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Distinguishing human cell types based on housekeeping gene signatures.
- Source :
-
Stem cells (Dayton, Ohio) [Stem Cells] 2012 Mar; Vol. 30 (3), pp. 580-4. - Publication Year :
- 2012
-
Abstract
- 'In this report, we use single cell gene expression to identify transcriptional patterns emerging during the differentiation of human embryonic stem cells (hESCs) into the endodermal lineage. Endoderm-specific transcripts are highly variable between individual CXCR4(+) endodermal cells, suggesting that either the cells generated from in vitro differentiation are distinct or that these embryonic cells tolerate a high degree of transcript variability. Housekeeping transcripts, on the other hand, are far more consistently expressed within the same cellular population. However, when we compare the levels of housekeeping transcripts between hESCs and derived endoderm, patterns emerge that can be used to clearly separate the two embryonic cell types. We further compared four additional human cell types, including 293T, induced pluripotent stem cell (iPSC), HepG2, and endoderm-derived iPSC. In each case, the relative levels of housekeeping transcripts defined a particular cell fate. Interestingly, we find that three transcripts, LDHA, NONO, and ACTB, contribute the most to this diversity and together serve to segregate all six cell types. Overall, this suggests that levels of housekeeping transcripts, which are expressed within all cells, can be leveraged to distinguish between human cell types and thus may serve as important biomarkers for stem cell biology and other disciplines.<br /> (Copyright © 2011 AlphaMed Press.)
- Subjects :
- Anthropology, Cultural
Antigens, Differentiation genetics
Antigens, Differentiation metabolism
Cell Differentiation
Embryonic Stem Cells classification
Embryonic Stem Cells metabolism
Embryonic Stem Cells physiology
Endoderm cytology
Endoderm metabolism
Gene Expression Profiling
Humans
Induced Pluripotent Stem Cells classification
Induced Pluripotent Stem Cells metabolism
Induced Pluripotent Stem Cells physiology
Single-Cell Analysis
Transcription, Genetic
Genes, Essential
Subjects
Details
- Language :
- English
- ISSN :
- 1549-4918
- Volume :
- 30
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Stem cells (Dayton, Ohio)
- Publication Type :
- Academic Journal
- Accession number :
- 22162332
- Full Text :
- https://doi.org/10.1002/stem.1009