Project description:Next generation sequencing is currently a cornerstone of genetic testing in routine diagnostics, allowing for the detection of sequence variants with so far unprecedented large scale, mainly in genetically heterogenous diseases, such as neurological disorders. It is a fast-moving field, where new wet enrichment protocols and bioinformatics tools are constantly being developed to overcome initial limitations. Despite the as yet undiscussed advantages, however, there are still some challenges in data analysis and the interpretation of variants. In this review, we address the current state of next generation sequencing diagnostic testing for inherited human disorders, particularly giving an overview of the available high-throughput sequencing approaches; including targeted, whole-exome and whole-genome sequencing; and discussing the main critical aspects of the bioinformatic process, from raw data analysis to molecular diagnosis.
Project description:Genetic risk factors that underlie many rare and common neurological diseases remain poorly understood because of the multi-factorial and heterogeneous nature of these disorders. Although genome-wide association studies (GWAS) have successfully uncovered numerous susceptibility genes for these diseases, odds ratios associated with risk alleles are generally low and account for only a small proportion of estimated heritability. These results implicated that there are rare (present in <5% of the population) but not causative variants exist in the pathogenesis of these diseases, which usually have large effect size and cannot be captured by GWAS. With the decreasing cost of next-generation sequencing (NGS) technologies, whole-genome sequencing (WGS) and whole-exome sequencing (WES) have enabled the rapid identification of rare variants with large effect size, which made huge progress in understanding the basis of many Mendelian neurological conditions as well as complex neurological diseases. In this article, recent NGS-based studies that aimed to investigate genetic causes for neurological diseases, including Alzheimer's disease, Parkinson's disease, epilepsy, multiple sclerosis, stroke, amyotrophic lateral sclerosis and spinocerebellar ataxias, have been reviewed. In addition, we also discuss the future directions of NGS applications in this article.
Project description:UnlabelledART is a set of simulation tools that generate synthetic next-generation sequencing reads. This functionality is essential for testing and benchmarking tools for next-generation sequencing data analysis including read alignment, de novo assembly and genetic variation discovery. ART generates simulated sequencing reads by emulating the sequencing process with built-in, technology-specific read error models and base quality value profiles parameterized empirically in large sequencing datasets. We currently support all three major commercial next-generation sequencing platforms: Roche's 454, Illumina's Solexa and Applied Biosystems' SOLiD. ART also allows the flexibility to use customized read error model parameters and quality profiles.AvailabilityBoth source and binary software packages are available at http://www.niehs.nih.gov/research/resources/software/art.
Project description:BackgroundGenetic screening in families with high risk to develop colorectal cancer (CRC) prevents incurable disease and permits personalized therapeutic and follow-up strategies. The advancement of next-generation sequencing (NGS) technologies has revolutionized the throughput of DNA sequencing.MethodsA series of 16 probands for either familial adenomatous polyposis (FAP; 8 cases) or hereditary nonpolyposis colorectal cancer (HNPCC; 8 cases) were investigated for intragenic mutations in five CRC familial syndromes-associated genes (APC, MUTYH, MLH1, MSH2, MSH6) applying both a custom multigene Ion AmpliSeq NGS panel and conventional Sanger sequencing.ResultsFourteen pathogenic variants were detected in 13/16 FAP/HNPCC probands (81.3 %); one FAP proband presented two co-existing pathogenic variants, one in APC and one in MUTYH. Thirteen of these 14 pathogenic variants were detected by both NGS and Sanger, while one MSH2 mutation (L280FfsX3) was identified only by Sanger sequencing. This is due to a limitation of the NGS approach in resolving sequences close or within homopolymeric stretches of DNA. To evaluate the performance of our NGS custom panel we assessed its capability to resolve the DNA sequences corresponding to 2225 pathogenic variants reported in the COSMIC database for APC, MUTYH, MLH1, MSH2, MSH6. Our NGS custom panel resolves the sequences where 2108 (94.7 %) of these variants occur. The remaining 117 mutations reside inside or in close proximity to homopolymer stretches; of these 27 (1.2 %) are imprecisely identified by the software but can be resolved by visual inspection of the region, while the remaining 90 variants (4.0 %) are blind spots. In summary, our custom panel would miss 4 % (90/2225) of pathogenic variants that would need a small set of Sanger sequencing reactions to be solved.ConclusionsThe multiplex NGS approach has the advantage of analyzing multiple genes in multiple samples simultaneously, requiring only a reduced number of Sanger sequences to resolve homopolymeric DNA regions not adequately assessed by NGS. The implementation of NGS approaches in routine diagnostics of familial CRC is cost-effective and significantly reduces diagnostic turnaround times.
Project description:PurposePreimplantation genetic testing for monogenic disorders (PGT-M) allows early diagnosis in embryos conceived in vitro. PGT-M helps to prevent known genetic disorders in affected families and ensures that pathogenic variants in the male or female partner are not passed on to offspring. The trend in genetic testing of embryos is to provide a comprehensive platform that enables robust and reliable testing for the causal pathogenic variant(s), as well as chromosomal abnormalities that commonly occur in embryos. In this study, we describe PGT protocol that allows direct mutation testing, haplotyping, and aneuploidy screening.MethodsDescribed PGT protocol called OneGene PGT allows direct mutation testing, haplotyping, and aneuploidy screening using next-generation sequencing (NGS). Whole genome amplification product is combined with multiplex PCR used for SNP enrichment. Dedicated bioinformatic tool enables mapping, genotype calling, and haplotyping of informative SNP markers. A commercial software was used for aneuploidy calling.ResultsOneGenePGT has been implemented for seven of the most common monogenic disorders, representing approximately 30% of all PGT-M indications at our IVF centre. The technique has been thoroughly validated, focusing on direct pathogenic variant testing, haplotype identification, and chromosome abnormality detection. Validation results show full concordance with Sanger sequencing and karyomapping, which were used as reference methods.ConclusionOneGene PGT is a comprehensive, robust, and cost-effective method that can be established for any gene of interest. The technique is particularly suitable for common monogenic diseases, which can be performed based on a universal laboratory protocol without the need for set-up or pre-testing.
