Gene and Variant Annotation for Mendelian Disorders in the Era of Advanced Sequencing Technologies

Utilization of Targeted RNA-Seq for the Resolution of Variant Pathogenicity and Enhancement of Diagnostic Yield in Dysferlinopathy

For inherited diseases, obtaining a definitive diagnosis is critical for proper disease management, family planning, and participation in clinical trials. This can be challenging for dysferlinopathy due to the significant clinical overlap between the 30+ subtypes of limb–girdle muscular dystrophy (LGMD) and the large number of variants of unknown significance (VUSs) that are identified in the dysferlin gene, DYSF. We performed targeted RNA-Seq using a custom gene-panel in 77 individuals with a clinical/genetic suspicion of dysferlinopathy and evaluated all 111 identified DYSF variants according to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines. This evaluation identified 11 novel DYSF variants and allowed for the classification of 87 DYSF variants as pathogenic/likely pathogenic, 8 likely benign, while 16 variants remained VUSs. By the end of the study, 60 of the 77 cases had a definitive diagnosis of dysferlinopathy, which was a 47% increase in diagnostic yield over the rate at study onset. This data shows the ability of RNA-Seq to assist in variant pathogenicity classification and diagnosis of dysferlinopathy and is, therefore, a type of analysis that should be considered when DNA-based genetic analysis is not sufficient to provide a definitive diagnosis.

A performance evaluation study: Variant annotation tools - The enigma of clinical next generation sequencing (NGS) based genetic testing

Dramatically expanding our ability for clinical genetic testing for inherited conditions and complex diseases such as cancer, next generation sequencing (NGS) technologies are allowing for rapid interrogation of thousands of genes and identification of millions of variants. Variant annotation, the process of assigning functional information to DNA variants based on the standardized Human Genome Variation Society (HGVS) nomenclature, is a fundamental challenge in the analysis of NGS data that has led to the development of many bioinformatic algorithms. In this study, we evaluated the performance of 3 variant annotation tools: Alamut® Batch, Ensembl Variant Effect Predictor (VEP), and ANNOVAR, benchmarked by a manually curated ground-truth set of 298 variants from the medical exome database at the Molecular Diagnostics Laboratory at Lurie Children's Hospital. Of the 3 tools, VEP produces the most accurate variant annotations (HGVS nomenclature for 297 of the 298 variants) due to usage of updated gene transcript versions within the algorithm. Alamut® Batch called 296 of the 298 variants correctly; strikingly, ANNOVAR exhibited the greatest number of discrepancies (20 of the 298 variants, 93.3% concordance with ground-truth set). Adoption of validated methods of variant annotation is critical in post-analytical phases of clinical testing.

Evaluation of Genetic Kidney Diseases in Living Donor Kidney Transplantation: Towards Precision Genomic Medicine in Donor Risk Assessment

Purpose of Review

To provide a comprehensive update on the role of genetic testing for the evaluation of kidney transplant recipient and living donor candidates.

Recent Findings

The evaluation of candidates for living donor transplantation and their potential donors occurs within an ever-changing landscape impacted by new evidence and risk assessment techniques. Criteria that were once considered contraindications to living kidney donation are now viewed as standard of care, while new tools identify novel risk markers that were unrecognized in past decades. Recent work suggests that nearly 10% of a cohort of patients with chronic/end-stage kidney disease had an identifiable genetic etiology, many whose original cause of renal disease was either unknown or misdiagnosed. Some also had an incidentally found genetic variant, unrelated to their nephropathy, but medically actionable. These patterns illustrate the substantial potential for genetic testing to better guide the selection of living donors and recipients, but guidance on the proper application and interpretation of novel technologies is in its infancy. In this review, we examine the utility of genetic testing in various kidney conditions, and discuss risks and unresolved challenges. Suggested algorithms in the context of related and unrelated donation are offered.

Summary

Genetic testing is a rapidly evolving strategy for the evaluation of candidates for living donor transplantation and their potential donors that has potential to improve risk assessment and optimize the safety of donation.

