Frischknecht, Mirjam; Neuditschko, Markus; Jagannathan, Vidhya; Drögemüller, Cord; Tetens, Jens; Thaller, Georg; Leeb, Tosso; Rieder, Stefan (2014). Imputation of sequence level genotypes in the Franches-Montagnes horse breed. Genetics, selection, evolution, 46(1), p. 63. BioMed Central 10.1186/s12711-014-0063-7
|
Text
s12711-014-0063-7.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (1MB) | Preview |
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.
METHODS
We 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.
RESULTS
The 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%.
CONCLUSIONS
Using 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.
Item Type: |
Journal Article (Original Article) |
---|---|
Division/Institute: |
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Institute of Genetics 05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) |
Graduate School: |
Graduate School for Cellular and Biomedical Sciences (GCB) |
UniBE Contributor: |
Frischknecht, Mirjam, Jagannathan, Vidya, Drögemüller, Cord, Leeb, Tosso |
Subjects: |
500 Science > 570 Life sciences; biology 500 Science > 590 Animals (Zoology) 600 Technology > 630 Agriculture |
ISSN: |
1297-9686 |
Publisher: |
BioMed Central |
Language: |
English |
Submitter: |
Cord Drögemüller |
Date Deposited: |
19 Aug 2015 10:24 |
Last Modified: |
05 Dec 2022 14:48 |
Publisher DOI: |
10.1186/s12711-014-0063-7 |
PubMed ID: |
25927638 |
BORIS DOI: |
10.7892/boris.71093 |
URI: |
https://boris.unibe.ch/id/eprint/71093 |