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Imputation for sequencing variants preselected to a customized low-density chip
The sequencing variants preselected from association analyses and bioinformatics analyses could improve genomic prediction. In this study, the imputation of sequencing SNPs preselected from major dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA) was investigated for both contemporary ani...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293337/ https://www.ncbi.nlm.nih.gov/pubmed/32533087 http://dx.doi.org/10.1038/s41598-020-66523-7 |
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author | Liu, Aoxing Lund, Mogens Sandø Boichard, Didier Mao, Xiaowei Karaman, Emre Fritz, Sebastien Aamand, Gert Pedersen Wang, Yachun Su, Guosheng |
author_facet | Liu, Aoxing Lund, Mogens Sandø Boichard, Didier Mao, Xiaowei Karaman, Emre Fritz, Sebastien Aamand, Gert Pedersen Wang, Yachun Su, Guosheng |
author_sort | Liu, Aoxing |
collection | PubMed |
description | The sequencing variants preselected from association analyses and bioinformatics analyses could improve genomic prediction. In this study, the imputation of sequencing SNPs preselected from major dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA) was investigated for both contemporary animals and old bulls in Danish Jersey. For contemporary animals, a two-step imputation which first imputed to 54 K and then to 54 K + DFS + FRA SNPs achieved highest accuracy. Correlations between observed and imputed genotypes were 91.6% for DFS SNPs and 87.6% for FRA SNPs, while concordance rates were 96.6% for DFS SNPs and 93.5% for FRA SNPs. The SNPs with lower minor allele frequency (MAF) tended to have lower correlations but higher concordance rates. For old bulls, imputation for DFS and FRA SNPs were relatively accurate even for bulls without progenies (correlations higher than 97.2% and concordance rates higher than 98.4%). For contemporary animals, given limited imputation accuracy of preselected sequencing SNPs especially for SNPs with low MAF, it would be a good strategy to directly genotype preselected sequencing SNPs with a customized SNP chip. For old bulls, given high imputation accuracy for preselected sequencing SNPs with all MAF ranges, it would be unnecessary to re-genotype preselected sequencing SNPs. |
format | Online Article Text |
id | pubmed-7293337 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72933372020-06-17 Imputation for sequencing variants preselected to a customized low-density chip Liu, Aoxing Lund, Mogens Sandø Boichard, Didier Mao, Xiaowei Karaman, Emre Fritz, Sebastien Aamand, Gert Pedersen Wang, Yachun Su, Guosheng Sci Rep Article The sequencing variants preselected from association analyses and bioinformatics analyses could improve genomic prediction. In this study, the imputation of sequencing SNPs preselected from major dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA) was investigated for both contemporary animals and old bulls in Danish Jersey. For contemporary animals, a two-step imputation which first imputed to 54 K and then to 54 K + DFS + FRA SNPs achieved highest accuracy. Correlations between observed and imputed genotypes were 91.6% for DFS SNPs and 87.6% for FRA SNPs, while concordance rates were 96.6% for DFS SNPs and 93.5% for FRA SNPs. The SNPs with lower minor allele frequency (MAF) tended to have lower correlations but higher concordance rates. For old bulls, imputation for DFS and FRA SNPs were relatively accurate even for bulls without progenies (correlations higher than 97.2% and concordance rates higher than 98.4%). For contemporary animals, given limited imputation accuracy of preselected sequencing SNPs especially for SNPs with low MAF, it would be a good strategy to directly genotype preselected sequencing SNPs with a customized SNP chip. For old bulls, given high imputation accuracy for preselected sequencing SNPs with all MAF ranges, it would be unnecessary to re-genotype preselected sequencing SNPs. Nature Publishing Group UK 2020-06-12 /pmc/articles/PMC7293337/ /pubmed/32533087 http://dx.doi.org/10.1038/s41598-020-66523-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liu, Aoxing Lund, Mogens Sandø Boichard, Didier Mao, Xiaowei Karaman, Emre Fritz, Sebastien Aamand, Gert Pedersen Wang, Yachun Su, Guosheng Imputation for sequencing variants preselected to a customized low-density chip |
title | Imputation for sequencing variants preselected to a customized low-density chip |
title_full | Imputation for sequencing variants preselected to a customized low-density chip |
title_fullStr | Imputation for sequencing variants preselected to a customized low-density chip |
title_full_unstemmed | Imputation for sequencing variants preselected to a customized low-density chip |
title_short | Imputation for sequencing variants preselected to a customized low-density chip |
title_sort | imputation for sequencing variants preselected to a customized low-density chip |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293337/ https://www.ncbi.nlm.nih.gov/pubmed/32533087 http://dx.doi.org/10.1038/s41598-020-66523-7 |
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