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accession-icon SRP041752
An aging-like phenotype occurs in Tif1?-/- hematopoietic stem cells
  • organism-icon Mus musculus
  • sample-icon 49 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To determine whether an accelerated aging-like phenotype occurs in hematopoiesis of young Tif1?-/- mice (4 months old), we purified 200,000 hematopoietic stem cells (LSK: Lineage negative, Sca1+, c-Kit+) from Tif1?-/- mice and performed high-throughput mRNA sequencing (RNA-seq). We compared this transcriptome to physiological aging by creating two other RNAseq libraries from young (4 months old) and old (20 months old) wild type mice. Overall design: RNAseq study on young Tif1?-/- mice (4 months old), young wild type mice (4 months old) and old wild type mice (20 months old).

Publication Title

Tif1γ regulates the TGF-β1 receptor and promotes physiological aging of hematopoietic stem cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE92698
Precipitation of mRNAs by Ago2 and phosphorylation mutants
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

Argonaute (Ago) proteins associate with microRNAs (miRNAs), which guide them to complementary target mRNAs resulting in gene silencing.

Publication Title

Phosphorylation of Argonaute proteins affects mRNA binding and is essential for microRNA-guided gene silencing <i>in vivo</i>.

Sample Metadata Fields

Cell line

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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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