Following the sequencing of the equine genome (EquCab2.0) it is important to utilize this information in the laboratory in conjunction with in silico studies. Digital Gene Expression (DGE, Illumina) profiling was used to characterize the assembly of genes expressed in equine skeletal muscle and to identify the subset of genes which were differentially expressed following a ten month period of exercise conditioning. DGE is a recently developed alternative to microarray gene expression profiling, currently the main platform used for global transcriptomic investigations. In contrast to microarray technology which is limited to the hybridisation of cDNA to probes printed on the array platform, DGE is not dependent on currently available sequence and thus provides a global, hypothesis free quantitative analysis of the transcriptome. The use of this technique will lead to a greater understanding of the molecular networks that control cellular function relating to muscle physiology in the horse. The study cohort comprised seven Thoroughbred racehorses from a single training yard with similar dietary and training management. The subjects undertook a regular exercise regime for ten months which consisted of 15-30 minute walk, followed by 1,000 m trot and 2,000 m canter once a day six times a week on an all-weather gallop as well as intermittent periods of higher intensity exercise (“work”) no more than once a week which consisted of 15-30 minute walk followed by 400 m trot, 500 m canter and 1,000 m gallop (sprint). Exercise physiological data (heart rate, velocity, plasma lactate concentrations etc.) were recorded throughout the conditioning period. Skeletal muscle biopsies were collected at rest from the gluteus medius following desensitisation of the site with 10 ml lidocaine (20mg/ml) in the same individuals at two time points: T1 – unconditioned, (9±0.5 months old) and T2 – conditioned (20±0.7 months old). RNA was isolated using the Trizol method, cDNA libraries were produced using the Illumna DGE sample preparation kit and directly sequenced using the Illumna Genome Analyser. This resulted in an average of 6.9 million tags per sample. Initial processing and alignment of tags to EquCab2.0 was carried out using the ELAND global alignment strategy (Illumna). Subsequent annotation of tags and statistical analyses were carried out using a custom written programme in the R-language (R Development Core Team, 2004). The online tool DAVID (Hosack et al. 2003) will be use for functional clustering and overrepresentation analyses of differentially expressed genes to identify gene pathways relevant to exercise. Results will be confirmed using real-time quantitative RT-PCR. This study will be the first to characterize global mRNA expression profiles in equine skeletal muscle following a period of exercise conditioning.