103 research outputs found
Functional and Pharmacological Analysis of Cardiomyocytes Differentiated from Human Peripheral Blood Mononuclear-Derived Pluripotent Stem Cells
SummaryAdvances in induced pluripotent stem cell (iPSC) technology have set the stage for routine derivation of patient- and disease-specific human iPSC-cardiomyocyte (CM) models for preclinical drug screening and personalized medicine approaches. Peripheral blood mononuclear cells (PBMCs) are an advantageous source of somatic cells because they are easily obtained and readily amenable to transduction. Here, we report that the electrophysiological properties and pharmacological responses of PBMC-derived iPSC CM are generally similar to those of iPSC CM derived from other somatic cells, using patch-clamp, calcium transient, and multielectrode array (MEA) analyses. Distinct iPSC lines derived from a single patient display similar electrophysiological features and pharmacological responses. Finally, we demonstrate that human iPSC CMs undergo acute changes in calcium-handling properties and gene expression in response to rapid electrical stimulation, laying the foundation for an in-vitro-tachypacing model system for the study of human tachyarrhythmias
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EM-mosaic detects mosaic point mutations that contribute to congenital heart disease.
BackgroundThe contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.MethodsWe developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available.ResultsEM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.ConclusionsWe estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses
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Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects.
Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to identify causative variants is limited. To identify causal CHD genes that are associated with specific molecular functions, the study used prior knowledge to filter de novo variants from 2,881 probands with sporadic severe CHD. This approach enabled the authors to identify an association between left ventricular outflow tract obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated signal transduction. Using CRISPR zebrafish knockdowns, the study confirmed that WAVE2 complex proteins brk1, nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac development
Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors
Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared with XHMM, and a significant enrichment of 15q11.2 deletions compared with controls. In addition, MEM identified eight cases of uniparental disomy, sample switches, and DNA contamination. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools
Modification of hERG1 channel gating by Cd2+
Each of the four subunits in a voltage-gated potassium channel has a voltage sensor domain (VSD) that is formed by four transmembrane helical segments (S1–S4). In response to changes in membrane potential, intramembrane displacement of basic residues in S4 produces a gating current. As S4 moves through the membrane, its basic residues also form sequential electrostatic interactions with acidic residues in immobile regions of the S2 and S3 segments. Transition metal cations interact with these same acidic residues and modify channel gating. In human ether-á-go-go–related gene type 1 (hERG1) channels, Cd2+ coordinated by D456 and D460 in S2 and D509 in S3 induces a positive shift in the voltage dependence of activation of ionic currents. Here, we characterize the effects of Cd2+ on hERG1 gating currents in Xenopus oocytes using the cut-open Vaseline gap technique. Cd2+ shifted the half-point (V1/2) for the voltage dependence of the OFF gating charge–voltage (QOFF-V) relationship with an EC50 of 171 µM; at 0.3 mM, V1/2 was shifted by +50 mV. Cd2+ also induced an as of yet unrecognized small outward current (ICd-out) upon repolarization in a concentration- and voltage-dependent manner. We propose that Cd2+ and Arg residues in the S4 segment compete for interaction with acidic residues in S2 and S3 segments, and that the initial inward movement of S4 associated with membrane repolarization displaces Cd2+ in an outward direction to produce ICd-out. Co2+, Zn2+, and La3+ at concentrations that caused ∼+35-mV shifts in the QOFF-V relationship did not induce a current similar to ICd-out, suggesting that the binding site for these cations or their competition with basic residues in S4 differs from Cd2+. New Markov models of hERG1 channels were developed that describe gating currents as a noncooperative two-phase process of the VSD and can account for changes in these currents caused by extracellular Cd2+
Genetic and Physiologic Dissection of the Vertebrate Cardiac Conduction System
Vertebrate hearts depend on highly specialized cardiomyocytes that form the cardiac conduction system (CCS) to coordinate chamber contraction and drive blood efficiently and unidirectionally throughout the organism. Defects in this specialized wiring system can lead to syncope and sudden cardiac death. Thus, a greater understanding of cardiac conduction development may help to prevent these devastating clinical outcomes. Utilizing a cardiac-specific fluorescent calcium indicator zebrafish transgenic line, Tg(cmlc2:gCaMP)s878, that allows for in vivo optical mapping analysis in intact animals, we identified and analyzed four distinct stages of cardiac conduction development that correspond to cellular and anatomical changes of the developing heart. Additionally, we observed that epigenetic factors, such as hemodynamic flow and contraction, regulate the fast conduction network of this specialized electrical system. To identify novel regulators of the CCS, we designed and performed a new, physiology-based, forward genetic screen and identified for the first time, to our knowledge, 17 conduction-specific mutations. Positional cloning of hobgoblins634 revealed that tcf2, a homeobox transcription factor gene involved in mature onset diabetes of the young and familial glomerulocystic kidney disease, also regulates conduction between the atrium and the ventricle. The combination of the Tg(cmlc2:gCaMP)s878 line/in vivo optical mapping technique and characterization of cardiac conduction mutants provides a novel multidisciplinary approach to further understand the molecular determinants of the vertebrate CCS
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EM-mosaic detects mosaic point mutations that contribute to congenital heart disease
Background
The contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.
Methods
We developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available.
Results
EM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.
Conclusions
We estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses
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