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Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools

Overview of attention for article published in BMC Genomics, July 2015
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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Title
Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools
Published in
BMC Genomics, July 2015
DOI 10.1186/s12864-015-1712-0
Pubmed ID
Authors

Zachary L. Fuller, Elina L. Niño, Harland M. Patch, Oscar C. Bedoya-Reina, Tracey Baumgarten, Elliud Muli, Fiona Mumoki, Aakrosh Ratan, John McGraw, Maryann Frazier, Daniel Masiga, Stephen Schuster, Christina M. Grozinger, Webb Miller

Abstract

With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including F ST, pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions. We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea. These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows ( http://usegalaxy.org/r/kenyanbee ) that can be applied to any model system with genomic information.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Switzerland 1 <1%
South Africa 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Poland 1 <1%
Unknown 114 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 21%
Researcher 22 18%
Student > Master 14 12%
Student > Bachelor 8 7%
Other 6 5%
Other 19 16%
Unknown 26 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 55 46%
Biochemistry, Genetics and Molecular Biology 21 18%
Environmental Science 2 2%
Engineering 2 2%
Business, Management and Accounting 1 <1%
Other 8 7%
Unknown 31 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 July 2015.
All research outputs
#13,933,099
of 24,514,423 outputs
Outputs from BMC Genomics
#4,772
of 10,999 outputs
Outputs of similar age
#119,777
of 267,720 outputs
Outputs of similar age from BMC Genomics
#124
of 259 outputs
Altmetric has tracked 24,514,423 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,999 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 56% 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 267,720 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 259 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 52% of its contemporaries.