Regulatory variations in the era of next-generation sequencing: Implications for clinical molecular diagnostics

Application of Next-Generation Sequencing in Neurodegenerative Diseases: Opportunities and Challenges

Genetic factors (gene mutations) lead to various rare and prevalent neurological diseases. Identification of underlying mutations in neurodegenerative diseases is of paramount importance due to the heterogeneous nature of the genome and different clinical manifestations. An early and accurate molecular diagnosis are cardinal for neurodegenerative patients to undergo proper therapeutic regimens. The next-generation sequencing (NGS) method examines up to millions of sequences at a time. As a result, the rare molecular diagnoses, previously presented with "unknown causes", are now possible in a short time. This method generates a large amount of data that can be utilized in patient management. Since each person has a unique genome, the NGS has transformed diagnostic and therapeutic strategies into sequencing and individual genomic mapping. However, this method has disadvantages like other diagnostic methods. Therefore, in this review, we aimed to briefly summarize the NGS method and correlated studies to unravel the genetic causes of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, epilepsy, and MS. Finally, we discuss the NGS challenges and opportunities in neurodegenerative diseases.

Identification of putative genetic modifying factors that influence the development of Papillon-Lefévre or Haim-Munk syndrome phenotypes

BACKGROUND

Papillon-Lefévre syndrome (PLS; OMIM 245000) and Haim-Munk syndrome (HMS; OMIM 245010), which are both characterized by palmoplantar hyperkeratosis and periodontitis, are phenotypic variants of the same disease caused by mutations of the cathepsin C (CTSC) gene.

AIM

To identify putative genetic modifying factors responsible for the differential development of the PLS or HMS phenotypes, we investigated two Hungarian patients with different phenotypic variants (PLS and HMS) but carrying the same homozygous nonsense CTSC mutation (c.748C/T; p.Arg250X).

METHODS

To gain insights into phenotype-modifying associations, whole exome sequencing (WES) was performed for both patients, and the results were compared to identify potentially relevant genetic modifying factors.

RESULTS

WES revealed two putative phenotype-modifying variants: (i) a missense mutation (rs34608771) of the SH2 domain containing 4A (SH2D4A) gene encoding an adaptor protein involved in intracellular signalling of cystatin F, a known inhibitor of the cathepsin protein, and (ii) a missense variant (rs55695858) of the odorant binding protein 2A (OBP2A) gene, influencing the function of the cathepsin protein through the glycosyltransferase 6 domain containing 1 (GLT6D1) protein.

CONCLUSION

Our study contributes to the accumulating evidence supporting the clinical importance of phenotype-modifying genetic factors, which have high potential to aid the elucidation of genotype-phenotype correlations and disease prognosis.

Next generation sequencing in pediatric hepatology and liver transplantation

Next generation sequencing (NGS) has revolutionized the analysis of human genetic variations, offering a highly cost-effective way to diagnose monogenic diseases (MDs). Because nearly half of the children with chronic liver disorders have a genetic cause and approximately 20% of pediatric liver transplantations are performed in children with MDs, NGS offers the opportunity to significantly improve the diagnostic yield in this field. Among the NGS strategies, the use of targeted gene panels has proven useful to rapidly and reliably confirm a clinical suspicion, whereas the whole exome sequencing (WES) with variants filtering has been adopted to assist the diagnostic workup in unclear clinical scenarios. WES is powerful but challenging because it detects a great number of variants of unknown significance that can be misinterpreted and lead to an incorrect diagnosis. In pediatric hepatology, targeted NGS can be very valuable to discriminate neonatal/infantile cholestatic disorders, disclose genetic causes of acute liver failure, and diagnose the subtype of inborn errors of metabolism presenting with a similar phenotype (such as glycogen storage disorders, mitochondrial cytopathies, or nonalcoholic fatty liver disease). The inclusion of NGS in diagnostic processes will lead to a paradigm shift in medicine, changing our approach to the patient as well as our understanding of factors affecting genotype-phenotype match. In this review, we discuss the opportunities and the challenges offered nowadays by NGS, and we propose a novel algorithm for cholestasis of infancy adopted in our center, including targeted NGS as a pivotal tool for the diagnosis of liver-based MDs. Liver Transplantation 24 282-293 2018 AASLD.

