Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

The NIH Human Pluripotent Stem Cell Database (Agilent, miRNA)

ABSTRACT: MicroRNA profiling was performed on RNA samples matched to those included in the NIH Human Pluripotent Stem Cell Database (Series GSE32923). Twenty undifferentiated human embryonic stem cell lines and 4 human tissues were analyzed. Expanded descriptions of methods used are available at: http://stemcelldb.nih.gov. 49 samples: 38 human ESC (UNDIFFerentiated), 1 human Brain, 1 human Heart, 1 human Liver, 1 human Ovary and 7 processing controls (UniRef).

ORGANISM(S): Homo sapiens

SUBMITTER: Kory Johnson

PROVIDER: E-GEOD-34199 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

StemCellDB: the human pluripotent stem cell database at the National Institutes of Health.

Mallon Barbara S BS Chenoweth Josh G JG Johnson Kory R KR Hamilton Rebecca S RS Tesar Paul J PJ Yavatkar Amarendra S AS Tyson Leonard J LJ Park Kyeyoon K Chen Kevin G KG Fann Yang C YC McKay Ronald D G RD

Stem cell research 20120926 1

Much of the excitement generated by induced pluripotent stem cell technology is concerned with the possibility of disease modeling as well as the potential for personalized cell therapy. However, to pursue this it is important to understand the 'normal' pluripotent state including its inherent variability. We have performed various molecular profiling assays for 21 hESC lines and 8 hiPSC lines to generate a comprehensive snapshot of the undifferentiated state of pluripotent stem cells. Analysis ...[more]

PMID: 23117585

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Project description:The MLL-AF4 fusion gene is a hallmark genomic aberration in high-risk acute lymphoblastic leukemia in infants. Although it is well-established that MLL-AF4 arises pre-natally during human development, its effects on hematopoietic development in utero remains unexplored. We have created a human-specific in vitro system to study early hemato-endothelial development in MLL-AF4-expressing human embryonic stem cells (hESCs). Differentiation and functional studies as well as clonal analyses and gene expression profiling reveal that expression of MLL-AF4 in hESCs has a phenotypic, functional and gene expression impact. It enhances the specification of hemogenic precursors from hESCs and impairs further hematopoietic commitment of these precursors in favour of the endothelial cell fate. Similar to that reported in cord blood CD34+ hematopoietic stem/progenitor cells (HSPCs), MLL-AF4 expression is not sufficient to transform hESC-derived hematopoietic cells in vitro or in vivo, indicating that additional events may be required to initiate leukemogenesis or that embryonic hematopoiesis is not the appropriate human cellular target for MLL-AF4-mediated leukemogenesis. This work illustrates how hESCs can provide unique insights into human development and further our understanding of how leukemic fusion genes known to arise pre-natally regulate human embryonic hematopoietic specification. MLL is involved in transcriptional regulation and most MLL translocations appear to result in increased expression of Hox genes and hematopoietic genes. We therefore assessed the impact of MLL-AF4 expression on the transcriptome of hESCs. Gene expression profiling performed in MLL-AF4 hESCs revealed that MLL-AF4 preferentially activates transcription. 1826 out of the 3001 genes (61%) expressed were up-regulated in MLL-AF4 hESCs. Human ESC samples were collected during the exponential cell growth phase and stabilized in RNA later. 500 ng of each total RNA sample was labelled with Cy3 using the Quick-Amp Labelling kit and hybridized with the Gene Expression Hybridization kit to a Whole Human Genome Oligo Microarray (Agilent Technologies) following the Manufacturer’s instructions. Each cell line was analyzed as independent duplicates. NEO-expressing (empty lentivector) hESC line was used as the baseline.

Dataset Information

The NIH Human Pluripotent Stem Cell Database (Agilent, miRNA)

Publications

StemCellDB: the human pluripotent stem cell database at the National Institutes of Health.

Similar Datasets

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