NUP155 insufficiency recalibrates a pluripotent transcriptome with network remodeling of a cardiogenic signaling module of a pluripotent network
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ABSTRACT:
PROVIDER: PRJNA437489 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6819560_1.fastq.gz | Fastqsanger.gz | |||
| SRR6819560_2.fastq.gz | Fastqsanger.gz | |||
| SRR6819561_1.fastq.gz | Fastqsanger.gz | |||
| SRR6819561_2.fastq.gz | Fastqsanger.gz | |||
| SRR6819562_1.fastq.gz | Fastqsanger.gz |
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Project description:Background: Atrial fibrillation is a cardiac disease driven by numerous idiopathic etiologies. NUP155 is a nuclear pore complex protein that has been identified as a clinical driver of atrial fibrillation, yet the precise mechanism is unknown. The present study employs a systems biology algorithm to identify effects of NUP155 disruption on cardiogenicity in a model of stem cell-derived differentiation. Methods: Embryonic stem (ES) cell lines (n=5) with truncated NUP155 (Nup155+/-) were cultured in parallel with wild type (WT) ES cells (n=5), and then harvested for RNAseq. Samples were run on an Illumina HiSeq 2000. Reads were analyzed using Strand NGS, Cytoscape, DAVID and Ingenuity Pathways Analysis to deconvolute the NUP155-disrupted transcriptome. Network topological analysis identified key features that controlled framework architecture and functional enrichment. Results: In NUP155 truncated ES cells, significant expression changes were detected in 326 genes compared to WT. These genes segregated into clusters that enriched for specific gene ontologies. Major network drivers included TP53, a regulator of genome integrity. Deconvolution of the collective framework into discrete sub-networks identified a module with the highest score that enriched for Cardiovascular System Development, and revealed NTRK1/TRKA and SRSF2/SC35 as critical hubs within this cardiogenic module. Conclusions: The strategy of pluripotent transcriptome deconvolution used here identified a novel association of NUP155 with potential drivers of arrhythmogenic AF. Here, NUP155 regulates cardioplasticity of a sub-network embedded within a larger framework of genome integrity, and exemplifies how transcriptome cardiogenicity in an embryonic stem cell genome is recalibrated by nucleoporin dysfunction.
2019-05-21 | GSE111596 | GEO
Project description:BACKGROUND:Atrial fibrillation is a cardiac disease driven by numerous idiopathic etiologies. NUP155 is a nuclear pore complex protein that has been identified as a clinical driver of atrial fibrillation, yet the precise mechanism is unknown. The present study employs a systems biology algorithm to identify effects of NUP155 disruption on cardiogenicity in a model of stem cell-derived differentiation. METHODS:Embryonic stem (ES) cell lines (n =?5) with truncated NUP155 were cultured in parallel with wild type (WT) ES cells (n =?5), and then harvested for RNAseq. Samples were run on an Illumina HiSeq 2000. Reads were analyzed using Strand NGS, Cytoscape, DAVID and Ingenuity Pathways Analysis to deconvolute the NUP155-disrupted transcriptome. Network topological analysis identified key features that controlled framework architecture and functional enrichment. RESULTS:In NUP155 truncated ES cells, significant expression changes were detected in 326 genes compared to WT. These genes segregated into clusters that enriched for specific gene ontologies. Deconvolution of the collective framework into discrete sub-networks identified a module with the highest score that enriched for Cardiovascular System Development, and revealed NTRK1/TRKA and SRSF2/SC35 as critical hubs within this cardiogenic module. CONCLUSIONS:The strategy of pluripotent transcriptome deconvolution used in the current study identified a novel association of NUP155 with potential drivers of arrhythmogenic AF. Here, NUP155 regulates cardioplasticity of a sub-network embedded within a larger framework of genome integrity, and exemplifies how transcriptome cardiogenicity in an embryonic stem cell genome is recalibrated by nucleoporin dysfunction.
