Genome sequencing and variant calling of HCM Patients with MYH7 variants
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PROVIDER: PRJNA1251723 | ENA |
REPOSITORIES: ENA
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Project description:Genome sequencing and variant calling of HCM Patients with MYH7 variants
| PRJNA1251724 | ENA
Project description:Single-cell sequencing methodologies such as scRNA-seq and scATAC-seq have become widespread and effective tools to interrogate tissue composition. Increasingly, variant callers are being applied to these methodologies to resolve the genetic heterogeneity of a sample, especially in the case of detecting the clonal architecture of a tumor. Typically, traditional bulk DNA variant callers are applied to the pooled reads of a single-cell library to detect candidate mutations. Recently, multiple studies have applied such callers on reads from individual cells, with some citing the ability to detect rare variants with higher sensitivity. Many studies apply these two approaches to the Chromium (10x Genomics) scRNA-seq and scATAC-seq methodologies. However, Chromium-based libraries may offer additional challenges to variant calling compared to existing single-cell methodologies, raising questions for the validity of variants obtained from such a workflow. To determine the merits and challenges of various variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries, we use sample libraries with matched bulk whole-genome-sequencing to evaluate the performance of callers. We review caller performance, finding that bulk callers applied on pooled reads significantly outperform individual-cell approaches. We also evaluate variants unique to scRNA-seq and scATAC-seq methodologies, finding patterns of noise but also potential capture of RNA-editing events. Finally, we review the notion that variant calling at the single-cell level can detect rare somatic variants, providing empirical results that suggest resolving such variants is infeasible in single-cell Chromium libraries.
2024-08-05 | GSE213503 | GEO
Project description:Single-cell sequencing methodologies such as scRNA-seq and scATAC-seq have become widespread and effective tools to interrogate tissue composition. Increasingly, variant callers are being applied to these methodologies to resolve the genetic heterogeneity of a sample, especially in the case of detecting the clonal architecture of a tumor. Typically, traditional bulk DNA variant callers are applied to the pooled reads of a single-cell library to detect candidate mutations. Recently, multiple studies have applied such callers on reads from individual cells, with some citing the ability to detect rare variants with higher sensitivity. Many studies apply these two approaches to the Chromium (10x Genomics) scRNA-seq and scATAC-seq methodologies. However, Chromium-based libraries may offer additional challenges to variant calling compared to existing single-cell methodologies, raising questions for the validity of variants obtained from such a workflow. To determine the merits and challenges of various variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries, we use sample libraries with matched bulk whole-genome-sequencing to evaluate the performance of callers. We review caller performance, finding that bulk callers applied on pooled reads significantly outperform individual-cell approaches. We also evaluate variants unique to scRNA-seq and scATAC-seq methodologies, finding patterns of noise but also potential capture of RNA-editing events. Finally, we review the notion that variant calling at the single-cell level can detect rare somatic variants, providing empirical results that suggest resolving such variants is infeasible in single-cell Chromium libraries.
2024-08-05 | GSE213338 | GEO
Project description:The most common form of genetic heart disease is hypertrophic cardiomyopathy (HCM), which is caused by mutations in cardiac sarcomeric genes and leads to abnormal heart muscle thickening. Complications of HCM include heart failure, arrhythmia, and sudden cardiac death. The dominant-negative c.1208 G>A (p.R403Q) mutation in b-myosin (MYH7) is a common and well-studied mutation that leads to increased cardiac contractility and HCM onset. Here we identify an adenine base editor (ABE) and single-guide RNA system that can efficiently correct this human pathogenic mutation with minimal off-target and bystander editing. We show that delivery of base editing components rescues pathological manifestations of HCM in iPSC-cardiomyocytes derived from HCM patients and in a humanized mouse model of HCM. Our findings demonstrate the use of base editing to treat inherited cardiac diseases and prompt the further development of ABE-based therapies to correct a variety of monogenic mutations causing cardiac disease.
2022-10-25 | GSE201755 | GEO
Project description:We use stable expression of a cystathionine-beta synthase (CBS) variant library in HEK293T cells to identify CBS coding sequence variants that alter mRNA abundance
2022-04-22 | GSE201057 | GEO
Project description:Center for Common Disease Genomics [CCDG]: Variant Calling Controls
| PRJNA671459 | ENA
Project description:Center for Common Disease Genomics [CCDG]: Variant Calling Controls
| PRJNA671455 | ENA
Project description:satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect
| PRJNA828159 | ENA
Project description:Hypertrophic cardiomyopathy (HCM) is characterized by asymmetric left ventricular (LV) hypertrophy and diastolic dysfunction, which leads to LV outflow tract obstruction (LVOTO) in the majority of cases. Mutations in genes encoding sarcomeric proteins cause HCM and are identified in more than half of the patients (sarcomere-mutation positive, SMP). Currently, more than 1500 HCM-causing mutations are known. Approximately 80% of mutations are located in the MYH7 and MYBPC3 genes, encoding for the thick filament proteins β-myosin heavy chain (β-MHC) and cardiac myosin-binding protein C (cMyBP-C), respectively. Less frequent are mutations in the TNNT2 and TNNI3 genes, encoding for the thin filament proteins cardiac troponin T (cTnT) and I (cTnI). Here, we applied an unbiased proteomics approach in a large number of myectomy samples from a clinically well-characterized HCM patient group to define HCM-specific derailments as well as genotype-specific changes at protein level. Our study shows that the downregulation of metabolic pathways and the upregulation of extracellular matrix proteins are the most prominent HCM-specific disease characteristics that are present in all samples independent of their genotype.
2021-01-14 | PXD012467 | Pride
Project description:MYH7 G256E hiPSC-CM (Day 30)
2024-04-15 | GSE220933 | GEO