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Genetic composition of captive panda population

Overview of attention for article published in BMC Genomic Data, October 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Title
Genetic composition of captive panda population
Published in
BMC Genomic Data, October 2016
DOI 10.1186/s12863-016-0441-y
Pubmed ID
Authors

Jiandong Yang, Fujun Shen, Rong Hou, Yang Da

Abstract

A major function of the captive panda population is to preserve the genetic diversity of wild panda populations in their natural habitats. Understanding the genetic composition of the captive panda population in terms of genetic contributions from the wild panda populations provides necessary knowledge for breeding plans to preserve the genetic diversity of the wild panda populations. The genetic contributions from different wild populations to the captive panda population were highly unbalanced, with Qionglai accounting for 52.2 % of the captive panda gene pool, followed by Minshan with 21.5 %, Qinling with 10.6 %, Liangshan with 8.2 %, and Xiaoxiangling with 3.6 %, whereas Daxiangling, which had similar population size as Xiaoxiangling, had no genetic representation in the captive population. The current breeding recommendations may increase the contribution of some small wild populations at the expense of decreasing the contributions of other small wild populations, i.e., increasing the Xiaoxiangling contribution while decreasing the contribution of Liangshan, or sharply increasing the Qinling contribution while decreasing the contributions of Xiaoxiangling and Liangshan, which were two of the three smallest wild populations and were already severely under-represented in the captive population. We developed three habitat-controlled breeding plans that could increase the genetic contributions from the smallest wild populations to 6.7-11.2 % for Xiaoxiangling, 11.5-12.3 % for Liangshan and 12.9-20.0 % for Qinling among the offspring of one breeding season while reducing the risk of hidden inbreeding due to related founders from the same habitat undetectable by pedigree data. The three smallest wild panda populations of Daxiangling, Xiaoxiangling and Liangshan either had no representation or were severely unrepresented in the current captive panda population. By incorporating the breeding goal of increasing the genetic contributions from the smallest wild populations into breeding plans, the severely under-represented small wild populations in the current captive panda population could be increased steadily for the near future.

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X Demographics

The data shown below were collected from the profiles of 3 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 18%
Other 2 12%
Researcher 2 12%
Student > Ph. D. Student 2 12%
Unspecified 1 6%
Other 3 18%
Unknown 4 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 35%
Biochemistry, Genetics and Molecular Biology 2 12%
Computer Science 2 12%
Environmental Science 1 6%
Unspecified 1 6%
Other 0 0%
Unknown 5 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 19 January 2017.
All research outputs
#4,168,422
of 25,374,917 outputs
Outputs from BMC Genomic Data
#131
of 1,204 outputs
Outputs of similar age
#64,989
of 329,225 outputs
Outputs of similar age from BMC Genomic Data
#7
of 24 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd 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 well, scoring higher than 88% 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 329,225 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 80% of its contemporaries.
We're also able to compare this research output to 24 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 70% of its contemporaries.