↓ Skip to main content

Transposable element polymorphisms recapitulate human evolution

Overview of attention for article published in Mobile DNA, November 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#44 of 354)
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
26 X users

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
97 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
Transposable element polymorphisms recapitulate human evolution
Published in
Mobile DNA, November 2015
DOI 10.1186/s13100-015-0052-6
Pubmed ID
Authors

Lavanya Rishishwar, Carlos E. Tellez Villa, I. King Jordan

Abstract

The human genome contains several active families of transposable elements (TE): Alu, L1 and SVA. Germline transposition of these elements can lead to polymorphic TE (polyTE) loci that differ between individuals with respect to the presence/absence of TE insertions. Limited sets of such polyTE loci have proven to be useful as markers of ancestry in human population genetic studies, but until this time it has not been possible to analyze the full genomic complement of TE polymorphisms in this way. For the first time here, we have performed a human population genetic analysis based on a genome-wide polyTE data set consisting of 16,192 loci genotyped in 2,504 individuals across 26 human populations. PolyTEs are found at very low frequencies, > 93 % of loci show < 5 % allele frequency, consistent with the deleteriousness of TE insertions. Nevertheless, polyTEs do show substantial geographic differentiation, with numerous group-specific polymorphic insertions. African populations have the highest numbers of polyTEs and show the highest levels of polyTE genetic diversity; Alu is the most numerous and the most diverse polyTE family. PolyTE genotypes were used to compute allele sharing distances between individuals and to relate them within and between human populations. Populations and continental groups show high coherence based on individuals' polyTE genotypes, and human evolutionary relationships revealed by these genotypes are consistent with those seen for SNP-based genetic distances. The patterns of genetic diversity encoded by TE polymorphisms recapitulate broad patterns of human evolution and migration over the last 60-100,000 years. The utility of polyTEs as ancestry informative markers is further underscored by their ability to accurately predict both ancestry and admixture at the continental level. A genome-wide list of polyTE loci, along with their population group-specific allele frequencies and FST values, is provided as a resource for investigators who wish to develop panels of TE-based ancestry markers. The genetic diversity represented by TE polymorphisms reflects known patterns of human evolution, and ensembles of polyTE loci are suitable for both ancestry and admixture analyses. The patterns of polyTE allelic diversity suggest the possibility that there may be a connection between TE-based genetic divergence and population-specific phenotypic differences. Graphical Abstractᅟ.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 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 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Germany 1 1%
Brazil 1 1%
Australia 1 1%
Spain 1 1%
New Zealand 1 1%
Unknown 90 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 29%
Student > Ph. D. Student 18 19%
Student > Master 13 13%
Student > Bachelor 7 7%
Student > Postgraduate 4 4%
Other 14 14%
Unknown 13 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 39%
Biochemistry, Genetics and Molecular Biology 36 37%
Chemistry 2 2%
Nursing and Health Professions 1 1%
Immunology and Microbiology 1 1%
Other 3 3%
Unknown 16 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 16 May 2023.
All research outputs
#2,356,450
of 24,798,538 outputs
Outputs from Mobile DNA
#44
of 354 outputs
Outputs of similar age
#29,477
of 258,015 outputs
Outputs of similar age from Mobile DNA
#2
of 8 outputs
Altmetric has tracked 24,798,538 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 354 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 87% 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 258,015 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 88% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.