Dataset Information

Comparative transcriptomic analysis of multiple cardiovascular fates from embryonic stem cells predicts novel regulators in human cardiogenesis.

ABSTRACT: Dissecting the gene expression programs which control the early stage cardiovascular development is essential for understanding the molecular mechanisms of human heart development and heart disease. Here, we performed transcriptome sequencing (RNA-seq) of highly purified human Embryonic Stem Cells (hESCs), hESC-derived Multipotential Cardiovascular Progenitors (MCPs) and MCP-specified three cardiovascular lineages. A novel algorithm, named as Gene Expression Pattern Analyzer (GEPA), was developed to obtain a refined lineage-specificity map of all sequenced genes, which reveals dynamic changes of transcriptional factor networks underlying early human cardiovascular development. Moreover, our GEPA predictions captured ~90% of top-ranked regulatory cardiac genes that were previously predicted based on chromatin signature changes in hESCs, and further defined their cardiovascular lineage-specificities, indicating that our multi-fate comparison analysis could predict novel regulatory genes. Furthermore, GEPA analysis revealed the MCP-specific expressions of genes in ephrin signaling pathway, positive role of which in cardiomyocyte differentiation was further validated experimentally. By using RNA-seq plus GEPA workflow, we also identified stage-specific RNA splicing switch and lineage-enriched long non-coding RNAs during human cardiovascular differentiation. Overall, our study utilized multi-cell-fate transcriptomic comparison analysis to establish a lineage-specific gene expression map for predicting and validating novel regulatory mechanisms underlying early human cardiovascular development.

SUBMITTER: Li Y

PROVIDER: S-EPMC4440522 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparative transcriptomic analysis of multiple cardiovascular fates from embryonic stem cells predicts novel regulators in human cardiogenesis.

Li Yang Y Lin Bo B Yang Lei L

Scientific reports 20150521

Dissecting the gene expression programs which control the early stage cardiovascular development is essential for understanding the molecular mechanisms of human heart development and heart disease. Here, we performed transcriptome sequencing (RNA-seq) of highly purified human Embryonic Stem Cells (hESCs), hESC-derived Multipotential Cardiovascular Progenitors (MCPs) and MCP-specified three cardiovascular lineages. A novel algorithm, named as Gene Expression Pattern Analyzer (GEPA), was develope ...[more]

PMID: 25997157

Similar Datasets

Project description:Cardiac development is a complex process resulting in an integrated, multilineage tissue with developmental corruption in early embryogenesis leading to congenital heart disease. Interrogation of individual genes has provided the backbone for cardiac developmental biology, yet a comprehensive transcriptome derived from natural cardiogenesis is required to gauge innate developmental milestones.Stage-specific cardiac structures were dissected from 8 distinctive mouse embryonic time points to produce genome-wide expressome analysis across cardiogenesis. With reference to this native cardiogenic expression roadmap, divergent induced pluripotent stem cell-derived cardiac expression profiles were mapped from procardiogenic 3-factor (SOX2, OCT4, KLF4) and less-cardiogenic 4-factor (plus c-MYC) reprogrammed cells. Expression of cardiac-related genes from 3-factor-induced pluripotent stem cell differentiated in vitro at days 5 and 11 and recapitulated expression profiles of natural embryos at days E7.5-E8.5 and E14.5-E18.5, respectively. By contrast, 4-factor-induced pluripotent stem cells demonstrated incomplete cardiogenic gene expression profiles beginning at day 5 of differentiation. Differential gene expression within the pluripotent state revealed 23 distinguishing candidate genes among pluripotent cell lines with divergent cardiogenic potentials. A confirmed panel of 12 genes, differentially expressed between high and low cardiogenic lines, was transformed into a predictive score sufficient to discriminate individual induced pluripotent stem cell lines according to relative cardiogenic potential.Transcriptome analysis attuned to natural embryonic cardiogenesis provides a robust platform to probe coordinated cardiac specification and maturation from bioengineered stem cell-based model systems. A panel of developmental-related genes allowed differential prognosis of cardiogenic competency, thus prioritizing cell lines according to natural blueprint to streamline functional applications.

Project description:Heart diseases are the most significant cause of morbidity and mortality in the world. De novo generated cardiomyocytes (CMs) are a great cellular source for cell-based therapy and other potential applications. Direct cardiac reprogramming is the newest method to produce CMs, known as induced cardiomyocytes (iCMs). During a direct cardiac reprogramming, also known as transdifferentiation, non-cardiac differentiated adult cells are reprogrammed to cardiac identity by forced expression of cardiac-specific transcription factors (TFs) or microRNAs. To this end, many different combinations of TFs (±microRNAs) have been reported for direct reprogramming of mouse or human fibroblasts to iCMs, although their efficiencies remain very low. It seems that the investigated TFs and microRNAs are not sufficient for efficient direct cardiac reprogramming and other cardiac specific factors may be required for increasing iCM production efficiency, as well as the quality of iCMs. Here, we analyzed gene expression data of cardiac fibroblast (CFs), iCMs and adult cardiomyocytes (aCMs). The up-regulated and down-regulated genes in CMs (aCMs and iCMs) were determined as CM and CF specific genes, respectively. Among CM specific genes, we found 153 transcriptional activators including some cardiac and non-cardiac TFs that potentially activate the expression of CM specific genes. We also identified that 85 protein kinases such as protein kinase D1 (PKD1), protein kinase A (PRKA), calcium/calmodulin-dependent protein kinase (CAMK), protein kinase C (PRKC), and insulin like growth factor 1 receptor (IGF1R) that are strongly involved in establishing CM identity. CM gene regulatory network constructed using protein kinases, transcriptional activators and intermediate proteins predicted some new transcriptional activators such as myocyte enhancer factor 2A (MEF2A) and peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1A), which may be required for qualitatively and quantitatively efficient direct cardiac reprogramming. Taken together, this study provides new insights into the complexity of cell fate conversion and better understanding of the roles of transcriptional activators, signaling pathways and protein kinases in increasing the efficiency of direct cardiac reprogramming and maturity of iCMs.

Dataset Information

Comparative transcriptomic analysis of multiple cardiovascular fates from embryonic stem cells predicts novel regulators in human cardiogenesis.

Publications

Comparative transcriptomic analysis of multiple cardiovascular fates from embryonic stem cells predicts novel regulators in human cardiogenesis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets