Understanding the functional mechanisms underlying genetic signals associated with complex traits and common diseases, such as cancer, diabetes and Alzheimer's disease, is a formidable challenge. Many genetic signals discovered through genome‐wide association studies map to non‐protein coding sequences, where their molecular consequences are difficult to evaluate. This article summarizes concepts for the systematic interpretation of non‐coding genetic signals using genome annotation data sets in different cellular systems. We outline strategies for the global analysis of multiple association intervals and the in‐depth molecular investigation of individual intervals. We highlight experimental techniques to validate candidate (potential causal) regulatory variants, with a focus on novel genome‐editing techniques including CRISPR/Cas9. These approaches are also applicable to low‐frequency and rare variants, which have become increasingly important in genomic studies of complex traits and diseases. There is a pressing need to translate genetic signals into biological mechanisms, leading to prognostic, diagnostic and therapeutic advances. Most of the genetic variants identified through GWAS as associated with complex traits, and common diseases map to non‐protein coding regions. We discuss the bioinformatic and experimental strategies available to translate these variants into molecular mechanisms, including emerging genome‐editing techniques.