation regions, and transcription insulators have the highest density of disease variants, with 472, 239, and 72 disease variants per one million base pairs, respectively.

Conclusions

Disease-associated variants in different disease categories are preferentially located in particular regulatory elements. These results will be useful for an overall understanding about the differences among the pathogenic mechanisms of various disease-associated variants.

A genome sequencing program for novel undiagnosed diseases

PURPOSE

The Scripps Idiopathic Diseases of Man (IDIOM) study aims to discover novel gene-disease relationships and provide molecular genetic diagnosis and treatment guidance for individuals with novel diseases using genome sequencing integrated with clinical assessment and multidisciplinary case review. Here we describe the operational protocol and initial results of the IDIOM study.

METHODS

A total of 121 cases underwent first-tier review by the principal investigators to determine whether the primary inclusion criteria were satisfied, 59 (48.8%) underwent second-tier review by our clinician-scientist review panel, and 17 patients (14.0%) and their family members were enrolled.

RESULTS

60% of cases resulted in a plausible molecular diagnosis, and 18% of cases resulted in a confirmed molecular diagnosis. Two of three confirmed cases led to the identification of novel gene-disease relationships. In the third confirmed case a previously described but unrecognized disease was revealed. In all three confirmed cases a new clinical management strategy was initiated based on the genetic findings.

CONCLUSION

Genome sequencing provides tangible clinical benefit for individuals with idiopathic genetic disease, not only in the context of molecular genetic diagnosis of known rare conditions but also in cases where prior clinical information regarding a new genetic disorder is lacking.

Symptom-driven idiopathic disease gene identification

Purpose

Rare genetic variants are the major cause of Mendelian disorders, yet only half of described genetic diseases have been causally linked to a gene. In addition, the total number of rare genetic diseases is projected to be far greater than that of those already described. Whole-genome sequencing of patients with subsequent genetic and functional analysis is a powerful way to describe these gene anomalies. However, this approach results in tens to hundreds of candidate disease-causative genes, and the identification of additional individuals suffering from the same disorder can be difficult because of rarity and phenotypic heterogeneity.

Methods

We describe a genetic network–based method to rank candidate genes identified in family-based sequencing studies, termed phenotype informed network (PIN) ranking. Furthermore, we present a case study as an extension of the PIN ranking method in which disease symptoms drive the network ranking and identification of the disease-causative gene.

Results

We demonstrate, through simulation, that our method is capable of identifying the correct disease-causative gene in a majority of cases. PIN-rank is available at https://genomics.scripps.edu/pin-rank/.

Conclusion

We have developed a method to prioritize candidate disease-causative genes based on symptoms that would be useful for both the prioritization of candidates and the identification of additional subjects.

Evolutionary and structural annotation of disease-associated mutations in human aminoacyl-tRNA synthetases

Background

Mutation(s) in proteins are a natural byproduct of evolution but can also cause serious diseases. Aminoacyl-tRNA synthetases (aaRSs) are indispensable components of all cellular protein translational machineries, and in humans they drive translation in both cytoplasm and mitochondria. Mutations in aaRSs have been implicated in a plethora of diseases including neurological conditions, metabolic disorders and cancer.

Results

We have developed an algorithmic approach for genome-wide analyses of sequence substitutions that combines evolutionary, structural and functional information. This pipeline enabled us to super-annotate human aaRS mutations and analyze their linkage to health disorders. Our data suggest that in some but not all cases, aaRS mutations occur in functional and structural sectors where they can manifest their pathological effects by altering enzyme activity or causing structural instability. Further, mutations appear in both solvent exposed and buried regions of aaRSs indicating that these alterations could lead to dysfunctional enzymes resulting in abnormal protein translation routines by affecting inter-molecular interactions or by disruption of non-bonded interactions. Overall, the prevalence of mutations is much higher in mitochondrial aaRSs, and the two most often mutated aaRSs are mitochondrial glutamyl-tRNA synthetase and dual localized glycyl-tRNA synthetase. Out of 63 mutations annotated in this work, only 12 (~20%) were observed in regions that could directly affect aminoacylation activity via either binding to ATP/amino-acid, tRNA or by involvement in dimerization. Mutations in structural cores or at potential biomolecular interfaces account for ~55% mutations while remaining mutations (~25%) remain structurally un-annotated.

