Dataset Information

Comparative Transcriptome Analysis Reveals Substantial Tissue Specificity in Human Aortic Valve.

ABSTRACT: RNA sequencing (RNA-seq) has revolutionary roles in transcriptome identification and quantification of different types of tissues and cells in many organisms. Although numerous RNA-seq data derived from many types of human tissues and cell lines, little is known on the transcriptome repertoire of human aortic valve. In this study, we sequenced the total RNA prepared from two calcified human aortic valves and reported the whole transcriptome of human aortic valve. Integrating RNA-seq data of 13 human tissues from Human Body Map 2 Project, we constructed a transcriptome repertoire of human tissues, including 19,505 protein-coding genes and 4,948 long intergenic noncoding RNAs (lincRNAs). Among them, 263 lincRNAs were identified as novel noncoding transcripts in our data. By comparing transcriptome data among different human tissues, we observed substantial tissue specificity of RNA transcripts, both protein-coding genes and lincRNAs, in human aortic valve. Further analysis revealed that aortic valve-specific lincRNAs were more likely to be recently derived from repetitive elements in the primate lineage, but were less likely to be conserved at the nucleotide level. Expression profiling analysis showed significant lower expression levels of aortic valve-specific protein-coding genes and lincRNA genes, when compared with genes that were universally expressed in various tissues. Isoform-level expression analysis also showed that a majority of mRNA genes had a major isoform expressed in the human aortic valve. To our knowledge, this is the first comparative transcriptome analysis between human aortic valve and other human tissues. Our results are helpful to understand the transcriptome diversity of human tissues and the underlying mechanisms that drive tissue specificity of protein-coding genes and lincRNAs in human aortic valve.

SUBMITTER: Wang J

PROVIDER: S-EPMC4968975 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Comparative Transcriptome Analysis Reveals Substantial Tissue Specificity in Human Aortic Valve.

Wang Jun J Wang Ying Y Gu Weidong W Ni Buqing B Sun Haoliang H Yu Tong T Gu Wanjun W Chen Liang L Shao Yongfeng Y

Evolutionary bioinformatics online 20160731

RNA sequencing (RNA-seq) has revolutionary roles in transcriptome identification and quantification of different types of tissues and cells in many organisms. Although numerous RNA-seq data derived from many types of human tissues and cell lines, little is known on the transcriptome repertoire of human aortic valve. In this study, we sequenced the total RNA prepared from two calcified human aortic valves and reported the whole transcriptome of human aortic valve. Integrating RNA-seq data of 13 h ...[more]

PMID: 27493474

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Project description:Recent studies indicated that small calcified particles observable by scanning electron microscopy (SEM) may initiate calcification in cardiovascular tissues. We hypothesized that if the calcified particles precede gross calcification observed in calcific aortic valve disease (CAVD), they would exhibit a regional asymmetric distribution associated with CAVD development, which always initiates at the base of aortic valve leaflets adjacent to the aortic outflow in a region known as the fibrosa. Testing this hypothesis required counting the calcified particles in histological sections of aortic valve leaflets. SEM images, however, do not provide high contrast between components within images, making the identification and quantification of particles buried within tissue extracellular matrix difficult. We designed a new unique pattern-matching based technique to allow for flexibility in recognizing particles by creating a gap zone in the detection criteria that decreased the influence of non-particle image clutter in determining whether a particle was identified. We developed this flexible pattern particle-labeling (FpPL) technique using synthetic test images and human carotid artery tissue sections. A conventional image particle counting method (preinstalled in ImageJ) did not properly recognize small calcified particles located in noisy images that include complex extracellular matrix structures and other commonly used pattern-matching methods failed to detect the wide variation in size, shape, and brightness exhibited by the particles. Comparative experiments with the ImageJ particle counting method demonstrated that our method detected significantly more (p < 2 × 10-7) particles than the conventional method with significantly fewer (p < 0.0003) false positives and false negatives (p < 0.0003). We then applied the FpPL technique to CAVD leaflets and showed a significant increase in detected particles in the fibrosa at the base of the leaflets (p < 0.0001), supporting our hypothesis. The outcomes of this study are twofold: (1) development of a new image analysis technique that can be adapted to a wide range of applications and (2) acquisition of new insight on potential early mediators of calcification in CAVD.

