The defence will be held online via Teams and in room ANNU 141: https://teams.microsoft.com/meet/295071485541445?p=ocYVr344ogXMZjF1O2

FUNCTIONAL GENOMIC INSIGHTS INTO FEED EFFICIENCY IN CATTLE USING TRANSCRIPTOMICS
Feed efficiency (FE) is a key trait influencing the economic and environmental sustainability of beef and dairy cattle production; however, the biological mechanisms underlying variation in FE remain incompletely understood. Transcriptomic approaches provide an opportunity to characterize molecular processes associated with FE by capturing changes in both protein-coding and regulatory transcripts. The objective of this thesis was to investigate the liver transcriptomic mechanisms underlying variation in FE in cattle by characterizing molecular responses associated with residual feed intake (RFI) and dietary treatment, including: (a) differentially expressed mRNA isoforms; (b) long non-coding RNAs (lncRNAs); and (c) lncRNA co-expression networks and regulatory modules. Analysis of mRNA isoforms revealed greater transcriptomic responses in low-RFI animals (Holstein: 207; Jersey: 183) compared with high-RFI animals (Holstein: 103; Jersey: 90), while high-concentrate diets induced greater transcriptomic divergence (Holstein: 278; Jersey: 272) compared with control diets. Differentially expressed isoforms showed enrichment within production- and reproduction-associated quantitative trait loci (QTL), with low-RFI animals displaying a more balanced distribution of milk and reproduction-related QTL regions. Characterization of lncRNAs identified candidate regulatory transcripts and predicted lncRNA-mRNA interactions, including MSTRG.10056-CYP4A59 and MSTRG.7088-SLC1A2. Co-expression network analyses identified lncRNA modules and hub transcripts associated with RFI and dietary response, with MSTRG.6142 consistently identified across Holstein and Jersey cattle and predicted to interact with ATP6V0D2. Collectively, these findings advance understanding of the molecular mechanisms underlying FE by integrating coding and non-coding transcriptomic analyses and identifying candidate regulatory elements for future validation and biomarker discovery in dairy cattle.
