Abstract
BackgroundGenotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Imputation methods rely partially on linkage disequilibrium between markers to infer unobserved genotypes. Bos indicus cattle (e.g. Nelore breed) are characterized, in general, by lower levels of linkage disequilibrium between genetic markers at short distances, compared to taurine breeds. Thus, it is important to evaluate the accuracy of imputation to better define which imputation method and chip are most appropriate for genomic applications in indicine breeds.MethodsAccuracy of genotype imputation in Nelore cattle was evaluated using different LD chips, imputation software and sets of animals. Twelve commercial and customized LD chips with densities ranging from 7 K to 75 K were tested. Customized LD chips were virtually designed taking into account minor allele frequency, linkage disequilibrium and distance between markers. Software programs FImpute and BEAGLE were applied to impute genotypes. From 995 bulls and 1247 cows that were genotyped with the Illumina® BovineHD chip (HD), 793 sires composed the reference set, and the remaining 202 younger sires and all the cows composed two separate validation sets for which genotypes were masked except for the SNPs of the LD chip that were to be tested.ResultsImputation accuracy increased with the SNP density of the LD chip. However, the gain in accuracy with LD chips with more than 15 K SNPs was relatively small because accuracy was already high at this density. Commercial and customized LD chips with equivalent densities presented similar results. FImpute outperformed BEAGLE for all LD chips and validation sets. Regardless of the imputation software used, accuracy tended to increase as the relatedness between imputed and reference animals increased, especially for the 7 K chip.ConclusionsIf the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-014-0069-1) contains supplementary material, which is available to authorized users.
Highlights
Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions
Values for percentage of correctly imputed genotypes (PERC) were proportionally smaller than the corresponding values for CORR since the penalty for one incorrectly imputed allele is relatively higher for PERC than for CORR
As documented in the literature [4,16], imputation accuracy increases with a decreasing proportion of SNPs to be imputed
Summary
Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Bos indicus cattle (e.g. Nelore breed) are characterized, in general, by lower levels of linkage disequilibrium between genetic markers at short distances, compared to taurine breeds. Genomic information from dense single nucleotide polymorphism (SNP) chips provides the opportunity to increase the rate of genetic progress in breeding programs, if a sufficient number of markers and animals with phenotypes (or pseudo-phenotypes such as estimated breeding values, EBV) are genotyped [1]. The Nelore (indicine) breed is the most important beef cattle breed in Brazil [5] For this breed, the Illumina® BovineHD chip (HD) is used as the “gold standard” for research purposes, since a low level of linkage disequilibrium between adjacent markers is observed in lower-density chips (e.g. 50 K) [6,7]. Lower-density chips are required to overcome this limitation, which highlights the importance of assessing the accuracy of imputing genotypes in the Nelore breed
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