In this demonstration we show how GeneAnalytics can be used to determine the quality of tissue dissection and cell isolation procedures. As an example, we evaluate gene set of a dermal guard papilla cell population that was subjected to microarray following dissection and FACS isolation. Using GeneAnalytics, we revealed that the researchers may not have isolated a pure guard papilla cell population, since the sample is mostly express neuronal gene markers instead of specific dermal markers. This test case demonstrates how GeneAnalytics can identify impurities in cell populations, based on our manually curated, filtered and annotated gene expression data. As such, it is a powerful tool for assessing the efficacy of biological sample isolation.
In this demonstration we showcase how GeneAnalytics can be used to assess stem cell differentiation protocols and to evaluate the fate of derived cells, based on their gene expression profile. As an example we evaluate the differentiation reliability of two cases:
1) hepatocytes derived from human embryonic stem cells (hESCs) and 2) pancreatic progenitors derived from mouse embryonic stem cells (mESCs). GeneAnalytics results support the hepatic fate in the first case, based on a strong match to data sets and selective markers of liver cells. However, the pancreatic fate in the second case could not be assessed, but instead the results indicate for a mixed cell populations. These two examples demonstrate how GeneAnalytics can be used to evaluate the efficacy and reliability of protocols for stem cell differentiation. We highly recommend using GeneAnalytics to assess the outcomes of your cell differentiation procedures.
This demonstration showcase how GeneAnalytics can be used to assess stem cell derivatives and to provide further understanding of their potential function in health and disease. As an example, we analyze the gene expression signature of a specific epithelial stem cell population, derived from human iPSCs, following differentiation and FACS isolation. These cells can be further differentiated into functional keratinocytes. Based on gene expression signature, GeneAnalytics assessed this cell population to be primary keratinocytes. The tool also identified the cell's most significant selective markers and provided substantial insights into their role in forming the protective epidermis barrier in both health and disease. This case demonstrates how GeneAnalytics can easily help you to define functional roles for your sample based on specific gene sets.
This case demonstrates how GeneAnalytics can be applied toward drug discovery. A gene set associated with retinitis pigmentosa (RP), an inherited, degenerative eye disease, was analyzed for identification of target cells, mechanisms of action and potential drugs. Mature rod cells, which are the cells most significantly affected by RP, was the entity that most closely matched the analyzed gene set. Analysis of the subset of genes associated with RP and that matched to rod cells provided novel insight into mechanisms underlying RP and suggested potential therapeutic approaches such as reducing cyclic GMP levels and/or inducing phosphodiesterase activity. Such approaches may lead to methods that can prolong rod cell survival and improve retinal function in rod cells affected by RP. This case demonstrates how GeneAnalytics can rapidly shed light on disease mechanisms and suggest potential approaches for drug development.