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Imputation of Sequence Level Genotypes in the Franches-Montagnes Horse Breed

Tuesday, August 19, 2014
Posters (The Westin Bayshore)
Mirjam Frischknecht , Graduate School for Cellular and Molecular biology, University of Bern, Bern, Switzerland
Markus Neuditschko , Swiss Competence Center of Animal Breeding and Genetics, Bern, Switzerland
Vidhya Jagannathan , Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
Cord Drögemüller , Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
Jens Tetens , Institute of Animal Breeding and Husbandry, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
Georg Thaller , Institute of Animal Breeding and Husbandry, University Kiel, Kiel, Germany
Tosso Leeb , Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
Stefan Rieder , Swiss Competence Center of Animal Breeding and Genetics, Bern, Switzerland
Abstract Text:

A cost-effective strategy to increase the density of available markers within a population is to sequence a small proportion of key individuals, and impute the remaining population, genotyped on a commercial SNP chip. Using 54,602 SNPs for 1,077 Franches-Montagnes (FM) horses and next generation sequencing (NGS) data for 28 representative FM horses and 14 Warmblood horses we performed genome-wide imputation for ~13 million SNPs. Imputation was performed with Impute2, Beagle and FImpute. The accuracy of the imputed genotypes was assessed using a cross-validation scheme. The mean imputation accuracy of FM horses using Impute2 was 95.6%. Using Beagle and FImpute this value was found to be 74.7% and 77.3%, respectively. After including Warmblood horses in the reference population the mean imputation accuracy increased to 96.8%. This indicates that imputation to high-density genotypes derived from NGS data was accurate.

Keywords:

horse

Next-generation sequencing

imputation

See more of: Posters: Methods and Tools - Genome Sequencing
See more of: Methods and Tools: Genome sequencing
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