Imputation of sequence level genotypes in the Franches-Montagnes horse breed

Mirjam Frischknecht , Markus Neuditschko , Vidhya Jagannathan , Cord Drögemüller , Jens Tetens , Georg Thaller , Tosso Leeb , Stefan Rieder

Background A cost-effective strategy to increase the density of available markers within a population is to sequence a small proportion of the population and impute whole-genome sequence data for the remaining population. Increased densities of typed markers are advantageous for genome-wide association studies (GWAS) and genomic predictions.MethodsWe obtained genotypes for 54 602 SNPs (single nucleotide polymorphisms) in 1077 Franches-Montagnes (FM) horses and Illumina paired-end whole-genome sequencing data for 30 FM horses and 14 Warmblood horses. After variant calling, the sequence-derived SNP genotypes (~13 million SNPs) were used for genotype imputation with the software programs Beagle, Impute2 and FImpute.ResultsThe mean imputation accuracy of FM horses using Impute2 was 92.0%. Imputation accuracy using Beagle and FImpute was 74.3% and 77.2%, respectively. In addition, for Impute2 we determined the imputation accuracy of all individual horses in the validation population, which ranged from 85.7% to 99.8%. The subsequent inclusion of Warmblood sequence data further increased the correlation between true and imputed genotypes for most horses, especially for horses with a high level of admixture. The final imputation accuracy of the horses ranged from 91.2% to 99.5%.ConclusionsUsing Impute2, the imputation accuracy was higher than 91% for all horses in the validation population, which indicates that direct imputation of 50k SNP-chip data to sequence level genotypes is feasible in the FM population. The individual imputation accuracy depended mainly on the applied software and the level of admixture.

Domaines: Sciences du Vivant [q-bio]

Mirjam Frischknecht, Markus Neuditschko, Vidhya Jagannathan, Cord Drögemüller, Jens Tetens, et al.. Imputation of sequence level genotypes in the Franches-Montagnes horse breed. Genetics Selection Evolution, 2014, 46 (1), pp.63. ⟨10.1186/s12711-014-0063-7⟩. ⟨hal-01341238⟩