Evaluating tools for transcription factor binding site prediction

Background

Binding of transcription factors to transcription factor binding sites (TFBSs) is key to the mediation of transcriptional regulation. Information on experimentally validated functional TFBSs is limited and consequently there is a need for accurate prediction of TFBSs for gene annotation and in applications such as evaluating the effects of single nucleotide variations in causing disease. TFBSs are generally recognized by scanning a position weight matrix (PWM) against DNA using one of a number of available computer programs. Thus we set out to evaluate the best tools that can be used locally (and are therefore suitable for large-scale analyses) for creating PWMs from high-throughput ChIP-Seq data and for scanning them against DNA.

Results

We evaluated a set of de novo motif discovery tools that could be downloaded and installed locally using ENCODE-ChIP-Seq data and showed that rGADEM was the best-performing tool. TFBS prediction tools used to scan PWMs against DNA fall into two classes — those that predict individual TFBSs and those that identify clusters. Our evaluation showed that FIMO and MCAST performed best respectively.

Conclusions

Selection of the best-performing tools for generating PWMs from ChIP-Seq data and for scanning PWMs against DNA has the potential to improve prediction of precise transcription factor binding sites within regions identified by ChIP-Seq experiments for gene finding, understanding regulation and in evaluating the effects of single nucleotide variations in causing disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1298-9) contains supplementary material, which is available to authorized users.

A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease

The interpretation of non-coding variants still constitutes a major challenge in the application of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and other small non-coding variants. Here we present Genomiser, an analysis framework that is able not only to score the relevance of variation in the non-coding genome, but also to associate regulatory variants to specific Mendelian diseases. Genomiser scores variants through either existing methods such as CADD or a bespoke machine learning method and combines these with allele frequency, regulatory sequences, chromosomal topological domains, and phenotypic relevance to discover variants associated to specific Mendelian disorders. Overall, Genomiser is able to identify causal regulatory variants as the top candidate in 77% of simulated whole genomes, allowing effective detection and discovery of regulatory variants in Mendelian disease.

Axons to Exons: the Molecular Diagnosis of Rare Neurological Diseases by Next-Generation Sequencing

Neurological disorders secondary to single gene mutations are an extremely heterogeneous group of diseases, individually rare, and often associated with progressive and severe disability. Given the degree of both clinical and genetic heterogeneity, next-generation sequencing (NGS) has become an important diagnostic tool. Multi-gene panel testing based on NGS is now prominently used, while whole-exome sequencing and whole-genome sequencing are emerging to facilitate the molecular diagnosis for many genetic neurological diseases. Although single-gene testing remains an important first tier test for disorders with clear phenotype-genotype correlation, NGS provides an expanding unbiased approach to identify rare mutations in genes known to be associated with genetically heterogeneous diseases, and those not initially considered by the clinician due to rarity or atypical clinical presentation. Given the decreasing costs and relatively rapid time to results, NGS-based assessment is quickly becoming a standard-of-care test for patients with genetic neurological diseases.

