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Title: The feasibility of using low-density marker panels for genotype imputation and genomic prediction of crossbred dairy cattle of East Africa
Contributor(s): Aliloo, H  (author)orcid ; Mrode, R (author); Okeyo, A M (author); Ni, G  (author); Goddard, M E (author); Gibson, J P (author)
Publication Date: 2018-10
Early Online Version: 2018-08-01
Open Access: Yes
DOI: 10.3168/jds.2018-14621Open Access Link
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Abstract: Cost-effective high-density (HD) genotypes of livestock species can be obtained by genotyping a proportion of the population using a HD panel and the remainder using a cheaper low-density panel, and then imputing the missing genotypes that are not directly assayed in the low-density panel. The efficacy of genotype imputation can largely be affected by the structure and history of the specific target population and it should be checked before incorporating imputation in routine genotyping practices. Here, we investigated the efficacy of imputation in crossbred dairy cattle populations of East Africa using 4 different commercial single nucleotide polymorphisms (SNP) panels, 3 reference populations, and 3 imputation algorithms. We found that Minimac and a reference population, which included a mixture of crossbred and ancestral purebred animals, provided the highest imputation accuracy compared with other scenarios of imputation. The accuracies of imputation, measured as the correlation between real and imputed genotypes averaged across SNP, were around 0.76 and 0.94 for 7K and 40K SNP, respectively, when imputed up to a 770K panel. We also presented a method to maximize the imputation accuracy of low-density panels, which relies on the pairwise (co)variances between SNP and the minor allele frequency of SNP. The performance of the developed method was tested in a 5-fold cross-validation process where various densities of SNP were selected using the (co)variance method and also by alternative SNP selection methods and then imputed up to the HD panel. The (co)variance method provided the highest imputation accuracies at almost all marker densities, with accuracies being up to 0.19 higher than the random selection of SNP. The accuracies of imputation from 7K and 40K panels selected using the (co)variance method were around 0.80 and 0.94, respectively. The presented method also achieved higher accuracy of genomic prediction at lower densities of selected SNP. The squared correlation between genomic breeding values estimated using imputed genotypes and those from the real 770K HD panel was 0.95 when the accuracy of imputation was 0.64. The presented method for SNP selection is straightforward in its application and can ensure high accuracies in genotype imputation of crossbred dairy populations in East Africa.
Publication Type: Journal Article
Source of Publication: Journal of Dairy Science, 101(10), p. 9108-9127
Publisher: Elsevier Inc
Place of Publication: United States of America
ISSN: 1525-3198
Fields of Research (FoR) 2008: 060412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
060408 Genomics
070201 Animal Breeding
Fields of Research (FoR) 2020: 310506 Gene mapping
310509 Genomics
300305 Animal reproduction and breeding
Socio-Economic Objective (SEO) 2008: 839999 Animal Production and Animal Primary Products not elsewhere classified
Socio-Economic Objective (SEO) 2020: 109999 Other animal production and animal primary products not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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