The increase in progressive kidney disease, rising numbers of patients with end-stage renal disease, organ shortages for kidney transplants and poor long-term graft survival rates underline the need for better strategies to diagnose, prevent and treat renal disease. Histological analysis, based on renal biopsies and readings of morphology, has limitations as key information for the management of the individual patient, and complementary technologies are needed. The sequencing of the human genome has provided the platform for applied molecular phenotyping. Microarray technology has become a routine method for robust high-throughput measurements of genome-wide transcriptome levels. This review will give examples of transcriptome profiling in nephrology and focus on lessons learned from studies in kidney transplantation. Molecular profiling detects changes not seen by morphology or captured by clinical markers. Gene expression signatures provide quantitative measurements of inflammatory burden and immune activation or metabolism, and reflect coordinated changes in pathways associated with injury and repair. Transcriptome profiling has the potential to improve our understanding of disease mechanisms, may provide tools to reclassify disease entities and be potentially helpful in individualizing therapies and predicting outcomes. However, description of transcriptome patterns is not an end in itself. The identification of predictive gene sets and the application to an individualized patient management requires integration of clinical and pathology-based variables as well as more objective reference markers and hard end points.