Current Status of Next-Generation Sequencing Approaches for Candidate Gene Discovery in Familial Parkinson´s Disease

Parkinson's disease is a neurodegenerative disorder with a heterogeneous genetic etiology. The advent of next-generation sequencing (NGS) technologies has aided novel gene discovery in several complex diseases, including PD. This Perspective article aimed to explore the use of NGS approaches to identify novel loci in familial PD, and to consider their current relevance. A total of 17 studies, spanning various populations (including Asian, Middle Eastern and European ancestry), were identified. All the studies used whole-exome sequencing (WES), with only one study incorporating both WES and whole-genome sequencing. It is worth noting how additional genetic analyses (including linkage analysis, haplotyping and homozygosity mapping) were incorporated to enhance the efficacy of some studies. Also, the use of consanguineous families and the specific search for de novo mutations appeared to facilitate the finding of causal mutations. Across the studies, similarities and differences in downstream analysis methods and the types of bioinformatic tools used, were observed. Although these studies serve as a practical guide for novel gene discovery in familial PD, these approaches have not significantly resolved the "missing heritability" of PD. We speculate that what is needed is the use of third-generation sequencing technologies to identify complex genomic rearrangements and new sequence variation, missed with existing methods. Additionally, the study of ancestrally diverse populations (in particular those of Black African ancestry), with the concomitant optimization and tailoring of sequencing and analytic workflows to these populations, are critical. Only then, will this pave the way for exciting new discoveries in the field.

PTEN hamartoma tumour syndrome: what happens when there is no PTEN germline mutation?

Hereditary cancer syndromes represent ~10% of all incident cancers. It is important to identify individuals having these disorders because, unlike patients with sporadic cancer, these patients require specialised life-long care, with implications for their families. Importantly, the identification of alterations in cancer-predisposing genes facilitates gene-informed molecular diagnosis, cancer risk assessment and gene-specific clinical management. Moreover, knowledge about gene function in the inherited cancers offers insights towards biological processes pertinent to the more common sporadic cancers. Conversely, without a known gene, clinical management is less precise, and it is impossible to offer predictive testing of family members. PTEN hamartoma tumour syndrome (PHTS) is an umbrella term encompassing four overgrowth and cancer predisposition disorders associated with germline PTEN mutations. With time, it became evident that only a finite subset of individuals with PHTS-associated phenotypes harbour germline PTEN mutations. Therefore, non-PTEN aetiologies exist in PTEN wildtype patients. Indeed, gene discovery efforts over the last decade elucidated multiple candidate cancer predisposition genes. While a subset of genes (e.g. AKT1, PIK3CA) are biologically plausible as being key effectors within the PTEN signalling cascade, other genes required meticulous functional interrogation to explain their contribution to PHTS-related phenotypes. Collectively, the extensive phenotypic heterogeneity of the clinical syndromes typically united by PTEN is reflected by the genetic heterogeneity revealed through gene discovery. Validating these gene discoveries is critical because, while PTEN wildtype patients can be diagnosed clinically, they do not have the benefit of specific gene-informed risk assessment and subsequent management.

Chemical map-based prediction of nucleosome positioning using the Bioconductor package nuCpos

Background

Assessing the nucleosome-forming potential of specific DNA sequences is important for understanding complex chromatin organization. Methods for predicting nucleosome positioning include bioinformatics and biophysical approaches. An advantage of bioinformatics methods, which are based on in vivo nucleosome maps, is the use of natural sequences that may contain previously unknown elements involved in nucleosome positioning in vivo. The accuracy of such prediction attempts reflects the genomic coordinate resolution of the nucleosome maps applied. Nucleosome maps are constructed using micrococcal nuclease digestion followed by high-throughput sequencing (MNase-seq). However, as MNase has a strong preference for A/T-rich sequences, MNase-seq may not be appropriate for this purpose. In addition to MNase-seq-based maps, base pair-resolution chemical maps of in vivo nucleosomes from three different species (budding and fission yeasts, and mice) are currently available. However, these chemical maps have yet to be integrated into publicly available computational methods.

