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Comparative transcriptomics reveals the conserved building blocks involved in parallel evolution of diverse phenotypic traits in ants

Overview of attention for article published in Genome Biology (Online Edition), March 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)

Mentioned by

news
7 news outlets
blogs
2 blogs
twitter
23 tweeters
facebook
1 Facebook page
googleplus
2 Google+ users

Citations

dimensions_citation
66 Dimensions

Readers on

mendeley
169 Mendeley
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Title
Comparative transcriptomics reveals the conserved building blocks involved in parallel evolution of diverse phenotypic traits in ants
Published in
Genome Biology (Online Edition), March 2016
DOI 10.1186/s13059-016-0902-7
Pubmed ID
Authors

Claire Morandin, Mandy M. Y. Tin, Sílvia Abril, Crisanto Gómez, Luigi Pontieri, Morten Schiøtt, Liselotte Sundström, Kazuki Tsuji, Jes Søe Pedersen, Heikki Helanterä, Alexander S. Mikheyev

Abstract

Reproductive division of labor in eusocial insects is a striking example of a shared genetic background giving rise to alternative phenotypes, namely queen and worker castes. Queen and worker phenotypes play major roles in the evolution of eusocial insects. Their behavior, morphology and physiology underpin many ecologically relevant colony-level traits, which evolved in parallel in multiple species. Using queen and worker transcriptomic data from 16 ant species we tested the hypothesis that conserved sets of genes are involved in ant reproductive division of labor. We further hypothesized that such sets of genes should also be involved in the parallel evolution of other key traits. We applied weighted gene co-expression network analysis, which clusters co-expressed genes into modules, whose expression levels can be summarized by their 'eigengenes'. Eigengenes of most modules were correlated with phenotypic differentiation between queens and workers. Furthermore, eigengenes of some modules were correlated with repeated evolution of key phenotypes such as complete worker sterility, the number of queens per colony, and even invasiveness. Finally, connectivity and expression levels of genes within the co-expressed network were strongly associated with the strength of selection. Although caste-associated sets of genes evolve faster than non-caste-associated, we found no evidence for queen- or worker-associated co-expressed genes evolving faster than one another. These results identify conserved functionally important genomic units that likely serve as building blocks of phenotypic innovation, and allow the remarkable breadth of parallel evolution seen in ants, and possibly other eusocial insects as well.

Twitter Demographics

The data shown below were collected from the profiles of 23 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 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
France 2 1%
Portugal 1 <1%
Chile 1 <1%
Ireland 1 <1%
Germany 1 <1%
New Zealand 1 <1%
Finland 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 157 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 26%
Researcher 32 19%
Student > Master 26 15%
Student > Bachelor 14 8%
Student > Postgraduate 7 4%
Other 29 17%
Unknown 17 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 95 56%
Biochemistry, Genetics and Molecular Biology 35 21%
Environmental Science 5 3%
Computer Science 5 3%
Engineering 3 2%
Other 5 3%
Unknown 21 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 81. 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 21 April 2016.
All research outputs
#392,919
of 21,172,126 outputs
Outputs from Genome Biology (Online Edition)
#270
of 4,011 outputs
Outputs of similar age
#8,301
of 280,411 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 21,172,126 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,011 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one has done particularly well, scoring higher than 93% 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 280,411 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 97% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them