Korkuc, Paula; Arends, Danny and Brockmann, Gudrun A. (2019) Finding the Optimal Imputation Strategy for Small Cattle Populations. Frontier in Genetics, 10 (52), pp. 1-10.
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Document available online at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00052/full
Summary
The imputation from lower density SNP chip genotypes to whole-genome sequencelevel is an established approach to generate high density genotypes for many individuals. Imputation accuracy is dependent on many factors and for small cattle populations such as the endangered German Black Pied cattle (DSN), determining the optimal imputation strategy is especially challenging since only a low number of high density genotypes is vailable. In this paper, the accuracy of imputation was explored with regard to (1) phasing of the target population and the reference panel for imputation, (2) comparison of a 1-step imputation approach, where 50 k genotypes are directly imputed to sequence level, to a 2-step imputation approach that used an intermediate step imputing first to 700 k and subsequently to sequence level, (3) the software tools Beagle and Minimac, and (4) the size and composition of the reference panel for imputation. Analyses were performed for 30 DSN and 30 Holstein Frisian cattle available from the 1000 Bull Genomes Project. Imputation accuracy was assessed using a leave-one-out cross validation procedure. We observed that phasing of the target populations and the reference panels affects the imputation accuracy significantly. Minimac reached higher accuracy when imputing using small reference panels, while Beagle performed better with larger reference panels. In contrast to previous research, we found that when a low number of animals is available at the intermediate imputation step, the 1-step imputation approach yielded higher imputation accuracy compared to a 2-step imputation. Overall, the size of the reference panel for imputation is the most important factor leading to higher imputation accuracy, although using a larger reference panel consisting of a related but different breed (Holstein Frisian) significantly reduced imputation accuracy.
Our findings provide specific recommendations for populations with a limited number of high density genotyped or sequenced animals available such as DSN. The overall recommendation when imputing a small population are to (1) use a large reference panel of the same breed, (2) use a large reference panel consisting of diverse breeds, or (3) when a large reference panel is not available, we recommend using a smaller same breed reference panel without including a different related breed.
EPrint Type: | Journal paper |
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Type of presentation: | Paper |
Keywords: | BLE, BÖL, BOEL, FKZ 15NA010, DSN – Deutsches Schwarzbuntes Niederungsrind, Milchvieh, Doppelnutzungsrind, Genreserve, Erhaltungszucht, Genetische Marker, Imputation |
Agrovoc keywords: | Language Value URI English cattle http://aims.fao.org/aos/agrovoc/c_1391 English genotypes http://aims.fao.org/aos/agrovoc/c_3225 |
Subjects: | Animal husbandry > Production systems > Dairy cattle Animal husbandry > Production systems > Beef cattle Animal husbandry > Breeding and genetics |
Research affiliation: | Germany > Federal Organic Farming Scheme - BOEL > Animals > Tierzucht Germany > University of Berlin - HU |
DOI: | 10.3389/fgene.2019.00052 |
Related Links: | https://orgprints.org/id/eprint/30261/, https://www.bundesprogramm.de |
Deposited By: | Korkuc, Dr. Paula |
ID Code: | 52426 |
Deposited On: | 18 Jan 2024 07:33 |
Last Modified: | 19 Jan 2024 13:52 |
Document Language: | English |
Status: | Published |
Refereed: | Peer-reviewed and accepted |
Additional Publishing Information: | Gefördert durch das Bundesministerium für Ernährung und Landwirtschaft aufgrund eines Beschlusses des Deutschen Bundestages im Rahmen des Bundesprogramms Ökologischer Landbau und andere Formen nachhaltiger Landwirtschaft. |
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