Transcriptomics

Dataset Information

5

Global gene expression profiles of iPSC from SMA patient, unaffected father and iPS 19.9 compared to transcriptomic data obtained by corresponding fibroblasts


ABSTRACT: Spinal Muscular Atrophy (SMA) is an autosomal recessive motor neuron disease and is the second most common genetic disorder leading to death in childhood. Motoneurons derived from induced pluripotent stem cells (iPS cells) obtained by reprogramming SMA patient and his healthy father fibroblasts, and genetically corrected SMA-iPSC obtained converting SMN2 into SMN1 with target gene correction (TGC), were used to study gene expression and splicing events linked to pathogenetic mechanisms. Microarray technology was used to assess global gene expression profiles of iPSC from SMA patient, unaffected father and iPS 19.9 (Prof. J. Thomson's lab) compared to transcriptomic data obtained by corresponding fibroblasts. The microarray data derived from three different individuals: SMA patient, healthy father and control iPS cells (19.9). We analyzed iPSC from SMA patient (n=2), iPS- from healthy father (n=1) and iPS-19.9 from Prof. Thomson's lab (n=3). The expression profile was compared to SMA patient's fibroblasts (n=2) and healthy father's fibroblasts (n=1)

ORGANISM(S): Homo sapiens  

SUBMITTER: Giulietta Riboldi   Dario Ronchi  Stefania Corti 

PROVIDER: E-GEOD-27206 | ArrayExpress | 2013-01-04

SECONDARY ACCESSION(S): GSE27206PRJNA141985

REPOSITORIES: GEO, ArrayExpress

altmetric image

Publications


Spinal muscular atrophy (SMA) is among the most common genetic neurological diseases that cause infant mortality. Induced pluripotent stem cells (iPSCs) generated from skin fibroblasts from SMA patients and genetically corrected have been proposed to be useful for autologous cell therapy. We generated iPSCs from SMA patients (SMA-iPSCs) using nonviral, nonintegrating episomal vectors and used a targeted gene correction approach based on single-stranded oligonucleotides to convert the survival mo  ...[more]

Similar Datasets

| GSE27206 | GEO
2013-01-04 | E-GEOD-27205 | ArrayExpress
| PRJNA141985 | ENA
| GSE13828 | GEO
| GSE61390 | GEO
2009-01-13 | E-GEOD-13828 | ArrayExpress
| GSE104499 | GEO
| PRJNA141983 | ENA
| GSE62935 | GEO
2018-12-31 | E-MTAB-4964 | ArrayExpress