<p>Stem cells are cells that have a unique ability to divide for an indefinite period. Additionally, they can give rise to a plethora of specialized cell types. The advent of high-throughput technologies made it possible to investigate gene expression on a large scale. This enabled scientists to perform comprehensive gene profiling studies of stem cells. Several authors have suggested that there might be a common set of genes that control the stemness of stem cells. In this study, we suggest that ”stemness” genes that are related to ”stemness” characteristics show a statistically significant down-regulation between undifferentiated and differentiated cells. For this we have analyzed microarray data from five different cell lines and compared their global expression profiles. Common down-regulated transcripts among those data sets were de- rived by using a well-established gene expression analysis procedure called Significance Analysis of Microarrays. Since all three data sets were provided by Cellartis AB, the derived list of common transcripts was subsequently compared with an external study. Moreover, we also performed a comparison with down-regulated genes derived from mouse embryonic stem cells. This was done to determine if there is a common set of stemness genes even across distinct species. Re- sults were further evaluated using a comprehensive data-set from a study by Skottman et al. (2005). All results where compared uti- lizing using a range of false discovery rate threshold values and the results were subsequently used for gene ontology term enrichment. GO terms where utilized to functionally annotate and classify those embryonic stem cell transcripts, that were found to be common in all data-sets and identify over-represented biological processes related to those genes.</p>
Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:his-3509 |
Date | January 2009 |
Creators | Jurczak, Daniel |
Publisher | University of Skövde, School of Life Sciences |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, text |
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