Results

We developed a Bioconductor package (named nuCpos) to demonstrate the superiority of chemical maps in predicting nucleosome positioning. The accuracy of chemical map-based prediction in rotational settings was higher than that of the previously developed MNase-seq-based approach. With our method, predicted nucleosome occupancy reasonably matched in vivo observations and was not affected by A/T nucleotide frequency. Effects of genetic alterations on nucleosome positioning that had been observed in living yeast cells could also be predicted. nuCpos calculates individual histone binding affinity (HBA) scores for given 147-bp sequences to examine their suitability for nucleosome formation. We also established local HBA as a new parameter to predict nucleosome formation, which was calculated for 13 overlapping nucleosomal DNA subsequences. HBA and local HBA scores for various sequences agreed well with previous in vitro and in vivo studies. Furthermore, our results suggest that nucleosomal subsegments that are disfavored in different rotational settings contribute to the defined positioning of nucleosomes.

Conclusions

Our results demonstrate that chemical map-based statistical models are beneficial for studying nucleosomal DNA features. Studies employing nuCpos software can enhance understanding of chromatin regulation and the interpretation of genetic alterations and facilitate the design of artificial sequences.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04240-2.

Ancient DNA analysis of rare genetic bone disorders

OBJECTIVE

Review of the current advancements in the field of paleogenetics that provide new opportunities in studying the evolution of rare genetic bone diseases.

MATERIAL AND METHODS

Based on cases from the literature, the genetics of rare bone diseases will be introduced and the main methodological issues will be addressed, focusing on the opportunities presented by the application of aDNA analyses in the field of paleopathology.

RESULTS

Medical literature provides large datasets on the genes responsible for rare bone disorders. These genes, subdivided in functional categories, display important future targets when analyzing rare genetic bone disorders in ancient human remains.

CONCLUSIONS

Knowledge on both phenotype and genotype is required to study rare diseases in ancient human remains.

SIGNIFICANCE

The proposed interdisciplinary research will provide new insight into the occurrence and spread of genetic risk factors in the past and will help in the diagnostics of these rare and often neglected diseases.

LIMITATIONS

The current limitations in ancient DNA research and targeting the disease-causing specific mutations (e.g., somatic or germline).

SUGGESTIONS FOR FURTHER RESEARCH

Methodological advancements and candidate gene lists provide the optimal basis for future interdisciplinary studies of rare genetic bone disorders in ancient human remains.

Inborn errors of immunity-recent advances in research on the pathogenesis

Primary immunodeficiency (PID) is a genetic disorder with a defect of one of the important components of our immune system. Classical PID has been recognized as a disorder with loss of function of the immune system. Recent studies have unveiled disorders with immune dysfunction with autoimmunity, autoinflammation, allergy, or predisposition to malignancy. Some of them were caused by an augmented immune function or a defect in immune regulation. With this background, the term inborn errors of immunity (IEI) is now used to refer to PID in the International Union of Immunological Societies (IUIS) classification. More than 400 responsible genes have been identified in patients with IEI so far, and importantly, many of them identified lately were caused by a heterologous mutation. Moreover, the onset is not necessarily in childhood, and we started seeing more and more IEI patients diagnosed in adulthood in the clinical settings. Recent advances in genetic analysis, including whole-exome analysis, whole-genome analysis, and RNA-seq have contributed to the identification of the disease-causing gene mutation. We also started to find heterogeneity of phenotype even in the patients with the same mutation in the same family, leading us to wonder if modifier gene or epigenetic modification is involved in the pathogenesis. In contrast, we accumulated many cases suggesting genetic heterogeneity is associated with phenotypic homogeneity. It has thus become difficult to deduce a responsible gene only from the phenotype in a certain type of IEI. Current curative therapy for IEI includes hematopoietic cell transplantation and gene therapy. Other curative therapeutic modalities have been long waited and are to be introduced in the future. These include a small molecule that inhibits the gain-of-function of the molecule- and genome-editing technology. Research on IEI will surely lead to a better understanding of other immune-related disorders including rheumatic diseases and atopic disorders.

Geographical Distribution of E-cadherin Germline Mutations in the Context of Diffuse Gastric Cancer: A Systematic Review

Simple Summary

E-cadherin (CDH1 gene) germline mutations are associated with the development of the autosomal cancer syndrome known as hereditary diffuse gastric cancer. About 30% of families fulfilling the clinical criteria established by the International Gastric Cancer Linkage Consortium have constitutional alterations of the CDH1 gene. Different patterns of CDH1 germline mutations have described as truncating, deletion, insertion, splice site, non sense, silence, and at last, missense alterations. The frequency of the different E-cadherin germline mutations in countries with different incidence rates for gastric carcinoma has reported extremely variable. In this study we aimed to assess the worldwide frequency of CDH1 germline mutations in gastric cancers coming from different geographical areas, using a systematic approach.

