Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle

van Binsbergen, Rianne, Bink, Marco C. A. M., Calus, Mario P. L., van Eeuwijk, Fred A., Hayes, Ben J., Hulsegge, Ina and Veerkamp, Roel F. (2014) Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle. Genetics Selection Evolution, 46 . doi:10.1186/1297-9686-46-41


Author van Binsbergen, Rianne
Bink, Marco C. A. M.
Calus, Mario P. L.
van Eeuwijk, Fred A.
Hayes, Ben J.
Hulsegge, Ina
Veerkamp, Roel F.
Title Accuracy of imputation to whole-genome sequence data in Holstein Friesian cattle
Journal name Genetics Selection Evolution   Check publisher's open access policy
ISSN 1297-9686
0999-193X
Publication date 2014-07-15
Sub-type Article (original research)
DOI 10.1186/1297-9686-46-41
Open Access Status DOI
Volume 46
Total pages 13
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Formatted abstract
Background: The use of whole-genome sequence data can lead to higher accuracy in genome-wide association studies and genomic predictions. However, to benefit from whole-genome sequence data, a large dataset of sequenced individuals is needed. Imputation from SNP panels, such as the Illumina BovineSNP50 BeadChip and Illumina BovineHD BeadChip, to whole-genome sequence data is an attractive and less expensive approach to obtain whole-genome sequence genotypes for a large number of individuals than sequencing all individuals. Our objective was to investigate accuracy of imputation from lower density SNP panels to whole-genome sequence data in a typical dataset for cattle.

Methods: Whole-genome sequence data of chromosome 1 (1737 471 SNPs) for 114 Holstein Friesian bulls were used. Beagle software was used for imputation from the BovineSNP50 (3132 SNPs) and BovineHD (40 492 SNPs) beadchips. Accuracy was calculated as the correlation between observed and imputed genotypes and assessed by five-fold cross-validation. Three scenarios S40, S60 and S80 with respectively 40%, 60%, and 80% of the individuals as reference individuals were investigated.

Results: Mean accuracies of imputation per SNP from the BovineHD panel to sequence data and from the BovineSNP50 panel to sequence data for scenarios S40 and S80 ranged from 0.77 to 0.83 and from 0.37 to 0.46, respectively. Stepwise imputation from the BovineSNP50 to BovineHD panel and then to sequence data for scenario S40 improved accuracy per SNP to 0.65 but it varied considerably between SNPs.

Conclusions: Accuracy of imputation to whole-genome sequence data was generally high for imputation from the BovineHD beadchip, but was low from the BovineSNP50 beadchip. Stepwise imputation from the BovineSNP50 to the BovineHD beadchip and then to sequence data substantially improved accuracy of imputation. SNPs with a low minor allele frequency were more difficult to impute correctly and the reliability of imputation varied more. Linkage disequilibrium between an imputed SNP and the SNP on the lower density panel, minor allele frequency of the imputed SNP and size of the reference group affected imputation reliability.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Article number 41

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
 
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