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This chapter first summarises major functional-genomics resources in cattle, including epigenomic, transcriptomic, proteomic, metabolomic, and phenomics datasets. It then reviews computational methods for integrating these annotations into genomic prediction models, highlights empirical evidence for both benefits and limitations, and discusses future directions for multi-omics genomic prediction. Particular attention is given to whether annotation-informed models provide incremental predictive value beyond strong marker-based, Bayesian, and sequence-based baselines.
Price: £25.00
Publisher: Burleigh Dodds Science Publishing
Imprint: Burleigh Dodds Science Publishing
Series: Burleigh Dodds Series in Agricultural Science
Publication Date:
08 November 2026
ISBN: 9781835458884
Format: eBook
BISACs:
- 1 Introduction
- 2 Landscape of functional annotations and data resources
- 3 Annotation-driven integration methods and evidence
- 4 Improving genomic prediction case studies
- 5 Conclusion and future trends
- 6 Where to look for further information
- 7 References