ABSTRACT
X-linked retinitis pigmentosa (XLRP) is characterized by progressive vision loss leading to legal blindness in males and a broad severity spectrum in carrier females. Pathogenic alterations of the retinitis pigmentosa GTPase regulator gene (RPGR) are responsible for over 70% of XLRP cases. In the retina, the RPGRORF15 transcript includes a terminal exon, called ORF15, that is altered in the large majority of RPGR-XLRP cases. Unfortunately, due to its highly repetitive sequence, ORF15 represents a considerable challenge in terms of sequencing for molecular diagnostic laboratories. However, in a recent preliminary work Yahya et al. reported a long-read sequencing approach seeming promising. Here, the aim of the study was to validate and integrate this new sequencing strategy in a routine screening workflow. For that purpose, we performed a masked test on 52 genomic DNA samples from male and female individuals carrying 32 different pathogenic ORF15 variations including 20 located in the highly repetitive region of the exon. For the latter, we have obtained a detection rate of 80-85% in males and 60-80% in females after bioinformatic analyses. These numbers raised to 100% for both status after adding a complementary visual inspection of ORF15 long-reads. In accordance with these results, and considering the frequency of ORF15 pathogenic variations in XLRP, we suggest that a long-read screening of ORF15 should be systematically considered before any other sequencing approach in subjects with a diagnosis compatible with XLRP.
ABSTRACT
Store-operated calcium entry (SOCE) plays a crucial role in maintaining cellular calcium homeostasis. This mechanism involves proteins, such as stromal interaction molecule 1 (STIM1) and ORAI1. Mutations in the genes encoding these proteins, especially STIM1, can lead to various diseases, including CRAC channelopathies associated with severe combined immunodeficiency. Herein, we describe a novel homozygous mutation, NM_003156 c.792-3C > G, in STIM1 in a patient with a clinical profile of CRAC channelopathy, including immune system deficiencies and muscle weakness. Functional analyses revealed three distinct spliced forms in the patient cells: wild-type, exon 7 skipping, and intronic retention. Calcium influx analysis revealed impaired SOCE in the patient cells, indicating a loss of STIM1 function. We developed an antisense oligonucleotide treatment that improves STIM1 splicing and highlighted its potential as a therapeutic approach. Our findings provide insights into the complex effects of STIM1 mutations and shed light on the multifaceted clinical presentation of the patient.
Subject(s)
Calcium , Mutation , Neoplasm Proteins , Stromal Interaction Molecule 1 , Humans , Stromal Interaction Molecule 1/genetics , Stromal Interaction Molecule 1/metabolism , Neoplasm Proteins/genetics , Neoplasm Proteins/metabolism , Calcium/metabolism , Channelopathies/genetics , Male , Calcium Release Activated Calcium Channels/genetics , Calcium Release Activated Calcium Channels/metabolism , Female , Severe Combined Immunodeficiency/genetics , ORAI1 Protein/genetics , ORAI1 Protein/metabolismABSTRACT
Alpha-tubulin 4A encoding gene (TUBA4A) has been associated with familial amyotrophic lateral sclerosis (fALS) and fronto-temporal dementia (FTD), based on identification of likely pathogenic variants in patients from distinct ALS and FTD cohorts. By screening a multicentric French cohort of 448 unrelated probands presenting with cerebellar ataxia, we identified ultra-rare TUBA4A missense variants, all being absent from public databases and predicted pathogenic by multiple in-silico tools. In addition, gene burden analyses in the 100,000 genomes project (100KGP) showed enrichment of TUBA4A rare variants in the inherited ataxia group compared to controls (OR: 57.0847 [10.2- 576.7]; p = 4.02 x10-07). Altogether, we report 12 patients presenting with spasticity and/or cerebellar ataxia and harboring a predicted pathogenic TUBA4A missense mutation, including 5 confirmed de novo cases and a mutation previously reported in a large family presenting with spastic ataxia. Cultured fibroblasts from 3 patients harboring distinct TUBA4A missense showed significant alterations in microtubule organisation and dynamics, providing insight of TUBA4A variants pathogenicity. Our data confirm the identification of a hereditary spastic ataxia disease gene with variable age of onset, expanding the clinical spectrum of TUBA4A associated phenotypes.
