Cor.At RNA (Day 2 & 14)
Gene-expression profiles represent a powerful tool to identify and and evaluate relevant targets for drug development strategies. However, the analysis of profiles generated from primary tissue is often difficult and not comprehensive because tissue preparations do not represent SINGLE cell types. In contrast to primary tissue in which cardiomyocytes represent only a proportion of 30-40% of total cells, the RNA from the Cor.At cells provides an ultimately pure and comprehensive source for gene expression analysis.
Cor.At® RNA is isolated from cultures of different developmental stages. We demonstrated that maturation occurs in vitro within a 2 week period. This fact enables researches to compare gene-expression profiles of a "new-born" phenotype versus an "adult" phenotype.
Gene expression analysis in a longitudinal study
To gain greater insight into the molecular characteristics of mouse ESC-derived cardiomyocytes, a detailed gene expression analysis was performed. To this end, RNA was prepared on daily basis for 36 consecutive days at different stages starting from cultures of undifferentiated ESCs, post embryonic body formation, early stages of the differentiation process, cardiomyocyte development stage, the selection period with puromycin and from prolonged culture of monolayers of pure cardiomyocytes. Real-time PCR was performed with RNA samples collected from all conditions. Based on the gene expression data, the transgenic ESC-derived cardiomyocytes express all tested cardiomyocyte marker genes, ion channels, and connexins involved in the formation of gap junctions to allow synchronized contraction of cardiomyocytes.
An example is depicted below
Advantages Cor.At RNA
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100% pure cardiomyocyte RNA.
- Standard protocols for many applications availableAvailable from two cardiomyocyte developmental stages (Day 2 and 14)
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Continuous supply of large lot sizes through highly controlled, standardized production process.
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Uniform gene expression patterns from lot to lot.
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Consistent performance – large lot sizes with minimal lot to lot variation.
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Predictive model – relevant cardiac physiology.