Faculty Opinions recommendation of Improving genetic diagnosis in Mendelian disease with transcriptome sequencing.

Author(s):  
Melanie Bahlo
2017 ◽  
Vol 9 (386) ◽  
pp. eaal5209 ◽  
Author(s):  
Beryl B. Cummings ◽  
Jamie L. Marshall ◽  
Taru Tukiainen ◽  
Monkol Lek ◽  
Sandra Donkervoort ◽  
...  

2016 ◽  
Author(s):  
Beryl B Cummings ◽  
Jamie L Marshall ◽  
Taru Tukiainen ◽  
Monkol Lek ◽  
Sandra Donkervoort ◽  
...  

AbstractExome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25-50%. Here, we explore the utility of transcriptome sequencing (RNA-seq) as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to over 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrentde novointronic mutation inCOL6A1that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.One Sentence SummaryTranscriptome sequencing improves the diagnostic rate for Mendelian disease in patients for whom genetic analysis has not returned a diagnosis.


2018 ◽  
Vol 22 (5) ◽  
pp. 620-626
Author(s):  
E. S. Rahmani ◽  
Н. Azarpara ◽  
M. Karimipoor ◽  
Н. Rahimi

The human primary immunodeficiency diseases (PIDs) refer to a rare heterogeneous group of single-gene inherited disorders causing malfunctions in the immune system, and thus the affected patients have a predisposition to severe life-threatening infections. The heterogeneous nature of PIDs, which involves at list 300 different genes, makes diagnosis of the disease a complex issue. Although studies revealed that six million people have a kind of PID, but due to a complex diagnosis procedure many affected individuals have not gotten a correct diagnosis. However, thanks to advancing in the DNA sequencing method and availability of sophisticated sequencers molecular characterization of genetic disorders have been revolutionized. The whole exome sequencing (WES) method can help clinicians detect Mendelian disease and other complex genetic disorders. The presented study used WES to investigate two infants with symptoms of primary immunodeficiency including hemophagocytic lymphohistio­cytosis (HLH) and severe combined immunodeficiency (SCID). It has been shown that the HLH patient had a mutation in the UNC13D gene (NM_199242.2:c.627delT), and the SCID patient had a mutation in the RAG1 gene (NM_000448.2:c.322C>G). It has been demonstrated that WES is a fast and cost-effective method facilitating genetic diagnosis in PID sufferers.


2018 ◽  
Author(s):  
Hefan Miao ◽  
Jiapeng Zhou ◽  
Qi Yang ◽  
Fan Liang ◽  
Depeng Wang ◽  
...  

AbstractFor a proportion of individuals judged clinically to have a recessive Mendelian disease, only one pathogenic variant can be found from clinical whole exome sequencing (WES), posing a challenge to genetic diagnosis and genetic counseling. Here we describe a case study, where WES identified only one pathogenic variant for an individual suspected to have glycogen storage disease type Ia (GSD-Ia), which is an autosomal recessive disease caused by bi-allelic mutations in the G6PC gene. Through Nanopore long-read whole-genome sequencing, we identified a 7kb deletion covering two exons on the other allele, suggesting that complex structural variants (SVs) may explain a fraction of cases when the second pathogenic allele is missing from WES on recessive diseases. Both breakpoints of the deletion are within Alu elements, and we designed Sanger sequencing and quantitative PCR assays based on the breakpoints for preimplantation genetic diagnosis (PGD) for the family planning on another child. Four embryos were obtained after in vitro fertilization (IVF), and an embryo without deletion in G6PC was transplanted after PGD and was confirmed by prenatal diagnosis, postnatal diagnosis, and subsequent lack of disease symptoms after birth. In summary, we present one of the first examples of using long-read sequencing to identify causal yet complex SVs in exome-negative patients, which subsequently enabled successful personalized PGD.


2021 ◽  
Author(s):  
Erin Zampaglione ◽  
Matthew Maher ◽  
Emily M. Place ◽  
Naomi E. Wagner ◽  
Stephanie DiTroia ◽  
...  

Purpose: In Mendelian disease diagnosis, variant analysis is a repetitive, error-prone, and time-consuming process. To address this, we have developed the Mendelian Analysis Toolkit (MATK), a configurable automated variant ranking program. Methods: MATK aggregates variant information from multiple annotation sources and uses expert-designed rules with parameterized weights to produce a ranked list of potentially causal solutions. MATK performance was measured by a comparison of MATK-aided versus human domain-expert analyses of 1060 inherited retinal degeneration (IRD) families investigated with an IRD-specific gene panel (589 families) and exome sequencing (471 families). Results: When comparing MATK-assisted analysis to expert curation, we found that 97.3% (541/556) of potential solutions found by experts were also identified by the MATK-assisted analysis. Furthermore, MATK-assisted analysis identified 114 additional potential solutions. The software also showed utility in data reanalysis after remapping to the GRCh38 genome build. Conclusion: MATK expedites the process of identifying likely solving variants in Mendelian traits and helps to remove variability coming from human error and researcher bias. MATK facilitates data re-analysis to keep up with the constantly improving annotation sources and NGS processing pipelines. The software is open source and available at https://gitlab.partners.org/meei-ogi-bioinformatics/MendelAnalysis


2021 ◽  
Author(s):  
Vicente A. Yepez ◽  
Mirjana Gusic ◽  
Robert Kopajtich ◽  
Christian Mertes ◽  
Nicholas H. Smith ◽  
...  

Lack of functional evidence hampers variant interpretation, leaving a large proportion of cases with a suspected Mendelian disorder without genetic diagnosis after genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies, and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA-sequencing (RNA-seq) in routine diagnostics. To address these issues, we implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease. We detected on average 12,500 genes per sample including around 60% disease genes - a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than one week from sample preparation to result reporting and provided a median of eight disease genes per patient for inspection. A genetic diagnosis was established for 16% of the WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions. Together, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics.


2021 ◽  
Author(s):  
Eyal Simonovsky ◽  
Moran Sharon ◽  
Maya Ziv ◽  
Omry Mauer ◽  
Idan Hekselman ◽  
...  

ABSTRACTGenetic studies of Mendelian and rare diseases face the critical challenges of identifying pathogenic gene variants and their modes-of-action. Previous efforts rarely utilized the tissue-selective manifestation of these diseases for their elucidation. Here we introduce an interpretable machine learning (ML) platform that utilizes heterogeneous and large-scale tissue-aware datasets of human genes, and rigorously, concurrently and quantitatively assesses hundreds of candidate mechanisms per disease. The resulting tissue-aware ML platform is applicable in gene-specific, tissue-specific, or patient-specific modes. Application of the platform to selected Mendelian disease genes pinpointed mechanisms that lead to tissue-specific disease manifestation. When applied jointly to diseases that manifest in the same tissue, the models revealed common known and previously underappreciated factors that underlie tissue-selective disease manifestation. Lastly, we harnessed our ML platform toward genetic diagnosis of tissue-selective rare diseases. Patient-specific models of candidate disease-causing genes from 50 patients successfully prioritized the pathogenic gene in 86% of the cases, implying that the tissue-selectivity of rare diseases aids in filtering out unlikely candidate genes. Thus, interpretable tissue-aware ML models can boost mechanistic understanding and genetic diagnosis of tissue-selective heritable diseases. A webserver supporting gene prioritization is available at https://netbio.bgu.ac.il/trace/.


2019 ◽  
Author(s):  
Youngha Lee ◽  
Soojin Park ◽  
Jin Sook Lee ◽  
Soo Yeon Kim ◽  
Jaeso Cho ◽  
...  

AbstractBackgroundA substantial portion of Mendelian disease patients suffers from genetic variants that are inherited in a recessive manner. A precise understanding of pathogenic recessive variants in a population would assist in pre-screening births of such patients. However, a systematic understanding of the contribution of recessive variants to Mendelian diseases is still lacking.MethodsGenetic diagnosis and variant discovery of 553 undiagnosed Korean patients with complex neurodevelopmental problems (KND for Korean NeuroDevelopmental cohort) were performed using whole exome sequencing of patients and their parents. Pathogenic variants were selected and evaluated based on a comparison to patient symptoms and genetic properties of the variants were analyzed.ResultsDisease-causing variants, including newly discovered variants, were identified in in 57.5% of the probands of the KND cohort. Of the 553 patients, 47.4% harbored variants that were previously reported as being pathogenic, and 35.1% of the previous reported pathogenic variants were inherited in a recessive manner. Genes that cause recessive disorders tend to be less constrained by loss-of-function variants and enriched in metabolic and mitochondrial pathways. This observation was applied to an estimation that approximately 1 in 17 healthy Korean individuals carry at least one of these pathogenic variants that develop severe neurodevelopmental problems in a recessive manner. Furthermore, the feasibility of these genes for carrier screening was evaluated.ConclusionsWe suggest that the odds are high for healthy individuals carrying a potentially pathogenic variant, and its genetic properties. Our results will serve as a foundation for recessive variant screening to reduce occurrences of rare Mendelian disease patients. Additionally, our results highlight the utility and necessity of whole exome sequencing-based diagnostics for improving patient care in a country with a centralized medical system.


Author(s):  
Mira Holliday ◽  
Emma S. Singer ◽  
Samantha B. Ross ◽  
Seakcheng Lim ◽  
Sean Lal ◽  
...  

Background - Transcriptome sequencing can improve genetic diagnosis of Mendelian diseases but requires access to tissue expressing disease-relevant transcripts. We explored genetic testing of hypertrophic cardiomyopathy (HCM) using transcriptome sequencing of patient-specific human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). We also explored whether antisense oligonucleotides (AOs) could inhibit aberrant mRNA splicing in hiPSC-CMs. Methods - We derived hiPSC-CMs from patients with HCM due to MYBPC3 splice-gain variants, or an unresolved genetic cause. We used transcriptome sequencing of hiPSC-CM RNA to identify pathogenic splicing and used AOs to inhibit this splicing. Results - Transcriptome sequencing of hiPSC-CMs confirmed aberrant splicing in two people with previously identified MYBPC3 splice-gain variants (NM_000256.3:c.1090+453C>T and NM_000256.3:c.1224-52G>A). In a patient with an unresolved genetic cause of HCM following genome sequencing, transcriptome sequencing of hiPSC-CMs revealed diverse cryptic exon splicing due to an MYBPC3 NM_000256.3:c.1928-569G>T variant, and this was confirmed in cardiac tissue from an affected sibling. AO treatment demonstrated almost complete inhibition of cryptic exon splicing in one patient-specific hiPSC-CM line. Conclusions - Transcriptome sequencing of patient specific hiPSC-CMs solved a previously undiagnosed genetic cause of HCM and may be a useful adjunct approach to genetic testing. AO inhibition of cryptic exon splicing is a potential future personalised therapeutic option.


2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Zhou Zhou ◽  
Qing Sang ◽  
Lei Wang

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