Bridging GWAS to genes: an integrative multi-omics approach using cattle data
We hypothesized that the 20 genes are the most likely causal genes for the trait because: mammary expression of these genes was associated with GEBV for the trait, they were significantly colocalized with GWAS signals, and they were enriched in gene ontology terms relevant to physiology of the trait. Our approach provides strong evidence for causal genes supported by multiple lines of evidence (GWAS, GSOR, and functional enrichment) and demonstrates the power of multi-omics data integration.
Authors
- J.E. Pryce (ORCID: https://orcid.org/0000-0002-1397-1282)
- Mathew D. Littlejohn (ORCID: https://orcid.org/0000-0001-9044-047X)
- Ruidong Xiang (ORCID: https://orcid.org/0000-0002-1584-7605)
- Thomas Lopdell (ORCID: https://orcid.org/0000-0002-7684-4870)
- Iona M. MacLeod
- Amanda J. Chamberlain
- Michael E. Goddard
- Mohammad Ghoreishifar
- Tuan Nguyen
Institutions
- Livestock Improvement Corporation (NZ)
- The University of Melbourne (AU)
- La Trobe University (AU)
- Agriculture Victoria (AU)
- AgriBio (AU)
- Massey University (NZ)
Publication Details
- Journal
- BMC Genomics
- Published
- 2026-01-14
- DOI
- https://doi.org/10.1186/s12864-026-12525-0
- Primary Topic
- Genetic and phenotypic traits in livestock
- Type
- article
- Field-Weighted Citation Impact
- 0.00