Sequencing technologies promising the “$1000 genome” have developed at a staggering pace, driven in part by the HapMap Project1 (which set out to catalog common variations throughout the genome in multiple ethnic populations) and the 1000 Genomes Project2 (a consortium to catalog rare variations from different ethnic populations worldwide). Commercial whole-genome sequencing platforms have yet to break the $1000 mark. However, sequencing throughput and accuracy are no longer limiting factors. Despite recent successes in patient-oriented whole-genome sequencing3-6, analyzing and interpreting these data sets represent a major challenge, particularly for the ∼98% of the genome that does not encode proteins. In 2009, an alternative to whole-genome sequencing was introduced7. Whole-exome sequencing uses high-throughput next-generation technologies to sequence only the portions of the genome that encode proteins (termed the exome). The goal of whole-exome sequencing is to identify sequence mutations that alter the amino acid content of a protein, potentially altering the protein’s function in a cell and leading to disease. Proof of concept for this approach was documented in a landmark paper that used whole-exome sequencing to identify the genetic cause of Freeman-Sheldon syndrome (OMIM [Online Mendelian Inheritance in Man] 193700)7. This study broke the technical and cost limitation barriers (compared with sequencing an entire genome) by sequencing only the protein-coding regions (∼1% of the genome) and showed that a study of only a few patients was sufficient to identify a disease-causing gene. Whole-exome sequencing has revolutionized disease-gene discovery and, supported by the 1000 Genomes Project2 and other large-scale sequencing studies (e.g., the NHLBI/NHGRI [National Heart, Lung, and Blood Institute/National Human Genome Research Institute] Exome Project), it promises to identify virtually all genes causing disorders with Mendelian inheritance—i.e., those disorders caused by single genes. In this review, we focus on …