↓ Skip to main content

Transcription factors interfering with dedifferentiation induce cell type-specific transcriptional profiles

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, April 2013
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
4 X users
facebook
1 Facebook page

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
156 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Transcription factors interfering with dedifferentiation induce cell type-specific transcriptional profiles
Published in
Proceedings of the National Academy of Sciences of the United States of America, April 2013
DOI 10.1073/pnas.1220200110
Pubmed ID
Authors

Takafusa Hikichi, Ryo Matoba, Takashi Ikeda, Akira Watanabe, Takuya Yamamoto, Satoko Yoshitake, Miwa Tamura-Nakano, Takayuki Kimura, Masayoshi Kamon, Mari Shimura, Koichi Kawakami, Akihiko Okuda, Hitoshi Okochi, Takafumi Inoue, Atsushi Suzuki, Shinji Masui

Abstract

Transcription factors (TFs) are able to regulate differentiation-related processes, including dedifferentiation and direct conversion, through the regulation of cell type-specific transcriptional profiles. However, the functional interactions between the TFs regulating different transcriptional profiles are not well understood. Here, we show that the TFs capable of inducing cell type-specific transcriptional profiles prevent the dedifferentiation induced by TFs for pluripotency. Of the large number of TFs expressed in a neural-lineage cell line, we identified a subset of TFs that, when overexpressed, strongly interfered with the dedifferentiation triggered by the procedure to generate induced pluripotent stem cells. This interference occurred through a maintenance mechanism of the cell type-specific transcriptional profile. Strikingly, the maintenance activity of the interfering TF set was strong enough to induce the cell line-specific transcriptional profile when overexpressed in a heterologous cell type. In addition, the TFs that interfered with dedifferentiation in hepatic-lineage cells involved TFs with known induction activity for hepatic-lineage cells. Our results suggest that dedifferentiation suppresses a cell type-specific transcriptional profile, which is primarily maintained by a small subset of TFs capable of inducing direct conversion. We anticipate that this functional correlation might be applicable in various cell types and might facilitate the identification of TFs with induction activity in efforts to understand differentiation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Japan 3 2%
Germany 1 <1%
France 1 <1%
Iran, Islamic Republic of 1 <1%
Portugal 1 <1%
Saudi Arabia 1 <1%
Spain 1 <1%
Unknown 143 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 26%
Student > Ph. D. Student 32 21%
Professor > Associate Professor 17 11%
Student > Master 16 10%
Student > Bachelor 8 5%
Other 27 17%
Unknown 15 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 83 53%
Biochemistry, Genetics and Molecular Biology 26 17%
Medicine and Dentistry 21 13%
Engineering 3 2%
Computer Science 2 1%
Other 6 4%
Unknown 15 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 17 April 2013.
All research outputs
#14,432,488
of 24,625,114 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#87,387
of 101,438 outputs
Outputs of similar age
#110,133
of 203,847 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#748
of 982 outputs
Altmetric has tracked 24,625,114 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 101,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.8. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 203,847 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 982 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.