Expression data during stem cell differentiation
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE6689 | GEO | 2008/01/07
SECONDARY ACCESSION(S): PRJNA99069
REPOSITORIES: GEO
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Project description:Stem cell development requires selection of specific genetic programs to direct cellular fate. Using microarray technology, we profile expression trends at selected timepoints during stem cell differentiation to characterize these changes. Experiment Overall Design: Total RNA was isolated using the Micro-to-Midi isolation kit (Invitrogen), and subjected to comparative gene expression profiling by labelled cRNA hybridization to the mouse genome 430 2.0 microarray (Affymetrix). Data acquired using the GeneChip Scanner 3000 was analyzed with the Genespring GX 7.3 microarray data software bioinformatics suite (Agilent Technologies) restricting the derived gene list to identify differentially expressed genes defined by a >1.5-fold difference and P<0.05. Data population sets were normalized to the undifferentiated phenotype, and quality filtered to eliminate background noise prior to hierarchical clustering.
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Project description:Pluripotent stem cells can be generated from somatic cells by using pure chemicals.However, the cell fate dynamics and molecular events that occur during the chemical reprogramming process remain unclear. In this study, we found that the chemical reprogramming process requires the early formation of extra-embryonic endoderm (XEN)-like cells and a late transition from XEN-like cells to CiPSCs, a new route that differs from the pathway of transcription factor-induced reprogramming. Moreover, by more precisely manipulating the cell fate transition in a step-wise manner through the XEN-like state, we identified small-molecule boosters and established a robust chemical reprogramming system, with a yield up to 1,000-fold greater than that of the previously reported protocol. These findings demonstrate that chemical reprogramming is a unique and promising approach in the future manipulation of cell fates. We analyzed the gene expression profiles of intermediate cells obtained from diferent timepoints during chemical reprogramming process,using RNA-Sequencing. Embryo-derived XEN cells (eXENs), chemically-derived eXEN cell lines (CeXENs), embryonic stem cells (ESCs) and chemically-induced pluripotent stem cells (CiPSCs) are used as controls.
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Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
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