Project description:BackgroundAscending thoracic aortic aneurysm (ATAA) is caused by the progressive weakening and dilatation of the aortic wall and can lead to aortic dissection, rupture, and other life-threatening complications. To improve our understanding of ATAA pathogenesis, we aimed to comprehensively characterize the cellular composition of the ascending aortic wall and to identify molecular alterations in each cell population of human ATAA tissues.MethodsWe performed single-cell RNA sequencing analysis of ascending aortic tissues from 11 study participants, including 8 patients with ATAA (4 women and 4 men) and 3 control subjects (2 women and 1 man). Cells extracted from aortic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster identification. ATAA-related changes were then examined by comparing the proportions of each cell type and the gene expression profiles between ATAA and control tissues. We also examined which genes may be critical for ATAA by performing the integrative analysis of our single-cell RNA sequencing data with publicly available data from genome-wide association studies.ResultsWe identified 11 major cell types in human ascending aortic tissue; the high-resolution reclustering of these cells further divided them into 40 subtypes. Multiple subtypes were observed for smooth muscle cells, macrophages, and T lymphocytes, suggesting that these cells have multiple functional populations in the aortic wall. In general, ATAA tissues had fewer nonimmune cells and more immune cells, especially T lymphocytes, than control tissues did. Differential gene expression data suggested the presence of extensive mitochondrial dysfunction in ATAA tissues. In addition, integrative analysis of our single-cell RNA sequencing data with public genome-wide association study data and promoter capture Hi-C data suggested that the erythroblast transformation-specific related gene(ERG) exerts an important role in maintaining normal aortic wall function.ConclusionsOur study provides a comprehensive evaluation of the cellular composition of the ascending aortic wall and reveals how the gene expression landscape is altered in human ATAA tissue. The information from this study makes important contributions to our understanding of ATAA formation and progression.

Project description:The hallmarks of calcific aortic valve disease (CAVD), an active and regulated process involving the creation of calcium nodules, lipoprotein accumulation, and chronic inflammation, are the significant changes that occur in the composition, organization, and mechanical properties of the extracellular matrix (ECM) of the aortic valve (AV). Most research regarding CAVD is based on experiments using two-dimensional (2D) cell culture or artificially created three-dimensional (3D) environments of valvular interstitial cells (VICs). Because the valvular ECM has a powerful influence in regulating pathological events, we developed an in vitro AV tissue culture model, which is more closely able to mimic natural conditions to study cellular responses underlying CAVD. AV leaflets, isolated from the hearts of 6-8-month-old sheep, were fixed with needles on silicon rubber rings to achieve passive tension and treated in vitro under pro-degenerative and pro-calcifying conditions. The degeneration of AV leaflets progressed over time, commencing with the first visible calcified domains after 14 d and winding up with the distinct formation of calcium nodules, heightened stiffness, and clear disruption of the ECM after 56 d. Both the expression of pro-degenerative genes and the myofibroblastic differentiation of VICs were altered in AV leaflets compared to that in VIC cultures. In this study, we have established an easily applicable, reproducible, and cost-effective in vitro AV tissue culture model to study pathological mechanisms underlying CAVD. The valvular ECM and realistic VIC-VEC interactions mimic natural conditions more closely than VIC cultures or 3D environments. The application of various culture conditions enables the examination of different pathological mechanisms underlying CAVD and could lead to a better understanding of the molecular mechanisms that lead to VIC degeneration and AS. Our model provides a valuable tool to study the complex pathobiology of CAVD and can be used to identify potential therapeutic targets for slowing disease progression.

Dataset Information

Comparative Transcriptome Analysis Reveals Substantial Tissue Specificity in Human Aortic Valve.

Publications

Comparative Transcriptome Analysis Reveals Substantial Tissue Specificity in Human Aortic Valve.

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