ABSTRACT
Deposition of the exon junction complex (EJC) upstream of exon-exon junctions helps maintain transcriptome integrity by preventing spurious re-splicing events in already spliced mRNAs. Here we investigate the importance of EJC for the correct splicing of the 2.2-megabase-long human DMD pre-mRNA, which encodes dystrophin, an essential protein involved in cytoskeletal organization and cell signaling. Using targeted RNA-seq, we show that knock-down of the eIF4A3 and Y14 core components of EJC in a human muscle cell line causes an accumulation of mis-splicing events clustered towards the 3' end of the DMD transcript (Dp427m). This deregulation is conserved in the short Dp71 isoform expressed ubiquitously except in adult skeletal muscle and is rescued with wild-type eIF4A3 and Y14 proteins but not with an EJC assembly-defective mutant eIF4A3. MLN51 protein and EJC-associated ASAP/PSAP complexes independently modulate the inclusion of the regulated exons 71 and 78. Our data confirm the protective role of EJC in maintaining splicing fidelity, which in the DMD gene is necessary to preserve the function of the critical C-terminal protein-protein interaction domain of dystrophin present in all tissue-specific isoforms. Given the role of the EJC in maintaining the integrity of dystrophin, we asked whether the EJC could also be involved in the regulation of a mechanism as complex as skeletal muscle differentiation. We found that eIF4A3 knockdown impairs myogenic differentiation by blocking myotube formation. Collectively, our data provide new insights into the functional roles of EJC in human skeletal muscle.
Subject(s)
Dystrophin , RNA Splicing , Humans , Cell Nucleus/metabolism , Dystrophin/genetics , Dystrophin/metabolism , Exons/genetics , RNA Splicing/genetics , RNA, Messenger/metabolismABSTRACT
BACKGROUND: Titinopathies are caused by mutations in the titin gene (TTN). Titin is the largest known human protein; its gene has the longest coding phase with 364 exons. Titinopathies are very complex neuromuscular pathologies due to the variable age of onset of symptoms, the great diversity of pathological and muscular impairment patterns (cardiac, skeletal muscle or mixed) and both autosomal dominant and recessive modes of transmission. Until now, only few CNVs in TTN have been reported without clear genotype-phenotype associations. METHODS: Our study includes eight families with dominant titinopathies. We performed next-generation sequencing or comparative genomic hybridisation array analyses and found CNVs in the TTN gene. We characterised these CNVs by RNA sequencing (RNAseq) analyses in six patients' muscles and performed genotype-phenotype inheritance association study by combining the clinical and biological data of these eight families. RESULTS: Seven deletion-type CNVs in the TTN gene were identified among these families. Genotype and RNAseq results showed that five deletions do not alter the reading frame and one is out-of-reading frame. The main phenotype identified was distal myopathy associated with contractures. The analysis of morphological, clinical and genetic data and imaging let us draw new genotype-phenotype associations of titinopathies. CONCLUSION: Identifying TTN CNVs will further increase diagnostic sensitivity in these complex neuromuscular pathologies. Our cohort of patients enabled us to identify new deletion-type CNVs in the TTN gene, with unexpected autosomal dominant transmission. This is valuable in establishing new genotype-phenotype associations of titinopathies, mainly distal myopathy in most of the patients.
Subject(s)
Distal Myopathies , Humans , Connectin/genetics , Distal Myopathies/genetics , DNA Copy Number Variations/genetics , Muscle, Skeletal/pathology , Mutation/genetics , PhenotypeABSTRACT
The transition from targeted to exome or genome sequencing in clinical contexts requires quality standards, such as targeted sequencing, in order to be fully adopted. However, no clear recommendations or methodology have emerged for evaluating this technological evolution. We developed a structured method based on four run-specific sequencing metrics and seven sample-specific sequencing metrics for evaluating the performance of exome sequencing strategies to replace targeted strategies. The indicators include quality metrics and coverage performance on gene panels and OMIM morbid genes. We applied this general strategy to three different exome kits and compared them with a myopathy-targeted sequencing method. After having achieved 80 million reads, all-tested exome kits generated data suitable for clinical diagnosis. However, significant differences in the coverage and PCR duplicates were observed between the kits. These are two main criteria to consider for the initial implementation with high-quality assurance. This study aims to assist molecular diagnostic laboratories in adopting and evaluating exome sequencing kits in a diagnostic context compared to the strategy used previously. A similar strategy could be used to implement whole-genome sequencing for diagnostic purposes.
Subject(s)
High-Throughput Nucleotide Sequencing , Laboratories, Clinical , Exome Sequencing , High-Throughput Nucleotide Sequencing/methods , Whole Genome Sequencing , Base Sequence , Sequence Analysis, DNA/methodsABSTRACT
SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).