| S-EPMC5977756 | biostudies-literature
Project description:Rationale: Cardiac development is a complex process that results in the first integrated, multi-lineage embryonic tissue. Imperfect developmental progression leads to congenital heart disease, the most common birth defect with developmental corruption affecting more than 1% of all live births. Interrogation of individual genes has provided the backbone for cardiac developmental biology, yet a comprehensive transcriptome derived from natural cardiogenesis is required to establish an unbiased roadmap to gauge innate developmental milestones necessary for stem cell-based differentiation and in vitro disease modeling. Objective: Establish a contextual expression database of spatial-temporal cardiac structures, and validate a predictive tool to diagnose and predict cardiogenic outcomes from individual pluripotent stem cell lines. Methods and Results: Stage-specific cardiac structures were dissected from eight distinctive embryonic time points to produce a genome-wide expressome analysis across the spectrum of early to late cardiogenesis. Hierarchical clustering of the time course dataset demonstrated discrete gene expression profiles during natural embryonic development. In reference to the native cardiogenic expression roadmap, disruptive iPSC-derived cardiac expression profiles were revealed from pro-cardiogenic 3-factor (SOX2, OCT4, KLF4) compared to non-cardiogenic 4-factor (addition of c-MYC) reprogramming regimens upon stage-specific differentiation. Expression of cardiac-related genes from 3F-iPSC differentiated in vitro at day 0, 5, and 11 recapitulated expression of natural embryos at days 0, E7.5-E8.5, and E14.5-E18.5, respectively. In contrast, 4F-iPSC demonstrated variable gastrulation gene expression profiles beginning at day 5 of differentiation. Differential gene expression within the pluripotent ground state between the archetypical high cardiogenic potential of embryonic stem cells recapitulated in 3F-iPSC vs. the low cardiogenic potential of 4F-iPSC revealed 23 distinguishing candidate genes. Upon subsequent differentiation, cell line-specific gene expression differences were magnified to 399 genes at day 5 and 726 genes at day 11. A confirmed panel of 20 genes, differentially expressed between high and low cardiogenic cell lines, was transformed into a predictive score that was sufficient to correctly rank independent iPSC lines according to cardiogenic potential. Conclusions: Transcriptome analysis attuned to the embryonic developing heart provides a robust platform to probe coordinated cardiac specification and maturation from stem cell-based cardiogenesis model systems. Based on this genome-wide expressome roadmap, a panel of pre-cardiac genes was extracted that allowed differential prognosis of cardiogenic competency from individual reprogrammed cell lines at the pluripotent state. The overall experimental design includes 3 time points (Day0, Day5, Day11) and 3 different stem cell lines: R1 embryonic stem cells (ESCs), H9 induced pluripotent stem cells (H9-iPSCs) generated/reprogrammed by 3 transcription factors (called 3F-iPSCs), and 19BL induced pluripotent stem cells (19BL-iPSCs) generated/reprogrammed by 4 transcription factors (called 4F-iPSC). At each time point, each cell line has 3 biological replicates. In total, there are 27 samples. R1-embryonic stem cells (R1-ESCs): Day0 undifferentiated ESCs - 3 biological replicates, Differentiated for 5 days (Day5) - 3 biological replicates, Differentiated for 11 days (Day11) - 3 biological replicates. 3F-iPSC (H9 iPSCs): Day 0 undifferentiated - 3 biological replicates, Differentiated for 5 days (Day5) - 3 biological replicates, Differentiated for 11 days (Day11) - 3 biological replicates. 4F-iPSC (19BL-iPSCs): Day0 undifferentiated - 3 biological replicates, Differentiated for 5 days (Day5) - 3 biological replicates, Differentiated for 11 days (Day11) - 3 biological replicates.
