↓ Skip to main content

Whole-genome sequence data uncover loss of genetic diversity due to selection

Overview of attention for article published in Genetics Selection Evolution, April 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 X user

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
53 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
Whole-genome sequence data uncover loss of genetic diversity due to selection
Published in
Genetics Selection Evolution, April 2016
DOI 10.1186/s12711-016-0210-4
Pubmed ID
Authors

Sonia E. Eynard, Jack J. Windig, Sipke J. Hiemstra, Mario P. L. Calus

Abstract

Whole-genome sequence (WGS) data give access to more complete structural genetic information of individuals, including rare variants, not fully covered by single nucleotide polymorphism chips. We used WGS to investigate the amount of genetic diversity remaining after selection using optimal contribution (OC), considering different methods to estimate the relationships used in OC. OC was applied to minimise average relatedness of the selection candidates and thus miminise the loss of genetic diversity in a conservation strategy, e.g. for establishment of gene bank collections. Furthermore, OC was used to maximise average genetic merit of the selection candidates at a given level of relatedness, similar to a genetic improvement strategy. In this study, we used data from 277 bulls from the 1000 bull genomes project. We measured genetic diversity as the number of variants still segregating after selection using WGS data, and compared strategies that targeted conservation of rare (minor allele frequency <5 %) versus common variants. When OC without restriction on the number of selected individuals was applied, loss of variants was minimal and most individuals were selected, which is often unfeasible in practice. When 20 individuals were selected, the number of segregating rare variants was reduced by 29 % for the conservation strategy, and by 34 % for the genetic improvement strategy. The overall number of segregating variants was reduced by 30 % when OC was restricted to selecting five individuals, for both conservation and genetic improvement strategies. For common variants, this loss was about 15 %, while it was much higher, 72 %, for rare variants. Fewer rare variants were conserved with the genetic improvement strategy compared to the conservation strategy. The use of WGS for genetic diversity quantification revealed that selection results in considerable losses of genetic diversity for rare variants. Using WGS instead of SNP chip data to estimate relationships slightly reduced the loss of rare variants, while using 50 K SNP chip data was sufficient to conserve common variants. The loss of rare variants could be mitigated by a few percent (up to 8 %) depending on which method is chosen to estimate relationships from WGS data.

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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 2%
Mexico 1 2%
Belgium 1 2%
Unknown 50 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 23%
Student > Master 11 21%
Researcher 9 17%
Student > Bachelor 3 6%
Student > Doctoral Student 3 6%
Other 6 11%
Unknown 9 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 53%
Biochemistry, Genetics and Molecular Biology 8 15%
Unspecified 1 2%
Veterinary Science and Veterinary Medicine 1 2%
Mathematics 1 2%
Other 0 0%
Unknown 14 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 April 2016.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from Genetics Selection Evolution
#550
of 822 outputs
Outputs of similar age
#193,531
of 315,328 outputs
Outputs of similar age from Genetics Selection Evolution
#11
of 16 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 315,328 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.