Project description:Next generation sequencing (NGS) technologies offer the possibility to map entire genomes at affordable costs. This brings the genetic testing procedure to a higher level of complexity. The positive aspect is the ease to cope with the complex diagnosis of genetically heterogeneous disorders and to identify novel disease genes. Worries arise from the management of too many DNA variations with unpredictable meaning and incidental findings that can cause ethical and clinical dilemmas. The technology of enrichment makes possible to focus the sequencing to the exome or to a more specific DNA target. This is being used to provide insights into the genetics underlying Mendelian traits involved in myopathies and to set up cost-effective diagnostic tests. This huge potential of the NGS applications makes likely that these will soon become the first approach in genetic diagnostic laboratories.
Project description:Aims/hypothesisCurrent genetic tests for diagnosing monogenic diabetes rely on selection of the appropriate gene for analysis according to the patient's phenotype. Next-generation sequencing enables the simultaneous analysis of multiple genes in a single test. Our aim was to develop a targeted next-generation sequencing assay to detect mutations in all known MODY and neonatal diabetes genes.MethodsWe selected 29 genes in which mutations have been reported to cause neonatal diabetes, MODY, maternally inherited diabetes and deafness (MIDD) or familial partial lipodystrophy (FPLD). An exon-capture assay was designed to include coding regions and splice sites. A total of 114 patient samples were tested--32 with known mutations and 82 previously tested for MODY (n = 33) or neonatal diabetes (n = 49) but in whom a mutation had not been found. Sequence data were analysed for the presence of base substitutions, small insertions or deletions (indels) and exonic deletions or duplications.ResultsIn the 32 positive controls we detected all previously identified variants (34 mutations and 36 polymorphisms), including 55 base substitutions, ten small insertions or deletions and five partial/whole gene deletions/duplications. Previously unidentified mutations were found in five patients with MODY (15%) and nine with neonatal diabetes (18%). Most of these patients (12/14) had mutations in genes that had not previously been tested.Conclusions/interpretationOur novel targeted next-generation sequencing assay provides a highly sensitive method for simultaneous analysis of all monogenic diabetes genes. This single test can detect mutations previously identified by Sanger sequencing or multiplex ligation-dependent probe amplification dosage analysis. The increased number of genes tested led to a higher mutation detection rate.
Project description:Next-generation sequencing technologies allow for rapid and inexpensive large-scale genomic analysis, creating unprecedented opportunities to integrate genomic data into the clinical diagnosis and management of neurological disorders. However, the scale and complexity of these data make them difficult to interpret and require the use of sophisticated bioinformatics applied to extensive datasets, including whole exome and genome sequences. Detailed analysis of genetic data has shown that accurate phenotype information is essential for correct interpretation of genetic variants and might necessitate re-evaluation of the patient in some cases. A multidisciplinary approach that incorporates bioinformatics, clinical evaluation, and human genetics can help to address these challenges. However, despite numerous studies that show the efficacy of next-generation sequencing in establishing molecular diagnoses, pathogenic mutations are generally identified in fewer than half of all patients with genetic neurological disorders, exposing considerable gaps in the understanding of the human genome and providing opportunities to focus research on improving the usefulness of genomics in clinical practice. Looking forward, the emergence of precision health in neurological care will increasingly apply genomic data analysis to pharmacogenetics, preventive medicine, and patient-targeted therapies.
Project description:PurposeTo develop a comprehensive genetic test for female and male infertility in support of medical decisions during assisted reproductive technology (ART) protocols.MethodsWe developed a next-generation sequencing (NGS) gene panel consisting of 87 genes including promoters, 5' and 3' untranslated regions, exons, and selected introns. In addition, sex chromosome aneuploidies and Y chromosome microdeletions were analyzed concomitantly using the same panel.ResultsThe NGS panel was analytically validated by retrospective analysis of 118 genomic DNA samples with known variants in loci representative of female and male infertility. Our results showed analytical accuracy of > 99%, with > 98% sensitivity for single-nucleotide variants (SNVs) and > 91% sensitivity for insertions/deletions (indels). Clinical sensitivity was assessed with samples containing variants representative of male and female infertility, and it was 100% for SNVs/indels, CFTR IVS8-5T variants, sex chromosome aneuploidies, and copy number variants (CNVs) and > 93% for Y chromosome microdeletions. Cost analysis shows potential savings when comparing this single NGS assay with the standard approach, which includes multiple assays.ConclusionsA single, comprehensive, NGS panel can simplify the ordering process for healthcare providers, reduce turnaround time, and lower the overall cost of testing for genetic assessment of infertility in females and males, while maintaining accuracy.
Project description:ObjectiveData from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.ResultsPrecise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.