2013-09-23 | E-GEOD-43197 | biostudies-arrayexpress
Project description:Rationale: Cardiac development is a complex process that results in the first integrated, multi-lineage embryonic tissue. Imperfect developmental progression leads to congenital heart disease, the most common birth defect with developmental corruption affecting more than 1% of all live births. Interrogation of individual genes has provided the backbone for cardiac developmental biology, yet a comprehensive transcriptome derived from natural cardiogenesis is required to establish an unbiased roadmap to gauge innate developmental milestones necessary for stem cell-based differentiation and in vitro disease modeling. Objective: Apply the contextual expression database of spatial-temporal cardiac structures (published in another manuscript by Li X. from the same group) to diagnose and predict cardiogenic outcomes from individual pluripotent stem cell lines. Methods and Results: Stage-specific cardiac structures were dissected from eight distinctive embryonic time points to produce a genome-wide expressome analysis across the spectrum of early to late cardiogenesis. Hierarchical clustering of the time course dataset demonstrated discrete gene expression profiles during natural embryonic development. In reference to the native cardiogenic expression roadmap, disruptive iPSC-derived cardiac expression profiles were revealed from pro-cardiogenic 3-factor (SOX2, OCT4, KLF4) compared to non-cardiogenic 4-factor (addition of c-MYC) reprogramming regimens upon stage-specific differentiation. Expression of cardiac-related genes from 3F-iPSC differentiated in vitro at day 0, 5, and 11 recapitulated expression of natural embryos at days 0, E7.5-E8.5, and E14.5-E18.5, respectively. In contrast, 4F-iPSC demonstrated variable gastrulation gene expression profiles beginning at day 5 of differentiation. Differential gene expression within the pluripotent ground state between the archetypical high cardiogenic potential of embryonic stem cells recapitulated in 3F-iPSC vs. the low cardiogenic potential of 4F-iPSC revealed 23 distinguishing candidate genes. Upon subsequent differentiation, cell line-specific gene expression differences were magnified to 399 genes at day 5 and 726 genes at day 11. A confirmed panel of 20 genes, differentially expressed between high and low cardiogenic cell lines, was transformed into a predictive score that was sufficient to correctly rank independent iPSC lines according to cardiogenic potential. Conclusions: Transcriptome analysis attuned to the embryonic developing heart provides a robust platform to probe coordinated cardiac specification and maturation from stem cell-based cardiogenesis model systems. Based on this genome-wide expressome roadmap, a panel of pre-cardiac genes was extracted that allowed differential prognosis of cardiogenic competency from individual reprogrammed cell lines at the pluripotent state.
2013-09-23 | GSE43197 | GEO
Project description:Pluripotent P19CL6 embryonic carcinoma cells can be differentiated to a cardiac lineage by culture in the presence of DMSO. The goal of this study was to characterize temporal gene expression patterns associated with cardiogenic differentiation. Gene expression analysis was conducted on differentiating P19CL6 cells at several time points following induction with 1% DMSO. Samples were processed for analysis by Affymetrix GeneChip. Analysis was done on P19CL6 cells growing in the absence of DMSO or in the presence of DMSO for 4, 6, 8, 10 or 12 days. Three independent samples (n=3) were used for all conditions except for 6-day and 12-day DMSO cultures (n=2).
2010-07-07 | E-GEOD-17910 | biostudies-arrayexpress
Project description:Pluripotent P19CL6 embryonic carcinoma cells can be differentiated to a cardiac lineage by culture in the presence of DMSO. The goal of this study was to characterize temporal gene expression patterns associated with cardiogenic differentiation. Gene expression analysis was conducted on differentiating P19CL6 cells at several time points following induction with 1% DMSO. Samples were processed for analysis by Affymetrix GeneChip.
2010-07-08 | GSE17910 | GEO
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2017-04-12 | GSE87696 | GEO
Project description:Despite investment in toxicogenomics, nonclinical safety studies are still used to predict clinical liabilities for new drug candidates. Network-based approaches for genomic analysis help overcome challenges with whole-genome transcriptional profiling using limited numbers of treatments for phenotypes of interest. Herein, we apply co-expression network analysis to safety assessment using rat liver gene expression data to define 415 modules, exhibiting unique transcriptional control, organized in a visual representation of the transcriptome (the ‘TXG-MAP’). Accounting for the overall transcriptional activity resulting from treatment, we explain mechanisms of toxicity and predict distinct toxicity phenotypes using module associations. We demonstrate that early network responses compliment traditional histology-based assessment in predicting outcomes for longer studies and identify a novel mechanism of hepatotoxicity involving endoplasmic reticulum stress and Nrf2 activation. Module-based molecular subtypes of cholestatic injury derived using rat translate to human. Moreover, compared to gene-level analysis alone, combining module and gene-level analysis performed in sequence identifies significantly more phenotype-gene associations, including established and novel biomarkers of liver injury.
2017-04-12 | GSE87730 | GEO
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2017-03-22 | GSE96848 | GEO
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| PRJNA757005 | ENA