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Whole-genome sequence data uncover loss of genetic diversity due to selection
BACKGROUND: 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 opti...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4831198/ https://www.ncbi.nlm.nih.gov/pubmed/27080121 http://dx.doi.org/10.1186/s12711-016-0210-4 |
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author | Eynard, Sonia E. Windig, Jack J. Hiemstra, Sipke J. Calus, Mario P. L. |
author_facet | Eynard, Sonia E. Windig, Jack J. Hiemstra, Sipke J. Calus, Mario P. L. |
author_sort | Eynard, Sonia E. |
collection | PubMed |
description | BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-016-0210-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4831198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48311982016-04-15 Whole-genome sequence data uncover loss of genetic diversity due to selection Eynard, Sonia E. Windig, Jack J. Hiemstra, Sipke J. Calus, Mario P. L. Genet Sel Evol Research Article BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-016-0210-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-04-14 /pmc/articles/PMC4831198/ /pubmed/27080121 http://dx.doi.org/10.1186/s12711-016-0210-4 Text en © Eynard et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Eynard, Sonia E. Windig, Jack J. Hiemstra, Sipke J. Calus, Mario P. L. Whole-genome sequence data uncover loss of genetic diversity due to selection |
title | Whole-genome sequence data uncover loss of genetic diversity due to selection |
title_full | Whole-genome sequence data uncover loss of genetic diversity due to selection |
title_fullStr | Whole-genome sequence data uncover loss of genetic diversity due to selection |
title_full_unstemmed | Whole-genome sequence data uncover loss of genetic diversity due to selection |
title_short | Whole-genome sequence data uncover loss of genetic diversity due to selection |
title_sort | whole-genome sequence data uncover loss of genetic diversity due to selection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4831198/ https://www.ncbi.nlm.nih.gov/pubmed/27080121 http://dx.doi.org/10.1186/s12711-016-0210-4 |
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