Conclusion

This work provides a comprehensive structural framework within which most defective human aaRSs have been structurally analyzed. The methodology described here could be employed to annotate mutations in other protein families in a high-throughput manner.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1063) contains supplementary material, which is available to authorized users.

FLAGS, frequently mutated genes in public exomes

BACKGROUND

Dramatic improvements in DNA-sequencing technologies and computational analyses have led to wide use of whole exome sequencing (WES) to identify the genetic basis of Mendelian disorders. More than 180 novel rare-disease-causing genes with Mendelian inheritance patterns have been discovered through sequencing the exomes of just a few unrelated individuals or family members. As rare/novel genetic variants continue to be uncovered, there is a major challenge in distinguishing true pathogenic variants from rare benign mutations.

METHODS

We used publicly available exome cohorts, together with the dbSNP database, to derive a list of genes (n = 100) that most frequently exhibit rare (<1%) non-synonymous/splice-site variants in general populations. We termed these genes FLAGS for FrequentLy mutAted GeneS and analyzed their properties.

RESULTS

Analysis of FLAGS revealed that these genes have significantly longer protein coding sequences, a greater number of paralogs and display less evolutionarily selective pressure than expected. FLAGS are more frequently reported in PubMed clinical literature and more frequently associated with diseased phenotypes compared to the set of human protein-coding genes. We demonstrated an overlap between FLAGS and the rare-disease causing genes recently discovered through WES studies (n = 10) and the need for replication studies and rigorous statistical and biological analyses when associating FLAGS to rare disease. Finally, we showed how FLAGS are applied in disease-causing variant prioritization approach on exome data from a family affected by an unknown rare genetic disorder.

CONCLUSIONS

We showed that some genes are frequently affected by rare, likely functional variants in general population, and are frequently observed in WES studies analyzing diverse rare phenotypes. We found that the rate at which genes accumulate rare mutations is beneficial information for prioritizing candidates. We provided a ranking system based on the mutation accumulation rates for prioritizing exome-captured human genes, and propose that clinical reports associating any disease/phenotype to FLAGS be evaluated with extra caution.

Exome-driven characterization of the cancer cell lines at the proteome level: the NCI-60 case study

Cancer genome deviates significantly from the reference human genome, and thus a search against standard genome databases in cancer cell proteomics fails to identify cancer-specific protein variants. The goal of this Article is to combine high-throughput exome data [Abaan et al. Cancer Res. 2013] and shotgun proteomics analysis [Modhaddas Gholami et al. Cell Rep. 2013] for cancer cell lines from NCI-60 panel to demonstrate further that the cell lines can be effectively recognized using identified variant peptides. To achieve this goal, we generated a database containing mutant protein sequences of NCI-60 panel of cell lines. The proteome data were searched using Mascot and X!Tandem search engines against databases of both reference and mutant protein sequences. The identification quality was further controlled by calculating a fraction of variant peptides encoded by the own exome sequence for each cell line. We found that up to 92.2% peptides identified by both search engines are encoded by the own exome. Further, we used the identified variant peptides for cell line recognition. The results of the study demonstrate that proteome data supported by exome sequence information can be effectively used for distinguishing between different types of cancer cell lines.

Stakeholder analysis in pharmacogenomics and genomic medicine in Greece

BACKGROUND

The pace of discoveries and advances in genomic research is not reflected in the pace of their translation and incorporation into day-to-day clinical medicine to individualize healthcare decision-making processes. One of the main obstacles is the poor understanding of the policies and the key stakeholders involved in these translation processes.

METHODS

We used the computerized version of the PolicyMaker political mapping tool to collect and organize important information about the pharmacogenomics and genomic medicine policy environment, serving as a database for assessments of the policy's content, the major players, their power and policy positions, their interests, and networks and coalitions that interconnect them.

RESULTS AND CONCLUSIONS

Our findings indicate that the genomic medicine policy environment in Greece seems to be rather positive, as the vast majority of the stakeholders express their medium to high support in the initially set goals of genomic medicine policy environment. The Ministry of Health and public healthcare insurance funds seem to oppose it, most likely due to financial constrains. These findings would contribute in selecting and implementing policy measures that will expedite the adoption of genomics into conventional medical interventions.