Feed is the largest variable cost in milk production industries, thus improving feed efficiency will give better use of resources. This project works closely on definitions of feed efficiency in dairy cattle and uses advanced integrated genomics, bioinformatics and systems biology methods linking transcriptomics differences to important attributes or traits related to dairy cattle feed efficiency. Twenty cows (10 Jersey; 10 Holstein Friesian) will be used in the experiment. These two groups of breeds will be divided into two feed efficiency groups depending on their feed efficiency status which are of high or low efficiency. mRNA will be extracted from liver biopsies samples for RNA-sequencing which will be performed on the Illumina HiSeq2500. Blood samples will be collected for genotyping and plasma. Plasma will be extracted from the blood for analysis of glucose, NEFA, β-hydroxybutyrates, Triacylglyceride and urea. Feed efficiency, namely Residual Feed Intake and Kleiber Ratio based on daily feed or dry matter intake, body weight and milk production records also will be calculated. The bovine RNAseq gene expression data will be analyzed using statistical-bioinformatics and systems biology approaches to identify a list of differentially expressed genes, co-expressed genes, differentially wired networks, co-expression, transcriptional regulatory networks and hub genes/biomarkers for feed efficiency. This study will provide molecular mechanisms of metabolic processes, energy balance, nutrient partitioning and deliver predictive biomarkers for feed efficiency in cattle. This study will also contribute to systems genomic prediction or selection models including the information on potential causal genes / SNPs or their functional modules.