Abstract

Hereditary diffuse gastric cancer (HDGC) is a complex and multifactorial inherited cancer predisposition syndrome caused by CDH1 germline mutations. Nevertheless, current CDH1 genetic screening recommendations disregard an unbalanced worldwide distribution of CDH1 variants, impacting testing efficacy and patient management. In this systematic review, we collected and analyzed all studies describing CDH1 variants in gastric cancer patients originating from both high- and low-prevalence countries. Selected studies were categorized as family study, series study, and unknown study, according to the implementation of HDGC clinical criteria for genetic testing. Our results indicate that CDH1 mutations are more frequently identified in gastric cancer low-incidence countries, and in the family study group that encompasses cases fulfilling criteria. Considering the type of CDH1 alterations, we verified that the relative frequency of mutation types varies within study groups and geographical areas. In the series study, the missense variant frequency is higher in high-incidence areas of gastric cancer, when compared with non-missense mutations. However, application of variant scoring for putative relevance led to a strong reduction of CDH1 variants conferring increased risk of gastric cancer. Herein, we demonstrate that criteria for CDH1 genetic screening are critical for identification of individuals carrying mutations with clinical significance. Further, we propose that future guidelines for testing should consider GC incidence across geographical regions for improved surveillance programs and early diagnosis of disease.

Detection of genetic variation and base modifications at base-pair resolution on both DNA and RNA

Accurate decoding of nucleic acid variation is critical to understand the complexity and regulation of genome function. Here we use a single-molecule magnetic tweezer (MT) platform to identify sequence variation and map a range of important epigenetic base modifications with high sensitivity, specificity, and precision in the same single molecules of DNA or RNA. We have also developed a highly specific amplification-free CRISPR-Cas enrichment strategy to isolate genomic regions from native DNA. We demonstrate enrichment of DNA from both E. coli and the FMR1 5'UTR coming from cells derived from a Fragile X carrier. From these kilobase-length enriched molecules we could characterize the differential levels of adenine and cytosine base modifications on E. coli, and the repeat expansion length and methylation status of FMR1. Together these results demonstrate that our platform can detect a variety of genetic, epigenetic, and base modification changes concomitantly within the same single molecules.

Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling

RNA polymerase transcribes certain genomic loci with higher errors rates. These transcription error-enriched genomic loci (TEELs) have implications in disease. Current deep-sequencing methods cannot distinguish TEELs from post-transcriptional modifications, stochastic transcription errors, and technical noise, impeding efforts to elucidate the mechanisms linking TEELs to disease. Here, we describe background error model-coupled precision nuclear run-on circular-sequencing (EmPC-seq) to discern genomic regions enriched for transcription misincorporations. EmPC-seq innovatively combines a nuclear run-on assay for capturing nascent RNA before post-transcriptional modifications, a circular-sequencing step that sequences the same nascent RNA molecules multiple times to improve accuracy, and a statistical model for distinguishing error-enriched regions among stochastic polymerase errors. Applying EmPC-seq to the ribosomal RNA transcriptome, we show that TEELs of RNA polymerase I are not randomly distributed but clustered together, with higher error frequencies at nascent transcript 3' ends. Our study establishes a reliable method of identifying TEELs with nucleotide precision, which can help elucidate their molecular origins.

Clinical utility of RNA sequencing to resolve unusual GNE myopathy with a novel promoter deletion

INTRODUCTION

UDP N-acetylglucosamine2-epimerase/N-acetylmannosamine-kinase (GNE) gene mutations can cause mostly autosomal-recessive myopathy with juvenile-onset known as hereditary inclusion-body myopathy (HIBM).

METHODS

We describe a family of a patient showing an unusual HIBM with both vacuolar myopathy and myositis without quadriceps-sparing, hindering diagnosis. We show how genetic testing with functional assays, clinical transcriptome sequencing (RNA-seq) in particular, helped facilitate both the diagnosis and a better understanding of the genotype-phenotype relationship.

