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RNA-Sequencing shows novel transcriptomic signatures in failing and non-failing human heart

ABSTRACT: The knowledge of an expression network signature in end-stage heart failure (HF) diseased hearts may offer important insights into the complex pathogenesis of advanced cardiac failure, as well as it may provide potential targets for therapeutic intervention. In this study, the NGS sequencing of RNA (RNA-Seq) method was employed to obtain the whole transcriptome of cardiac tissues from transplant recipients with advanced stage of HF. The analysis of RNA-Seq data presents novel challenges and many methods have been developed for the purpose of mapping reads to genomic features and quantifying gene expression. The main goal of this work was to identify, characterize and catalogue all the transcripts expressed within cardiac tissue and to quantify the differential expression of transcripts in both physio- and pathological conditions through whole transcriptome analyses. Expression levels, differential splicing, allele-specific expression, RNA editing and fusion transcripts constitute important information when comparing samples for disease related studies. Analysis methods for RNA-Seq data are continuing to evolve. Thus, in order to find the best solution for filter generated list of differentially expressed genes, an informatic approach of NOISeq BIO method has been applied in this RNA-Seq analysis. Most of the genes obtained by filtering differentially expressed gene list, have been experimentally validated by Real time RT-PCR. Noteworthy, these findings provide valuable resources for further studies of the molecular mechanisms involved in heart ischemic response thus leading to potential novel biomarkers and targets for therapeutic intervention in the onset and progression of cardiomyopathies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE71613 | GEO | 2015/11/01

SECONDARY ACCESSION(S): PRJNA291619

REPOSITORIES: GEO

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Project description:Accurate and comprehensive de novo transcriptome profiling in heart is a central issue to better understand cardiac physiology and diseases. Although significant progress has been made in genome-wide profiling for quantitative changes in cardiac gene expression, current knowledge offers limited insights to the total complexity in cardiac transcriptome at individual exon level. To develop more robust bioinformatic approaches to analyze high-throughput RNA sequencing (RNA-Seq) data, with the focus on the investigation of transcriptome complexity at individual exon and transcript levels. In addition to overall gene expression analysis, the methods developed in this study were used to analyze RNA-Seq data with respect to individual transcript isoforms, novel spliced exons, novel alternative terminal exons, novel transcript clusters (i.e., novel genes) and long non-coding RNA genes. We applied these approaches to RNA-Seq data obtained from mouse hearts following pressure-overload induced by trans-aortic constriction. Based on experimental validations, analyses of the features of the identified exons/transcripts, and expression analyses including previously published RNA-Seq data, we demonstrate that the methods are highly effective in detecting and quantifying individual exons and transcripts. Novel insights inferred from the examined aspects of the cardiac transcriptome open ways to further experimental investigations. Our work provided a comprehensive set of methods to analyze mouse cardiac transcriptome complexity at individual exon and transcript levels. Applications of the methods may infer important new insights to gene regulation in normal and disease hearts in terms of exon utilization and potential involvement of novel components of cardiac transcriptome. Left ventricular tissues were collected from C57BL/6 mice after 1 week (hypertrophy stage, HY) and 8 weeks post trans-aortic constriction (TAC) procedure (heart failure stage, HF), respectively, and their corresponding Sham controls (Sham-HY, Sham-HF). To conduct RNA-Seq analysis, total RNAs from six TAC and Sham-operated mice at the HY stage and four TAC and corresponding Sham mice at the HF stage were obtained.

Project description:Rationale: Cardiac extracellular matrix (ECM) comprises a dynamic molecular network providing structural support to heart tissue function. Understanding the impact of ECM remodeling on cardiac cells during heart failure (HF) is essential to prevent adverse ventricular remodeling and restore organ functionality in affected patients. Objectives: We aimed to (i) identify consistent modifications to cardiac ECM structure and mechanics that contribute to HF and (ii) determine the underlying molecular mechanisms. Methods and Results: We first performed decellularization of human and murine ECM (dECM) and then analyzed the pathological changes occurring in dECM during HF by atomic force (AFM), two-photon microscopy, high-resolution 3D image analysis and computational fluid dynamics (CFD) simulation. We then performed molecular and functional assays in patient-derived cardiac fibroblasts (CFs) based on YAP-TEAD mechanosensing activity and collagen contraction assays. The analysis of HF dECM resulting from ischemic (IHD) or dilated cardiomyopathy (DCM), as well as from mouse infarcted tissue, identified a common pattern of modifications in their 3D topography. As compared to healthy heart, HF ECM exhibited aligned, flat and compact fiber bundles, with reduced elasticity and organizational complexity. At the molecular level, RNA sequencing of HF CFs highlighted the overrepresentation of dysregulated genes involved in ECM organization, or being connected to TGFß1, Interleukin-1, TNF-alpha and BDNF signaling pathways. Functional tests performed on HF CFs pointed at mechanosensor YAP as a key player in ECM remodeling in the diseased heart via transcriptional activation of focal adhesion assembly. Finally, in vitro experiments clarified pathological cardiac ECM prevents cell homing, thus providing further hints to identify a possible window of action for cell therapy in cardiac diseases. Conclusions: Our multi-parametric approach has highlighted repercussions of ECM remodeling on cell homing, CF activation and focal adhesion protein expression via hyper-activated YAP signaling during HF. Key words: Decellularization, extracellular matrix, dilated cardiomyopathy, ischemic heart disease, YAP, dilated cardiomyopathy, mechanobiology.

Project description:Mechanical unloading by ventricular assist devices (VAD) leads to significant gene-expression changes often summarized as reverse remodeling. However, little is known on individual transcriptome changes during VAD-support and its relationship to non-failing hearts (NF). In addition no data are available for the transcriptome regulation during non-pulsatile VAD-support. Therefore we analysed the gene-expression patterns of 30 paired samples from VAD-supported (including 8 non-pulsatile VADs) and 8 non-failing control hearts (NF) using the first total human genome-array available. Transmural myocardial samples were collected for RNA-isolation. RNA was isolated by commercial methods and processed according to chip-manufacturer recommendations. cRNA were hybridized on Affymetrix HG-U133 Plus 2.0 arrays, providing coverage of the whole human genome Array. Data was analyzed using Microarray Analysis Suite 5.0 (Affymetrix) and clustered by Expressionist software (Genedata). 352 transcripts were differentially regulated between samples from VAD-implantation and NF, whereas 510 were significantly regulated between VAD-transplantation and NF (paired t-test p<0.001, fold change >=1.6). Remarkably, only a minor fraction of 111 transcripts was regulated in heart failure (HF) and during VAD-support. Unsupervised hierarchical clustering of paired VAD- and NF-samples revealed separation of HF- and NF- samples, however individual differentiation of VAD-implantation and VAD-transplantation was not accomplished. Clustering of pulsatile and non-pulsatile VAD did not lead to robust separation of gene expression patterns. During VAD-support myocardial gene expression changes do not indicate reversal of the HF-phenotype, but reveal a distinct HF-related pattern. Transcriptome analysis of pulsatile and non-pulsatile VAD-supported hearts did not provide evidence for a pump-mode specific transcriptome pattern. Microarrays were used to elucidate the differences between non-failing control hearts and those, suffering from end-stage heart failure pre and post mechanical unloading.

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RNA-Sequencing shows novel transcriptomic signatures in failing and non-failing human heart

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