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Genetic divergence and the genetic architecture of complex traits in chromosome substitution strains of mice

Overview of attention for article published in BMC Genomic Data, May 2012
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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)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Citations

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25 Dimensions

Readers on

mendeley
36 Mendeley
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2 CiteULike
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Title
Genetic divergence and the genetic architecture of complex traits in chromosome substitution strains of mice
Published in
BMC Genomic Data, May 2012
DOI 10.1186/1471-2156-13-38
Pubmed ID
Authors

Sabrina H Spiezio, Toyoyuki Takada, Toshihiko Shiroishi, Joseph H Nadeau

Abstract

The genetic architecture of complex traits strongly influences the consequences of inherited mutations, genetic engineering, environmental and genetic perturbations, and natural and artificial selection. But because most studies are under-powered, the picture of complex traits is often incomplete. Chromosome substitution strains (CSSs) are a unique paradigm for these genome surveys because they enable statistically independent, powerful tests for the phenotypic effects of each chromosome on a uniform inbred genetic background. A previous CSS survey in mice and rats revealed many complex trait genes (QTLs), large phenotypic effects, extensive epistasis, as well as systems properties such as strongly directional phenotypic changes and genetically-determined limits on the range of phenotypic variation. However, the unusually close genetic relation between the CSS progenitor strains in that study raised questions about the impact of genetic divergence: would greater divergence between progenitor strains, with the corresponding changes in gene regulation and protein function, lead to significantly more distinctive phenotypic features, or alternatively would epistasis and systems constraints, which are pervasive in CSSs, limit the range of phenotypic variation regardless of the extent of DNA sequence variation?

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
United States 1 3%
Norway 1 3%
Unknown 33 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 33%
Student > Ph. D. Student 9 25%
Student > Bachelor 3 8%
Other 3 8%
Professor > Associate Professor 3 8%
Other 4 11%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 58%
Biochemistry, Genetics and Molecular Biology 6 17%
Computer Science 2 6%
Immunology and Microbiology 1 3%
Psychology 1 3%
Other 1 3%
Unknown 4 11%
Attention Score in Context

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 02 July 2013.
All research outputs
#3,415,128
of 25,374,647 outputs
Outputs from BMC Genomic Data
#103
of 1,204 outputs
Outputs of similar age
#21,825
of 176,325 outputs
Outputs of similar age from BMC Genomic Data
#4
of 17 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 91% 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 176,325 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 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.