↓ Skip to main content

Potential of promotion of alleles by genome editing to improve quantitative traits in livestock breeding programs

Overview of attention for article published in Genetics Selection Evolution, July 2015
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 822)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
3 news outlets
twitter
22 X users

Citations

dimensions_citation
126 Dimensions

Readers on

mendeley
182 Mendeley
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
Potential of promotion of alleles by genome editing to improve quantitative traits in livestock breeding programs
Published in
Genetics Selection Evolution, July 2015
DOI 10.1186/s12711-015-0135-3
Pubmed ID
Authors

Janez Jenko, Gregor Gorjanc, Matthew A Cleveland, Rajeev K Varshney, C. Bruce A Whitelaw, John A Woolliams, John M Hickey

Abstract

Genome editing (GE) is a method that enables specific nucleotides in the genome of an individual to be changed. To date, use of GE in livestock has focussed on simple traits that are controlled by a few quantitative trait nucleotides (QTN) with large effects. The aim of this study was to evaluate the potential of GE to improve quantitative traits that are controlled by many QTN, referred to here as promotion of alleles by genome editing (PAGE). Multiple scenarios were simulated to test alternative PAGE strategies for a quantitative trait. They differed in (i) the number of edits per sire (0 to 100), (ii) the number of edits per generation (0 to 500), and (iii) the extent of use of PAGE (i.e. editing all sires or only a proportion of them). The base line scenario involved selecting individuals on true breeding values (i.e., genomic selection only (GS only)-genomic selection with perfect accuracy) for several generations. Alternative scenarios complemented this base line scenario with PAGE (GS + PAGE). The effect of different PAGE strategies was quantified by comparing response to selection, changes in allele frequencies, the number of distinct QTN edited, the sum of absolute effects of the edited QTN per generation, and inbreeding. Response to selection after 20 generations was between 1.08 and 4.12 times higher with GS + PAGE than with GS only. Increases in response to selection were larger with more edits per sire and more sires edited. When the total resources for PAGE were limited, editing a few sires for many QTN resulted in greater response to selection and inbreeding compared to editing many sires for a few QTN. Between the scenarios GS only and GS + PAGE, there was little difference in the average change in QTN allele frequencies, but there was a major difference for the QTN with the largest effects. The sum of the effects of the edited QTN decreased across generations. This study showed that PAGE has great potential for application in livestock breeding programs, but inbreeding needs to be managed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 22 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 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Poland 1 <1%
France 1 <1%
Unknown 178 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 24%
Student > Ph. D. Student 36 20%
Student > Master 28 15%
Student > Bachelor 14 8%
Other 7 4%
Other 22 12%
Unknown 32 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 105 58%
Biochemistry, Genetics and Molecular Biology 22 12%
Environmental Science 3 2%
Computer Science 3 2%
Veterinary Science and Veterinary Medicine 3 2%
Other 10 5%
Unknown 36 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 08 July 2019.
All research outputs
#986,643
of 25,374,647 outputs
Outputs from Genetics Selection Evolution
#3
of 822 outputs
Outputs of similar age
#11,695
of 277,587 outputs
Outputs of similar age from Genetics Selection Evolution
#1
of 14 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 99% 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 277,587 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 95% of its contemporaries.
We're also able to compare this research output to 14 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 92% of its contemporaries.