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accession-icon SRP100157
Coupling shRNA screening with single-cell RNA-Seq identifies mechanisms regulating senescence during reprogramming
  • organism-icon Homo sapiens
  • sample-icon 376 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Ectopic expression of the transcription factors Oct4, Sox2, Klf4 and c-Myc (OSKM) can reprogram somatic cells into induced pluripotent stem cells (iPSCs). These iPSCs are highly similar to embryonic stem cells and can be used for regenerative medicine, drug screening and disease modelling. Despite recent advances, reprogramming is a slow and inefficient process. This suggests that there are several safeguarding mechanisms to counteract cell fate conversion. Cellular senescence is one of these barriers, which is mediated through activation of the tumour suppressors p53/p21CIP1, p15INK4b and p16INK4a. In this study, we have screened for shRNAs blunting reprogramming-induced senescence. We integrated single-cell RNA sequencing (scRNA-Seq) with shRNA screening to investigate the mechanism of action of the identified candidates. Overall design: 376 samples: 280 IMR90 cells expressing OSKM and shRNA library derived from the shRNA screen (bypassing senescence), 64 OSKM-expressing IMR90 cells (senescent), 32 IMR90 cells expressing control vector

Publication Title

Coupling shRNA screens with single-cell RNA-seq identifies a dual role for mTOR in reprogramming-induced senescence.

Sample Metadata Fields

Specimen part, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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