Subject(s)
Algorithms , RNA Splicing , Humans , RNA Splicing/geneticsABSTRACT
Copy-number variations (CNVs) are an essential component of genetic variation distributed across large parts of the human genome. CNV detection from next-generation sequencing data and artificial intelligence algorithms have progressed in recent years. However, only a few tools have taken advantage of machine-learning algorithms for CNV detection, and none propose using artificial intelligence to automatically detect probable CNV-positive samples. The most developed approach is to use a reference or normal dataset to compare with the samples of interest, and it is well known that selecting appropriate normal samples represents a challenging task that dramatically influences the precision of results in all CNV-detecting tools. With careful consideration of these issues, we propose here ifCNV, a new software based on isolation forests that creates its own reference, available in R and python with customizable parameters. ifCNV combines artificial intelligence using two isolation forests and a comprehensive scoring method to faithfully detect CNVs among various samples. It was validated using targeted next-generation sequencing (NGS) datasets from diverse origins (capture and amplicon, germline and somatic), and it exhibits high sensitivity, specificity, and accuracy. ifCNV is a publicly available open-source software (https://github.com/SimCab-CHU/ifCNV) that allows the detection of CNVs in many clinical situations.
ABSTRACT
Titin protein is responsible for muscle elasticity. The TTN gene, composed of 364 exons, is subjected to extensive alternative splicing and leads to different isoforms expressed in skeletal and cardiac muscle. Variants in TTN are responsible for myopathies with a wide phenotypic spectrum and autosomal dominant or recessive transmission. The I-band coding domain, highly subject to alternative splicing, contains a three-zone block of repeated sequences with 99% homology. Sequencing and localization of variants in these areas are complex when using short-reads sequencing, a second-generation sequencing technique. We have implemented a protocol based on the third-generation sequencing technology (long-reads sequencing). This new method allows us to localize variants in these repeated areas to improve the diagnosis of TTN-related myopathies and offer the analysis of relatives in postnatal or in prenatal screening.
Subject(s)
Muscular Diseases , Alternative Splicing/genetics , Connectin/genetics , Exons/genetics , Humans , Muscular Diseases/genetics , Protein Isoforms/geneticsABSTRACT
MobiDetails is an expert tool, online application which gathers useful data for the interpretation of DNA variants in the context of molecular diagnosis. It brings together in a single tool many sources of data, such as population genetics, various kinds of predictors, Human Genome Variation Society (HGVS) nomenclatures, curated databases, and access to various annotations. Accurate interpretation of DNA variants is crucial and can impact the patient care or have familial outcomes (prenatal diagnosis). Its importance will increase in the coming years with the expansion of the personalized medicine. MobiDetails is specifically designed to help with this task. Exonic or intronic substitutions and small insertions/deletions related to more than 18,000 human genes are easily submitted and annotated in real-time. It is a responsive website that can be accessed using mobiles or tablets during medical staff meetings. MobiDetails is based on publicly available resources, does not include any specific data on patients or phenotypes, and is freely available for academic use at https://mobidetails.iurc.montp.inserm.fr/MD/ .
Subject(s)
DNA , Databases, Genetic , Genetic Variation , Precision Medicine , Computational Biology , Genome, Human , Humans , INDEL Mutation , Phenotype , SoftwareABSTRACT
Next generation sequencing (NGS) has allowed the titin gene (TTN) to be identified as a major contributor to neuromuscular disorders, with high clinical heterogeneity. The mechanisms underlying the phenotypic variability and the dominant or recessive pattern of inheritance are unclear. Titin is involved in the formation and stability of the sarcomeres. The effects of the different TTN variants can be harmless or pathogenic (recessive or dominant) but the interpretation is tricky because the current bioinformatics tools can not predict their functional impact effectively. Moreover, TTN variants are very frequent in the general population. The combination of deep phenotyping associated with RNA molecular analyses, western blot (WB) and functional studies is often essential for the interpretation of genetic variants in patients suspected of titinopathy. In line with the current guidelines and suggestions, we implemented for patients with skeletal myopathy and with potentially disease causing TTN variant(s) an integrated genotype-transcripts-protein-phenotype approach, associated with phenotype and variants segregation studies in relatives and confrontation with published data on titinopathies to evaluate pathogenic effects of TTN variants (even truncating ones) on titin transcripts, amount, size and functionality. We illustrate this integrated approach in four patients with recessive congenital myopathy.
Subject(s)
Connectin/genetics , Genotype , Muscular Diseases/genetics , Phenotype , Adolescent , Child , Female , High-Throughput Nucleotide Sequencing , Humans , Middle Aged , Muscle, Skeletal/pathology , MutationABSTRACT
MOTIVATION: Microsatellite instability (MSI) is a molecular marker of DNA mismatch repair deficiency frequently at play in oncogenesis. MSI testing is used for diagnostic, prognostic and therapeutic purposes in several cancers. The current gold standard analysis for microsatellite status is based on length distribution analysis of multiplex-PCR generated DNA fragments from tumor samples which is a laborious and time consuming method. Next generation sequencing (NGS) using amplicon panels is an easy, accurate and scalable technique to determine both the microsatellite status and tumor genome mutations at the same time. Here, we describe MIAmS, an application designed to tag microsatellite status from amplicon NGS of tumor samples. Interestingly, this tool does not require paired normal tissue for comparison. In addition, this scalable application provides a user-friendly report for the interpretation of the results by biologists and exhibits a strong accuracy and robustness for determination of the MSI status. AVAILABILITY: https://github.com/bialimed/miams. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online, evaluation data are available at http://www.ebi.ac.uk/ena/data/view/PRJEB31725.
