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Genome edited sheep and cattle

Overview of attention for article published in Transgenic Research, September 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#24 of 942)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
policy
2 policy sources
twitter
7 X users
patent
8 patents
facebook
1 Facebook page

Citations

dimensions_citation
204 Dimensions

Readers on

mendeley
222 Mendeley
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Title
Genome edited sheep and cattle
Published in
Transgenic Research, September 2014
DOI 10.1007/s11248-014-9832-x
Pubmed ID
Authors

Chris Proudfoot, Daniel F. Carlson, Rachel Huddart, Charles R. Long, Jane H. Pryor, Tim J. King, Simon G. Lillico, Alan J. Mileham, David G. McLaren, C. Bruce A. Whitelaw, Scott C. Fahrenkrug

Abstract

Genome editing tools enable efficient and accurate genome manipulation. An enhanced ability to modify the genomes of livestock species could be utilized to improve disease resistance, productivity or breeding capability as well as the generation of new biomedical models. To date, with respect to the direct injection of genome editor mRNA into livestock zygotes, this technology has been limited to the generation of pigs with edited genomes. To capture the far-reaching applications of gene-editing, from disease modelling to agricultural improvement, the technology must be easily applied to a number of species using a variety of approaches. In this study, we demonstrate zygote injection of TALEN mRNA can also produce gene-edited cattle and sheep. In both species we have targeted the myostatin (MSTN) gene. In addition, we report a critical innovation for application of gene-editing to the cattle industry whereby gene-edited calves can be produced with specified genetics by ovum pickup, in vitro fertilization and zygote microinjection (OPU-IVF-ZM). This provides a practical alternative to somatic cell nuclear transfer for gene knockout or introgression of desirable alleles into a target breed/genetic line.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 222 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 <1%
Denmark 1 <1%
Uruguay 1 <1%
Brazil 1 <1%
Unknown 218 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 17%
Researcher 32 14%
Student > Master 32 14%
Student > Bachelor 27 12%
Other 9 4%
Other 28 13%
Unknown 56 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 92 41%
Biochemistry, Genetics and Molecular Biology 40 18%
Veterinary Science and Veterinary Medicine 13 6%
Engineering 7 3%
Medicine and Dentistry 4 2%
Other 14 6%
Unknown 52 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 01 December 2022.
All research outputs
#1,243,410
of 24,907,378 outputs
Outputs from Transgenic Research
#24
of 942 outputs
Outputs of similar age
#12,789
of 244,625 outputs
Outputs of similar age from Transgenic Research
#1
of 17 outputs
Altmetric has tracked 24,907,378 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 942 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has done particularly well, scoring higher than 97% 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 244,625 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.