Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of mouse multipotent adult progenitor cells


ABSTRACT: We compare the transcriptome of embryonic stem cells (ESCs), adult stem cells with apparent greater differentiation potential such as multipotent adult progenitor cells (MAPCs), mesenchymal stem cells (MSCs) and neurospheres (NS). Mouse and rat MAPCs were used in this study and two different array platforms (Affymetrix and NIA) were used for mouse samples. Experiment Overall Design: Three mRNA samples (biological replicates) per cell type taken at different passage number were compared. Cell types include mouse ESCs, mouse MSCs and three clones isolated using mouse MAPC culture condition: mMAPC-1, mMAPC-2 and mClone-3. mMAPC-1 and mClone-3 were obtained from same bone marrow isolation, mMAPC-2 was obtained in a different bone marrow isolation. Two clones derived from same rat bone marrow using rat MAPC culture conditions were compared. Three mRNA samples (biological replicates) per clone were taken at different passage numbers

ORGANISM(S): Mus musculus

SUBMITTER: Fernando Ulloa Montoya 

PROVIDER: E-GEOD-6933 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Comparative transcriptome analysis of embryonic and adult stem cells with extended and limited differentiation capacity.

Ulloa-Montoya Fernando F   Kidder Benjamin L BL   Pauwelyn Karen A KA   Chase Lucas G LG   Luttun Aernout A   Crabbe Annelies A   Geraerts Martine M   Sharov Alexei A AA   Piao Yulan Y   Ko Minoru S H MS   Hu Wei-Shou WS   Verfaillie Catherine M CM  

Genome biology 20070101 8


<h4>Background</h4>Recently, several populations of postnatal stem cells, such as multipotent adult progenitor cells (MAPCs), have been described that have broader differentiation ability than classical adult stem cells. Here we compare the transcriptome of pluripotent embryonic stem cells (ESCs), MAPCs, and lineage-restricted mesenchymal stem cells (MSCs) to determine their relationship.<h4>Results</h4>Applying principal component analysis, non-negative matrix factorization and k-means clusteri  ...[more]

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