ABSTRACT
The recent deployment of next-generation sequencing approaches in routine laboratory analysis has considerably modified the landscape of BRCA1 and BRCA2 germline alteration detection in patients with a high risk of developing breast and/or ovarian cancer. Several commercial multiplex amplicon-based panels and bioinformatics solutions are currently available. In this study, we evaluated the combinations of several BRCA testing assays and bioinformatics solutions for the identification of single-nucleotide variants, insertion/deletion variants, and copy number variations (CNVs). Four assays (BRCA Tumor, BRCA HC, Ion AmpliSeq BRCA, and Access Array BRCA) and two commercial bioinformatics solutions (SeqNext software version 4.3.1 and Sophia DDM version 5.0.13) were tested on a set of 28 previously genotyped samples. All solutions exhibited accurate detection of single-nucleotide variants and insertion/deletion variants, except for Ion AmpliSeq BRCA, which exhibited a decrease in coverage. Of interest, for CNV analysis, the best accuracy was observed with the Sophia DDM platform regardless of the BRCA kit used. Finally, the performance of the most relevant combination (BRCA Tumor and Sophia DDM) was blindly validated on an independent set of 152 samples. Altogether, our results emphasize the need to accurately compare and control both molecular next-generation sequencing approaches and bioinformatics pipelines to limit the number of discrepant alterations and to provide a powerful tool for reliable detection of genetic alterations in BRCA1 and BRCA2, notably CNVs.
Subject(s)
BRCA1 Protein/genetics , BRCA2 Protein/genetics , Benchmarking , Computational Biology/methods , Germ Cells/metabolism , High-Throughput Nucleotide Sequencing/methods , Mutation/genetics , DNA Copy Number Variations/genetics , DNA Mutational Analysis , Humans , Reproducibility of ResultsABSTRACT
Interpretation of next-generation sequencing constitutes the main limitation of molecular diagnostics. In diagnosing myopathies and muscular dystrophies, another issue is efficiency in predicting the pathogenicity of variants identified in large genes, especially TTN; current in silico prediction tools show limitations in predicting and ranking the numerous variants of such genes. We propose a variant-prioritization tool, the MoBiDiCprioritization algorithm (MPA). MPA is based on curated interpretation of data on previously reported variants, biological assumptions, and splice and missense predictors, and is used to prioritize all types of single-nucleotide variants. MPA was validated by comparing its sensitivity and specificity to those of dbNSFP database prediction tools, using a data set composed of DYSF, DMD, LMNA, NEB, and TTN variants extracted from expert-reviewed and ExAC databases. MPA obtained the best annotation rates for missense and splice variants. As MPA aggregates the results from several predictors, individual predictor errors are counterweighted, improving the sensitivity and specificity of missense and splice variant predictions. We propose a sequential use of MPA, beginning with the selection of variants with higher scores and followed by, in the absence of candidate pathologic variants, consideration of variants with lower scores. We provide scripts and documentation for free academic use and a validated annotation pipeline scaled for panel and exome sequencing to prioritize single-nucleotide variants from a VCF file.
Subject(s)
Algorithms , High-Throughput Nucleotide Sequencing/methods , Molecular Diagnostic Techniques/methods , Molecular Sequence Annotation/methods , Polymorphism, Single Nucleotide/genetics , Computer Simulation , Humans , Mutation, Missense/genetics , RNA Splicing/geneticsABSTRACT
Mycobacterium sp. strain 4858 is a nontuberculous mycobacterium isolated from sputum in a Cambodian patient with a pulmonary infection. We report the first complete 5.6-Mbp-long genome sequence of Mycobacterium strain 4858, with 68.24% GC content, carrying 5,255 protein-coding genes, 47 tRNAs, and 3 rRNA genes.
ABSTRACT
Mycobacterium sp. strain 3519A is a nontuberculous mycobacterium isolated from sputum from a Cambodian patient with a pulmonary infection. We report here the first complete 7.3-Mbp-long genome sequence of Mycobacterium sp. 3519A with 66.35% GC content, encoding 7,029 protein-coding genes, 50 tRNAs, and 5 rRNA genes.