RESULTS

We identified a novel 7.08 kb pathogenic deletion upstream of GNE using array comparative genomic hybridization (aCGH) and a common Val727Met variant. Using RNA-seq, we found only monoallelic (Val727Met-allele) expression, leading to ~50% GNE reduction in muscle. Importantly, α-dystroglycan is hypoglycosylated in the patient muscle, suggesting HIBM could be a "dystroglycanopathy."

CONCLUSIONS

Our study shows the importance of considering aCGH for GNE-myopathies, and the potential of RNA-seq for faster, definitive molecular diagnosis of unusual myopathies. Muscle Nerve, 2019.

Uncovering Missing Heritability in Rare Diseases

The problem of 'missing heritability' affects both common and rare diseases hindering: discovery, diagnosis, and patient care. The 'missing heritability' concept has been mainly associated with common and complex diseases where promising modern technological advances, like genome-wide association studies (GWAS), were unable to uncover the complete genetic mechanism of the disease/trait. Although rare diseases (RDs) have low prevalence individually, collectively they are common. Furthermore, multi-level genetic and phenotypic complexity when combined with the individual rarity of these conditions poses an important challenge in the quest to identify causative genetic changes in RD patients. In recent years, high throughput sequencing has accelerated discovery and diagnosis in RDs. However, despite the several-fold increase (from ~10% using traditional to ~40% using genome-wide genetic testing) in finding genetic causes of these diseases in RD patients, as is the case in common diseases-the majority of RDs are also facing the 'missing heritability' problem. This review outlines the key role of high throughput sequencing in uncovering genetics behind RDs, with a particular focus on genome sequencing. We review current advances and challenges of sequencing technologies, bioinformatics approaches, and resources.

Functional and Structural Features of Disease-Related Protein Variants

Modern sequencing technologies provide an unprecedented amount of data of single-nucleotide variations occurring in coding regions and leading to changes in the expressed protein sequences. A significant fraction of these single-residue variations is linked to disease onset and collected in public databases. In recent years, many scientific studies have been focusing on the dissection of salient features of disease-related variations from different perspectives. In this work, we complement previous analyses by updating a dataset of disease-related variations occurring in proteins with 3D structure. Within this dataset, we describe functional and structural features that can be of interest for characterizing disease-related variations, including major chemico-physical properties, the strength of association to disease of variation types, their effect on protein stability, their location on the protein structure, and their distribution in Pfam structural/functional protein models. Our results support previous findings obtained in different data sets and introduce Pfam models as possible fingerprints of patterns of disease related single-nucleotide variations.

Widening the landscape of heritable pulmonary hypertension mutations in paediatric and adult cases

BACKGROUND

Heritable forms of pulmonary arterial hypertension (PAH) and pulmonary veno-occlusive disease/pulmonary capillary haemangiomatosis (PVOD/PCH) diverge by lung histopathological lesions, clinical and para-clinical presentation, their responsible genes, and mode of transmission. Since the identification of the BMPR2 gene in families affected by PAH, mutations in several other genes have been discovered for both forms. The mutation landscape in these new genes is not yet well known.

METHODS

We set up a next-generation sequencing-based targeted sequencing gene panel allowing known genes for PAH and PVOD/PCH to be analysed simultaneously. Genetic analysis was prospectively performed on 263 PAH and PVOD/PCH patients (adult and paediatric cases).

RESULTS

Pathogenic mutations were identified in 19.5% of sporadic PAH patients (n=180), 54.5% of familial PAH patients and 13.3% of PVOD/PCH patients. BMPR2 was the most frequently mutated gene, followed by TBX4 in both paediatric and adult PAH. BMP9 mutations were identified in 1.2% of adult PAH cases. EIF2AK4 biallelic mutations were restricted to PVOD/PCH. A truncating mutation and a predicted loss-of-function variant were also identified in BMP10 in two severely affected sporadic PAH female patients.

CONCLUSION

Our results confirm that mutations are found in genes beyond BMPR2 in heritable PAH, emphasise the role of TBX4 and BMP9, and designate BMP10 as a new PAH gene.