The potential role of the sodium iodide symporter gene polymorphism in the development of differentiated thyroid cancer

The sodium iodide symporter (NIS) (solute carrier family 5; SLC5A), mediates the active transport of iodine anion (I(-)) into thyroid follicular cells to facilitate thyroid hormone biosynthesis. Considering its fundamental role in thyroid function, our objective in this study is to explore its potential involvement in the pathogenesis of differentiated thyroid cancer (DTC). Following a preliminary sequencing of the gene in a representative sample of the general population, five variants, (1) rs45602038, (2) rs4808708, (3) rs4808709, (4) rs7250346 and (5) rs12327843, were selected for a larger population-based association study consisting of 507 cases and 597 controls, of which only the rs45602038_TT [Odds ratio (95% confidence interval)=1.90 (1.26-2.88); p=0.002] was associated with disease following adjustment for other confounders using the multivariate analysis. Furthermore, a 5-mer haplotype CGAGT constructed from the five studied SNPs conferred a significant risk (χ(2)=10.98; p=0.0009) for DTC. This association trickled down through shorter derivatives, with the 4-mer haplotype CGAG (χ(2)=13.25; p=0.0003) displaying the most significant association and the 3-mer GAG (χ(2)=11.80; p=0.0006) being equally strongly linked to the disease. Comparison of the flanking derivatives of the primary 5-mer haplotype also indicated that the 3-mer CGA (χ(2)=4.04; p=0.045) constructed from SNP block 1-3 was a lot weaker than that of the AGT (χ(2)=6.73; p=0.0095) constructed from the blocks 3-5 from the other end of the gene. Put together, these data implicate the three nucleotide changes at the rs4808708, rs4808709 and rs7250346 loci (blocks 2-4) as the core for this relationship.

Next-generation sequencing in childhood disorders

Genetics has been revolutionised by recent technologies. The latest addition to these advances is next-generation sequencing, which is set to transform clinical diagnostics in every branch of medicine. In the research arena this has already been instrumental in identifying hundreds of novel genetic syndromes, making a molecular diagnosis possible for the first time in numerous refractory cases. However, the pace of change has left many clinicians bewildered by new terminology and the implications of next-generation sequencing for their clinical practice. The rapid developments have also left many diagnostic laboratories struggling to implement these new technologies with limited resources. This review explains the basic concepts of next-generation sequencing, gives examples of its role in clinically applied research and examines the challenges of its introduction into clinical practice.

Application of high-throughput sequencing for studying genomic variations in congenital heart disease

Congenital heart diseases (CHD) represent the most common birth defect in human. The majority of cases are caused by a combination of complex genetic alterations and environmental influences. In the past, many disease-causing mutations have been identified; however, there is still a large proportion of cardiac malformations with unknown precise origin. High-throughput sequencing technologies established during the last years offer novel opportunities to further study the genetic background underlying the disease. In this review, we provide a roadmap for designing and analyzing high-throughput sequencing studies focused on CHD, but also with general applicability to other complex diseases. The three main next-generation sequencing (NGS) platforms including their particular advantages and disadvantages are presented. To identify potentially disease-related genomic variations and genes, different filtering steps and gene prioritization strategies are discussed. In addition, available control datasets based on NGS are summarized. Finally, we provide an overview of current studies already using NGS technologies and showing that these techniques will help to further unravel the complex genetics underlying CHD.

Ultra-rare mutation in long-range enhancer predisposes to thyroid carcinoma with high penetrance

Thyroid cancer shows high heritability but causative genes remain largely unknown. According to a common hypothesis the genetic predisposition to thyroid cancer is highly heterogeneous; being in part due to many different rare alleles. Here we used linkage analysis and targeted deep sequencing to detect a novel single-nucleotide mutation in chromosome 4q32 (4q32A>C) in a large pedigree displaying non-medullary thyroid carcinoma (NMTC). This mutation is generally ultra-rare; it was not found in 38 NMTC families, in 2676 sporadic NMTC cases or 2470 controls. The mutation is located in a long-range enhancer element whose ability to bind the transcription factors POU2F and YY1 is significantly impaired, with decreased activity in the presence of the C- allele compared with the wild type A-allele. An enhancer RNA (eRNA) is transcribed in thyroid tissue from this region and is greatly downregulated in NMTC tumors. We suggest that this is an example of an ultra-rare mutation predisposing to thyroid cancer with high penetrance.