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Combined cistrome and transcriptome analysis of SKI in AML cells identifies SKI as a co-repressor for RUNX1

Overview of attention for article published in Nucleic Acids Research, February 2018
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Title
Combined cistrome and transcriptome analysis of SKI in AML cells identifies SKI as a co-repressor for RUNX1
Published in
Nucleic Acids Research, February 2018
DOI 10.1093/nar/gky119
Pubmed ID
Authors

Christine Feld, Peeyush Sahu, Miriam Frech, Florian Finkernagel, Andrea Nist, Thorsten Stiewe, Uta-Maria Bauer, Andreas Neubauer

Abstract

SKI is a transcriptional co-regulator and overexpressed in various human tumors, for example in acute myeloid leukemia (AML). SKI contributes to the origin and maintenance of the leukemic phenotype. Here, we use ChIP-seq and RNA-seq analysis to identify the epigenetic alterations induced by SKI overexpression in AML cells. We show that approximately two thirds of differentially expressed genes are up-regulated upon SKI deletion, of which >40% harbor SKI binding sites in their proximity, primarily in enhancer regions. Gene ontology analysis reveals that many of the differentially expressed genes are annotated to hematopoietic cell differentiation and inflammatory response, corroborating our finding that SKI contributes to a myeloid differentiation block in HL60 cells. We find that SKI peaks are enriched for RUNX1 consensus motifs, particularly in up-regulated SKI targets upon SKI deletion. RUNX1 ChIP-seq displays that nearly 70% of RUNX1 binding sites overlap with SKI peaks, mainly at enhancer regions. SKI and RUNX1 occupy the same genomic sites and cooperate in gene silencing. Our work demonstrates for the first time the predominant co-repressive function of SKI in AML cells on a genome-wide scale and uncovers the transcription factor RUNX1 as an important mediator of SKI-dependent transcriptional repression.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 17%
Researcher 3 13%
Student > Postgraduate 3 13%
Student > Bachelor 2 8%
Student > Doctoral Student 2 8%
Other 5 21%
Unknown 5 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 42%
Agricultural and Biological Sciences 4 17%
Medicine and Dentistry 2 8%
Computer Science 1 4%
Neuroscience 1 4%
Other 1 4%
Unknown 5 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 February 2018.
All research outputs
#14,377,572
of 23,025,074 outputs
Outputs from Nucleic Acids Research
#21,349
of 26,396 outputs
Outputs of similar age
#188,115
of 331,055 outputs
Outputs of similar age from Nucleic Acids Research
#152
of 230 outputs
Altmetric has tracked 23,025,074 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 26,396 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 230 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.