Genetic landscape and novel disease mechanisms from a large LGMD cohort of 4656 patients

Objective

Limb‐girdle muscular dystrophies (LGMDs), one of the most heterogeneous neuromuscular disorders (NMDs), involves predominantly proximal‐muscle weakness with >30 genes associated with different subtypes. The clinical‐genetic overlap among subtypes and with other NMDs complicate disease‐subtype identification lengthening diagnostic process, increases overall costs hindering treatment/clinical‐trial recruitment. Currently seven LGMD clinical trials are active but still no gene‐therapy‐related treatment is available. Till‐date no nation‐wide large‐scale LGMD sequencing program was performed. Our objectives were to understand LGMD genetic basis, different subtypes’ relative prevalence across US and investigate underlying disease mechanisms.

Methods

A total of 4656 patients with clinically suspected‐LGMD across US were recruited to conduct next‐generation sequencing (NGS)‐based gene‐panel testing during June‐2015 to June‐2017 in CLIA‐CAP‐certified Emory‐Genetics‐Laboratory. Thirty‐five LGMD‐subtypes‐associated or LGMD‐like other NMD‐associated genes were investigated. Main outcomes were diagnostic yield, gene‐variant spectrum, and LGMD subtypes’ prevalence in a large US LGMD‐suspected population.

Results

Molecular diagnosis was established in 27% (1259 cases; 95% CI, 26–29%) of the patients with major contributing genes to LGMD phenotypes being: CAPN3(17%), DYSF(16%), FKRP(9%) and ANO5(7%). We observed an increased prevalence of genetically confirmed late‐onset Pompe disease, DNAJB6‐associated LGMD subtype1E and CAPN3‐associated autosomal‐dominant LGMDs. Interestingly, we identified a high prevalence of patients with pathogenic variants in more than one LGMD gene suggesting possible synergistic heterozygosity/digenic/multigenic contribution to disease presentation/progression that needs consideration as a part of diagnostic modality.

Interpretation

Overall, this study has improved our understanding of the relative prevalence of different LGMD subtypes, their respective genetic etiology, and the changing paradigm of their inheritance modes and novel mechanisms that will allow for improved timely treatment, management, and enrolment of molecularly diagnosed individuals in clinical trials.

Functional Annotation of Animal Genomes (FAANG): Current Achievements and Roadmap

Functional annotation of genomes is a prerequisite for contemporary basic and applied genomic research, yet farmed animal genomics is deficient in such annotation. To address this, the FAANG (Functional Annotation of Animal Genomes) Consortium is producing genome-wide data sets on RNA expression, DNA methylation, and chromatin modification, as well as chromatin accessibility and interactions. In addition to informing our understanding of genome function, including comparative approaches to elucidate constrained sequence or epigenetic elements, these annotation maps will improve the precision and sensitivity of genomic selection for animal improvement. A scientific community-driven effort has already created a coordinated data collection and analysis enterprise crucial for the success of this global effort. Although it is early in this continuing process, functional data have already been produced and application to genetic improvement reported. The functional annotation delivered by the FAANG initiative will add value and utility to the greatly improved genome sequences being established for domesticated animal species.

Functional Assays Are Essential for Interpretation of Missense Variants Associated with Variable Expressivity

Missense DNA variants have variable effects upon protein function. Consequently, interpreting their pathogenicity is challenging, especially when they are associated with disease variability. To determine the degree to which functional assays inform interpretation, we analyzed 48 CFTR missense variants associated with variable expressivity of cystic fibrosis (CF). We assessed function in a native isogenic context by evaluating CFTR mutants that were stably expressed in the genome of a human airway cell line devoid of endogenous CFTR expression. 21 of 29 variants associated with full expressivity of the CF phenotype generated <10% wild-type CFTR (WT-CFTR) function, a conservative threshold for the development of life-limiting CF lung disease, and five variants had moderately decreased function (10% to ∼25% WT-CFTR). The remaining three variants in this group unexpectedly had >25% WT-CFTR function; two were higher than 75% WT-CFTR. As expected, 14 of 19 variants associated with partial expressivity of CF had >25% WT-CFTR function; however, four had minimal to no effect on CFTR function (>75% WT-CFTR). Thus, 6 of 48 (13%) missense variants believed to be disease causing did not alter CFTR function. Functional studies substantially refined pathogenicity assignment with expert annotation and criteria from the American College of Medical Genetics and Genomics and Association for Molecular Pathology. However, four algorithms (CADD, REVEL, SIFT, and PolyPhen-2) could not differentiate between variants that caused severe, moderate, or minimal reduction in function. In the setting of variable expressivity, these results indicate that functional assays are essential for accurate interpretation of missense variants and that current prediction tools should be used with caution.

