Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes

Abstract

The objective of this study was to quantify the accuracy of imputing the genotype of parents using information on the genotype of their progeny and a family-based and population-based imputation algorithm. Two separate data sets were used, one containing both dairy and beef animals (n = 3122) with high-density genotypes (735 151 single nucleotide polymorphisms (SNPs)) and the other containing just dairy animals (n = 5489) with medium-density genotypes (51 602 SNPs). Imputation accuracy of three different genotype density panels were evaluated representing low (i.e. 6501 SNPs), medium and high density. The full genotypes of sires with genotyped half-sib progeny were masked and subsequently imputed. Genotyped half-sib progeny group sizes were altered from 4 up to 12 and the impact on imputation accuracy was quantified. Up to 157 and 258 sires were used to test the accuracy of imputation in the dairy plus beef data set and the dairy-only data set, respectively. The efficiency and accuracy of imputation was quantified as the proportion of genotypes that could not be imputed, and as both the genotype concordance rate and allele concordance rate. The median proportion of genotypes per animal that could not be imputed in the imputation process decreased as the number of genotyped half-sib progeny increased; values for the medium-density panel ranged from a median of 0.015 with a half-sib progeny group size of 4 to a median of 0.0014 to 0.0015 with a half-sib progeny group size of 8. The accuracy of imputation across different paternal half-sib progeny group sizes was similar in both data sets. Concordance rates increased considerably as the number of genotyped half-sib progeny increased from four (mean animal allele concordance rate of 0.94 in both data sets for the medium-density genotype panel) to five (mean animal allele concordance rate of 0.96 in both data sets for the medium-density genotype panel) after which it was relatively stable up to a half-sib progeny group size of eight. In the data set with dairy-only animals, sufficient sires with paternal half-sib progeny groups up to 12 were available and the withinanimal mean genotype concordance rates continued to increase up to this group size. The accuracy of imputation was worst for the low-density genotypes, especially with smaller half-sib progeny group sizes but the difference in imputation accuracy between density panels diminished as progeny group size increased; the difference between high and medium-density genotype panels was relatively small across all half-sib progeny group sizes. Where biological material or genotypes are not available on individual animals, at least five progeny can be genotyped (on either a medium or high-density genotyping platform) and the parental alleles imputed with, on average, ⩾96% accuracy.

Inter- and intra-reproducibility of genotypes from sheep technical replicates on Illumina and Affymetrix platforms

“…The mean within-animal genotype and allele concordance rates of 0.9993 and 0.9996, respectively between duplicate samples on the Illumina OvineSNP50 platform and also the near unity genotype and allele concordance rates of 0.9993 and 0.9997, respectively between the two Illumina platforms, are excellent and corroborate the respective values of 0.9989 and 0.9993 reported by Berry et al [3] using duplicate genotypes of 134 cattle that were genotyped on the Illumina BovineSNP50 beadchip. Using six samples from the human HapMap project, Hong et al [4] reported a mean genotype concordance rate of 0.9940 between duplicate samples on an Illumina platform and of 0.9987 between duplicate samples on an Affymetrix platform; all genotype comparisons undertaken by Hong et al [4] originated from the same genotyping laboratory.…”

“…However, only two (experienced) laboratories were compared, which limited the possibility that a laboratory effect impacted genotype. Nonetheless, the high concordance rate between duplicate bovine samples reported by Berry et al [3], based on genotypes that were generated across multiple laboratories, provides further confidence that there is good genotype concordance across different service providers. Furthermore, most, if not all, of the discrepancies between duplicate genotypes on the platforms used in our study were actually due to a homozygous genotype of one replicate being called as a heterozygous in the other replicate, or vice versa.…”

“…In a comparison based on 134 bovine technical replicates, which were both genotyped on the Illumina BovineSNP50 Beadchip, Berry et al [3] reported mean genotype and allele concordance rates per individual of 0.9989 and 0.9993, respectively. In a comparison between six human technical replicates, Hong et al [4] documented a mean (standard deviation) genotype concordance rate between Illumina and Affymetrix platforms of 98.80% (0.34%).…”

Evaluation of developed low-density genotype panels for imputation to higher density in independent dairy and beef cattle populations1

“…Several studies have evaluated the accuracy of imputation from alternative-density genotype panels ranging from commercially available panels (Berry and Kearney, 2011;Berry et al, 2014) to custom-derived panels of SNP (Habier et al, 2009; Weigel et al, Figure 3. The mean allele concordance rate per animal across varying number of SNP selected using Feature Selection using Feature Similarity (diagonal lines), randomly (white bar), and uniformly (light gray bar), based on genomic characteristics (darkest bar), or by the block method (horizontal lined bar).…”

“…Beagle and FImpute are imputation software packages commonly used for cattle (Berry and Kearney, 2011;Berry et al, 2014;Carvalheiro et al, 2014). Beagle uses population LD to impute missing genotypes whereas FImpute exploits both family information and population LD.…”