Data · dataset · 2015
Nuclear transcriptome profiling of induced pluripotent stem cells and embryonic stem cells identify non-coding loci resistant to reprogramming
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Identification of functionally relevant differences between induced pluripotent stem cells (iPSC) and reference embryonic stem cells (ESC) remains a central question for therapeutic applications.
Description
Differences in gene expression between iPSC and ESC have been examined by microarray and more recently with RNA-SEQ technologies. We here report an in depth analyses of nuclear and cytoplasmic transcriptomes, using the CAGE (cap analysis of gene expression) technology, for 5 iPSC clones derived from mouse lymphocytes B and 3 ESC lines.
This approach reveals nuclear transcriptomes significantly more complex in ESC than in iPSC. Hundreds of yet not annotated putative non-coding RNAs and enhancer-associated transcripts specifically transcribed in ESC have been detected and supported with epigenetic and chromatin-chromatin interactions data. We identified super-enhancers transcriptionally active specifically in ESC and associated with genes implicated in the maintenance of pluripotency.
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Similarly, we detected non-coding transcripts of yet unknown function being regulated by ESC specific super-enhancers. Taken together, these results demonstrate that current protocols of iPSC reprogramming do not trigger activation of numerous cis -regulatory regions. It thus reinforces the need for already suggested deeper monitoring of the non-coding transcriptome when characterizing iPSC clones.
Such differences in regulatory transcript expression may indeed impact their potential for clinical applications.
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- Repository landing page tandf.figshare.com/articles/dataset/Nuclear_transcriptome_profiling_of_induced_pl… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1304578 ↗
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Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.4161/15384101.2014.988031 doi.org/10.4161/15384101.2014.988031 ↗
publication · from DataCite
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- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1304578 ↗
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Topics
- Stated by source
- Biological sciences · Computer and information sciences · Earth and related environmental sciences
- From keywords
- Cancer · Medicine & Health
- Inferred from text
- RNA sequencing 65%
Provenance · 1 source records, 14 field assertions
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|---|---|---|---|
| DataCite | 10.6084/m9.figshare.1304578 | 14 d ago | JSON v1 |
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