Small-Molecule Screening for Genetic Diseases

The genetic determinants of many diseases, including monogenic diseases and cancers, have been identified; nevertheless, targeted therapy remains elusive for most. High-throughput screening (HTS) of small molecules, including high-content analysis (HCA), has been an important technology for the discovery of molecular tools and new therapeutics. HTS can be based on modulation of a known disease target (called reverse chemical genetics) or modulation of a disease-associated mechanism or phenotype (forward chemical genetics). Prominent target-based successes include modulators of transthyretin, used to treat transthyretin amyloidoses, and the BCR-ABL kinase inhibitor Gleevec, used to treat chronic myelogenous leukemia. Phenotypic screening successes include modulators of cystic fibrosis transmembrane conductance regulator, splicing correctors for spinal muscular atrophy, and histone deacetylase inhibitors for cancer. Synthetic lethal screening, in which chemotherapeutics are screened for efficacy against specific genetic backgrounds, is a promising approach that merges phenotype and target. In this article, we introduce HTS technology and highlight its contributions to the discovery of drugs and probes for monogenic diseases and cancer.

Inferring the effect of genomic variation in the new era of genomics

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene-variant-disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next-generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as "synergistic heterozygosity," digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large-scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.

Short-term costs of integrating whole-genome sequencing into primary care and cardiology settings: a pilot randomized trial

Purpose

Great uncertainty exists about the costs associated with whole genome sequencing (WGS).

Methods

One hundred cardiology patients with cardiomyopathy diagnoses, and 100 ostensibly healthy primary care patients were randomized to receive a family history report alone or with a WGS report. Cardiology patients also reviewed prior genetic test results. WGS costs were estimated by tracking resource use and staff time. Downstream costs were estimated by identifying services in administrative data, medical records, and patient surveys for 6 months.

Results

The incremental cost per patient of WGS testing was $5,098 in cardiology settings and $5,073 in primary care settings compared to family history alone. Mean six month downstream costs did not differ statistically between the control and WGS arms in either setting (cardiology: difference = −$1,560, 95%CI −$7,558 to $3,866, p=0.36; primary care: difference = $681, 95%CI −$884 to $2,171, p=0.70). Scenario analyses showed the cost reduction of omitting or limiting the types of secondary findings was less than $69 and $182 per patient in cardiology and primary care, respectively.

Conclusion

Short-term costs of WGS were driven by the costs of sequencing and interpretation rather than downstream healthcare. Disclosing additional types of secondary findings has a limited cost impact following disclosure.

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.

Classifying nitrilases as aliphatic and aromatic using machine learning technique

ProCos (Protein Composition Server, script version), one of the machine learning techniques, was used to classify nitrilases as aliphatic and aromatic nitrilases. Some important feature vectors were used to train the algorithm, which included pseudo-amino acid composition (PAAC) and five-factor solution score (5FSS). This clearly differentiated into two groups of nitrilases, i.e., aliphatic and aromatic, achieving maximum sensitivity of 100.00%, specificity of 90.00%, accuracy of 95.00% and Mathew Correlation Coefficient (MCC) of about 0.90 for the pseudo-amino acid composition. On the other hand, five-factor solution score achieved a sensitivity of 96.00%, specificity of 84.00%, accuracy of 90.00% and Mathew Correlation Coefficient (MCC) of about 0.81. The total count of aliphatic amino acids, Ala (A), Gly (G), Leu (L), Ile (I), Val (V), Met (M) and Pro (P), was found to be higher, i.e., 42.7 in case of aliphatic nitrilases, whereas it was 40.1 in aromatic nitrilases. On the other hand, aromatic amino acids, Tyr (Y), Trp (W), His (H) and Phe (F) number, were found to be higher, i.e., 12.7 in aromatic nitrilases as compared to aliphatic nitrilases which was 10.7. This approach will help in predicting a nitrilase as aromatic or aliphatic nitrilase based on its amino acid sequence. Access to the scripts can be done logging onto GitHub using keyword 'Nitrilase' or 'https://github.com/rover2380/Nitrilase.git'.