With a large number of genetically modified organisms (GMOs) entering the food and feed markets, it is now urgent to develop effective and efficient GMO detection methods. We present here a novel GMO detection method, named GmoDetector, which was designed to detect nearly all of the known transgenic elements and GMO events of GM crops and plants. We adopted in GmoDetector targeted enrichment of the DNA segments specific to the transgenic elements and GMO events, deep-sequencing profiling of the targeted sequences, and detailed bioinformatics analysis of sequencing data. GmoDetector was able to detect GMOs in the forms of grains, fresh plant leaves , and processed food. In comparison to the existing, dominating PCR-based GMO detection methods, GmoDetector was shown to be accurate, sensitive, and efficient to detect GM plants with mixed multiple GMOs and with a very low (e.g., as low as 0.1%) concentration of GMO materials. GmoDetector has recently been adopted to develop a Chinese national standard for GMO detection.