Details

Autor(en) / Beteiligte

• Vosgerau, Sarah
• Krattenmacher, Nina
• Falker-Gieske, Clemens
• Seidel, Anita
• Tetens, Jens
• Stock, Kathrin F.
• Nolte, Wietje
• Wobbe, Mirell
• Blaj, Iulia
• Reents, Reinhard
• Kühn, Christa
• von Depka Prondzinski, Mario
• Kalm, Ernst
• Thaller, Georg

Titel

Genetic and genomic characterization followed by single-step genomic evaluation of withers height in German Warmblood horses

Ist Teil von

• Journal of applied genetics, 2022-05, Vol.63 (2), p.369-378

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2022

Quelle

MEDLINE

Beschreibungen/Notizen

•    Reliability of genomic predictions is influenced by the size and genetic composition of the reference population. For German Warmblood horses, compilation of a reference population has been enabled through the cooperation of five German breeding associations. In this study, preliminary data from this joint reference population were used to genetically and genomically characterize withers height and to apply single-step methodology for estimating genomic breeding values for withers height. Using data on 2113 mares and their genomic information considering about 62,000 single nucleotide polymorphisms (SNPs), analysis of the genomic relationship revealed substructures reflecting breed origin and different breeding goals of the contributing breeding associations. A genome-wide association study confirmed a known quantitative trait locus (QTL) for withers height on equine chromosome (ECA) 3 close to LCORL and identified a further significant peak on ECA 1. Using a single-step approach with a combined relationship matrix, the estimated heritability for withers height was 0.31 (SE = 0.08) and the corresponding genomic breeding values ranged from − 2.94 to 2.96 cm. A mean reliability of 0.38 was realized for these breeding values. The analyses of withers height showed that compiling a reference population across breeds is a suitable strategy for German Warmblood horses. The single-step method is an appealing approach for practical genomic prediction in horses, because not many genotypes are available yet and animals without genotypes can by this way directly contribute to the estimation system.