Sequence-based GWAS in 180,000 German Holstein cattle reveals new candidate variants for milk production traits
Our findings proved the power of large samples and sequence-based GWAS in detecting new association signals. In order to fully exploit the power of GWAS, one should aim at very large samples combined with whole-genome sequence data. These can also come with both computational and time burdens, as presented in our study. Although milk production traits in cattle are comprehensively investigated, the genetic background of these traits is still not fully understood, with the potential for many new associations to be revealed, as shown. With constantly growing sample sizes, we expect more insights into the genetic architecture of milk production traits in the future.
Authors
- Johannes Heise (ORCID: https://orcid.org/0000-0002-7605-7148)
- J.E. Pryce (ORCID: https://orcid.org/0000-0002-1397-1282)
- Ana-Marija Križanac (ORCID: https://orcid.org/0000-0002-7446-8031)
- Zengting Liu (ORCID: https://orcid.org/0000-0002-7112-0320)
- Jens Tetens (ORCID: https://orcid.org/0000-0001-5352-464X)
- Jörn Bennewitz (ORCID: https://orcid.org/0000-0001-6450-1160)
- Clemens Falker‐Gieske (ORCID: https://orcid.org/0000-0001-9160-1909)
- Christian Reimer (ORCID: https://orcid.org/0000-0002-9697-2511)
- Georg Thaller (ORCID: https://orcid.org/0000-0002-6782-2039)
Institutions
- University of Hohenheim (DE)
- Friedrich-Loeffler-Institut (DE)
- La Trobe University (AU)
- Christian-Albrechts-Universität zu Kiel (DE)
- Agriculture Victoria (AU)
- AgriBio (AU)
- University of Göttingen (DE)
Publication Details
- Journal
- Genetics Selection Evolution
- Published
- 2025-02-04
- DOI
- https://doi.org/10.1186/s12711-025-00951-9
- Citations
- 12
- Primary Topic
- Genetic and phenotypic traits in livestock
- Type
- article
- Field-Weighted Citation Impact
- 21.81
Funders
- La Trobe University
- Teagasc
- Deutsche Forschungsgemeinschaft
- Georg-August-Universität Göttingen
- Max-Planck-Gesellschaft
- Agriculture Victoria