Högskolan i Skövde

Human embryonic stem cells (hESCs) represent populations of pluripotent undifferentiated cells with unlimited replication capacity which can be coaxed to differentiate into a variety of specialized cells. As a result, there is great hope that hESCs will be extremely useful by providing platforms for various in vitro applications (e.g. in drug discovery) as well as for future use of hESCs and their differentiated progeny in cell replacement therapies. In order to realize the potential of hESCs, it is necessary to gain much deeper knowledge about the processes that govern differentiation of these cells.

In recent years, significant progress towards understanding cellular differentiation has been fuelled, in part, by studying gene expression using microarrays. In this large scale studies, statistical methods are used to normalize the gene expression data and render comparisons between different samples. In lower throughput analyses, RNA levels in hESCs are also measured using RT-PCR requiring normalization of the gene expression data to adequately correct for inter-sample variation. In general, investigators have used the traditional housekeeping genes (HKGs) (e.g. GAPDH, b-tubulin, b-actin) in studies of hESCs. HKGs are involved in basic functions needed for the sustenance of the cell and are assumed to be constitutively expressed at a constant level. Based on these features, HKGs are frequently used for normalization of gene expression data. However, it is well known that the expression of several of these genes vary considerably in adult tissues and their suitability as HKGs in hESCs remains to be proven. In this regard, the RNA levels of HPRT and b-tubulin were shown to vary substantially in differentiating mouse ESCs.

In the present study, we used the CodeLinkTM Gene Expression Bioarray system to interrogate changes in gene expression occurring during differentiation of hESCs. Notably, in the three hESC lines used for the study, we observed that the RNA levels of 56 frequently used HKGs varied to a degree that rendered them inappropriate as reference genes. Therefore, we defined a novel set of HKGs specifically for hESCs. Here we present a comprehensive list of 292 genes that are stably expressed (coefficient of variation<20%) in differentiating hESCs. These genes were further grouped into high, medium, and low expressed genes. The expression patterns of these novel HKGs show very little overlap with results obtained from somatic cells and tissues. We further explored the stability of this novel set of HKGs in independent, publicly available gene expression data from hESCs and observed substantial similarities in terms of stably expressed genes. Taken together, these results suggest that hESCs have a unique HKG signature and underscore the necessity to validate the expression profiles of putative HKGs. In addition, the novel set of identified HKGs can preferentially be used as controls in gene expression analyses of differentiating hESCs.