Study of stem cell function using microarray experiments

GeneChips in stem cell research

An understanding of the genes and signaling networks responsible for stem cell growth and differentiation will be essential for their ultimate therapeutic application. GeneChips are miniature platforms of nucleotides capable of monitoring the expression levels of almost every known and unknown gene. Performing a GeneChip experiment is like snapping a picture of a cell's mRNA (transcripts), thus giving a static view and measurement of gene expression inside the cell. Taking multiple "pictures" of stem cells as they grow and differentiate will provide insight into the genetic mechanisms of "stemness" or can be used to create "transcriptional signatures" to assess differentiation and variability between stem cell lines. The first half of this chapter covers the many components involved in a GeneChip experiment, illustrating the many variables at each step and describing a protocol for analysis that is inexpensive and requires minimal computer skills. The chapter then describes how researchers are currently applying GeneChips to stem cell biology. We conclude that the true potential of GeneChip technology lies in the in silico analysis-their integration and comparison of diverse data sets, where the biological questions are the driving force in the analysis.

Identification of novel pathway regulation during myogenic differentiation

Stem cell differentiation is governed by extracellular signals that activate intracellular networks (or pathways) to drive phenotypic specification. Using a novel gene clustering strategy we determined pathway relationships from a genome-wide transcriptional dataset of skeletal myoblast differentiation. Established myogenic pathways, including cell contractility and cell-cycle arrest, were predicted with extreme statistical significance (p approximately 0). In addition, gene sets associated with angiogenesis, neuronal activity, and mRNA splicing were regulated, exposing developmental and therapeutic implications. Acquisition of transcriptional data spanning the entire differentiation time course provided context for a dynamic landscape of functional pathway regulation. This novel perspective on myogenic cell differentiation revealed previously unrecognized patterns of regulation. We predict that similar analyses will facilitate ongoing efforts to define molecular mechanisms in other stem cell and developmental paradigms. Finally, by combining an iterative process of analysis with supplementation of novel pathways, this application may evolve into a powerful discovery tool.

Naturally occurring mutations in human mitochondrial pre-tRNASer(UCN) can affect the transfer ribonuclease Z cleavage site, processing kinetics, and substrate secondary structure

tRNAs are transcribed as precursors with a 5' end leader and a 3' end trailer. The 5' end leader is processed by RNase P, and in most organisms in all three kingdoms, transfer ribonuclease (tRNase) Z can endonucleolytically remove the 3' end trailer. Long ((L)) and short ((S)) forms of the tRNase Z gene are present in the human genome. tRNase Z(L) processes a nuclear-encoded pre-tRNA approximately 1600-fold more efficiently than tRNase Z(S) and is predicted to have a strong mitochondrial transport signal. tRNase Z(L) could, thus, process both nuclear- and mitochondrially encoded pre-tRNAs. More than 150 pathogenesis-associated mutations have been found in the mitochondrial genome, most of them in the 22 mitochondrially encoded tRNAs. All the mutations investigated in human mitochondrial tRNA(Ser(UCN)) affect processing efficiency, and some affect the cleavage site and secondary structure. These changes could affect tRNase Z processing of mutant pre-tRNAs, perhaps contributing to mitochondrial disease.

Identification of candidate regulators of embryonic stem cell differentiation by comparative phosphoprotein affinity profiling

Embryonic stem cells are a unique cell population capable both of self-renewal and of differentiation into all tissues in the adult organism. Despite the central importance of these cells, little information is available regarding the intracellular signaling pathways that govern self-renewal or early steps in the differentiation program. Embryonic stem cell growth and differentiation correlates with kinase activities, but with the exception of the JAK/STAT3 pathway, the relevant substrates are unknown. To identify candidate phosphoproteins with potential relevance to embryonic stem cell differentiation, a systems biology approach was used. Proteins were purified using phosphoprotein affinity columns, then separated by two-dimensional gel electrophoresis, and detected by silver stain before being identified by tandem mass spectrometry. By comparing preparations from undifferentiated and differentiating mouse embryonic stem cells, a set of proteins was identified that exhibited altered post-translational modifications that correlated with differentiation state. Evidence for altered post-translational modification included altered gel mobility, altered recovery after affinity purification, and direct mass spectra evidence. Affymetrix microarray analysis indicated that gene expression levels of these same proteins had minimal variability over the same differentiation period. Bioinformatic annotations indicated that this set of proteins is enriched with chromatin remodeling, catabolic, and chaperone functions. This set of candidate phosphoprotein regulators of stem cell differentiation includes products of genes previously noted to be enriched in embryonic stem cells at the mRNA expression level as well as proteins not associated previously with stem cell differentiation status.

Inconsistencies over time in 5% of NetAffx probe-to-gene annotations

Background

DNA microarray probes are designed to match particular mRNA transcripts, often based on expressed sequences like ESTs, or cDNAs, many times incomplete. As a result, the relations between probes and genes can change as the sequence data are updated. However, it is frequent that the reported results of microarray analyses are given just as lists of genes without any reference to the underlying probes.

Results

We show for a particular commercial microarray design that the number of probes associated to some genes change with time. These changes concern approximately 5% of the probe sets across the history of annotation releases over a two year span.

Conclusion

We recommend to report probe set identifiers when publishing microarray results, and to submit those analyses to microarray public databases to ensure that the interpretation of the data is updated with the latest set of annotations.