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Increased Genomic Integrity of an Improved Protein-Based Mouse Induced Pluripotent Stem Cell Method Compared With Current Viral-Induced Strategies

Overview of attention for article published in Stem Cells Translational Medicine, April 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

blogs
1 blog
twitter
4 tweeters

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
15 Mendeley
citeulike
1 CiteULike
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Title
Increased Genomic Integrity of an Improved Protein-Based Mouse Induced Pluripotent Stem Cell Method Compared With Current Viral-Induced Strategies
Published in
Stem Cells Translational Medicine, April 2014
DOI 10.5966/sctm.2013-0149
Pubmed ID
Authors

Hansoo Park, Dohoon Kim, Chun-Hyung Kim, Ryan E. Mills, Mi-Yoon Chang, Rebecca Cheryl Iskow, Sanghyeok Ko, Jung-Il Moon, Hyun Woo Choi, Paulo Sng Man Yoo, Jeong Tae Do, Min-Joon Han, Eun Gyo Lee, Joon Ki Jung, Chengsheng Zhang, Robert Lanza, Kwang-Soo Kim

Abstract

It has recently been shown that genomic integrity (with respect to copy number variants [CNVs]) is compromised in human induced pluripotent stem cells (iPSCs) generated by viral-based ectopic expression of specific transcription factors (e.g., Oct4, Sox2, Klf4, and c-Myc). However, it is unclear how different methods for iPSC generation compare with one another with respect to CNV formation. Because array-based methods remain the gold standard for detecting unbalanced structural variants (i.e., CNVs), we have used this approach to comprehensively identify CNVs in iPSC as a proxy for determining whether our modified protein-based method minimizes genomic instability compared with retro- and lentiviral methods. In this study, we established an improved method for protein reprogramming by using partially purified reprogramming proteins, resulting in more efficient generation of iPSCs from C57/BL6J mouse hepatocytes than using protein extracts. We also developed a robust and unbiased 1 M custom array CGH platform to identify novel CNVs and previously described hot spots for CNV formation, allowing us to detect CNVs down to the size of 1.9 kb. The genomic integrity of these protein-based mouse iPSCs (p-miPSCs) was compared with miPSCs developed from viral-based strategies (i.e., retroviral: retro-miPSCs or lentiviral: lenti-miPSCs). We identified an increased CNV content in lenti-miPSCs and retro-miPSCs (29∼53 CNVs) compared with p-miPSCs (9∼10 CNVs), indicating that our improved protein-based reprogramming method maintains genomic integrity better than current viral reprogramming methods. Thus, our study, for the first time to our knowledge, demonstrates that reprogramming methods significantly influence the genomic integrity of resulting iPSCs.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Student > Doctoral Student 3 20%
Researcher 2 13%
Student > Master 1 7%
Lecturer 1 7%
Other 2 13%
Unknown 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 60%
Biochemistry, Genetics and Molecular Biology 5 33%
Unknown 1 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 30 April 2014.
All research outputs
#1,301,886
of 12,509,879 outputs
Outputs from Stem Cells Translational Medicine
#220
of 991 outputs
Outputs of similar age
#23,159
of 190,479 outputs
Outputs of similar age from Stem Cells Translational Medicine
#13
of 32 outputs
Altmetric has tracked 12,509,879 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 991 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.9. This one has done well, scoring higher than 77% of its peers.
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 190,479 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.