Accuracy of Imputation of Microsatellite Markers from BovineSNP50 and BovineHD BeadChip in Hanwoo Population of Korea

Abstract

Until now microsatellite (MS) have been a popular choice of markers for parentage verification. Recently many countries have moved or are in process of moving from MS markers to single nucleotide polymorphism (SNP) markers for parentage testing. FAO-ISAG has also come up with a panel of 200 SNPs to replace the use of MS markers in parentage verification. However, in many countries most of the animals were genotyped by MS markers till now and the sudden shift to SNP markers will render the data of those animals useless. As National Institute of Animal Science in South Korea plans to move from standard ISAG recommended MS markers to SNPs, it faces the dilemma of exclusion of old animals that were genotyped by MS markers. Thus to facilitate this shift from MS to SNPs, such that the existing animals with MS data could still be used for parentage verification, this study was performed. In the current study we performed imputation of MS markers from the SNPs in the 500-kb region of the MS marker on either side. This method will provide an easy option for the labs to combine the data from the old and the current set of animals. It will be a cost efficient replacement of genotyping with the additional markers. We used 1,480 Hanwoo animals with both the MS data and SNP data to impute in the validation animals. We also compared the imputation accuracy between BovineSNP50 and BovineHD BeadChip. In our study the genotype concordance of 40% and 43% was observed in the BovineSNP50 and BovineHD BeadChip respectively.

Accuracy of Imputation of Microsatellite Markers from an SNP50K Chip in Spanish Assaf Sheep

“…1, the accuracy of our imputation results for the three metrics analyzed (C, length r 2 , and allelic r 2 ) in the different scenarios tested (SNP windows ranged between 0.5 and 10 Mb) was higher than 0.90 (C), 0.80 (length r 2 ), and 0.75 (allelic r 2 ) for all haplotype lengths. The accuracy results presented in this study were higher than those found in a previous study performed in cattle by Sharma et al (26), which reached a concordance of 0.40 and a correlation between the real and imputed microsatellites of 0.31. In addition, we have explored not only the viability of performing microsatellite imputation but also the optimum number of SNPs necessary to perform accurate imputation of microsatellite information.…”

“…Therefore, the large number of samples included in this study, and as a consequence, the large number of individuals genotyped in the reference population, could in uence the high accuracy rates achieved because it is necessary to impute the odd haplotypes (28) accurately and could also reduce the concordance rates obtained in the null models. Therefore, this nding explained the higher concordance rates obtained than those in previous studies on microsatellite imputation from SNP data conducted with lower sample sizes in humans (17) [1,916 samples] and cattle (26) [1,482 samples].…”

“…In addition, the selection of the reference and test populations during cross-validation by a nonparametric bootstrap approach avoids the overestimation of the imputation metrics by avoiding the selection of immediate relative samples in the different groups. On the other hand, the effective population size was 214, higher than in highly selected cattle breeds (26), but in the wide range of effective population sizes described in sheep breeds from values of 78 in Romney, 100 in Wiltshire breed, 128 in Churra breed, to 1,317 in Qezel (29)(30)(31). Lower values can lead to an overestimation of imputation accuracy metrics; however, if we compared our concordance rates with the concordance rates obtained in the microsatellite imputation in cattle carried out by Sharma et al…”

“…Therefore, the imputation procedure developed represents a useful and inexpensive approach to perform parentage veri cation when different genotyping platforms have been used across generations. The results from this study will undoubtedly have a great impact on Assaf sheep breeders, allowing them to perform a transition from microsatellite maker kinship veri cation to the use of SNP panels (26). In addition to constituting a clear advantage for sheep producers, the imputation methodologies developed can provide advantages in genomic studies by combining both types of data, such as in genome-wide association analyses (GWAS).…”

Association of Genetic Variants of ELMO1 Gene With Diabetic Nephropathy in the North Indian Population

“…The average concordance rate of the SNPs was observed to be 76.4% (Supplementary Table S5). Accuracy of imputation is known to increase with the increase in reference population size and also by including the familial genotype data in the reference population 41 . The sample size of the reference population is not large, but the numbers of SNPs were good enough to make a conclusion that the accuracy of the present data is of good quality.…”