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Breeding by Design for Functional Rice with Genome Editing Technologies
Published on: January 3, 2025
Enhancing low-level genome-edited crop detection and identification in food mixtures using nanopore adaptive
Arno Stuyts1,2, Amin Zolfaghari1,2, Jolien D'aes1
1Sciensano, Transversal activities in Applied Genomics (TAG), Brussels, Belgium.
NPJ Science of Food
|May 11, 2026
Summary
Detecting genetically modified organisms (GMOs) in complex food mixtures is challenging. This study introduces adaptive sampling with high-throughput sequencing to efficiently identify specific GE lines within food samples.
Area of Science:
- Food Science
- Genetics
- Biotechnology
Background:
- European Union regulations mandate safety and traceability for genetically modified organisms (GMOs) and genome-edited (GE) organisms in the food chain.
- Detecting GE organisms is difficult due to subtle genetic differences (single nucleotide variations) from wild-type counterparts.
- Current high-throughput sequencing methods for genetic fingerprint detection are limited to pure samples, posing challenges for complex food matrices.
Purpose of the Study:
- To explore the use of high-throughput sequencing with adaptive sampling (AS) for detecting and identifying GE organisms in complex food mixtures.
- To reduce matrix complexity and enable targeted species enrichment for improved GE detection.
Main Methods:
- Developed and tested a proof-of-concept using high-throughput sequencing with adaptive sampling (AS) on mixtures of soybean and trace levels of GE or wild-type rice.
- Compared three sequencing modes: standard sequencing, AS enriching rice, and AS depleting soybean.
- Analyzed sequencing data to confirm enrichment and identification of the target rice line using its genetic fingerprint.
Main Results:
- Successfully demonstrated the feasibility of using adaptive sampling (AS) to selectively enrich target species (rice) within a complex food matrix (soybean).
- Confirmed the ability to detect and identify both GE and wild-type rice lines using their specific genetic fingerprints after AS enrichment.
- Showcased reduced matrix complexity and improved detection capabilities compared to standard sequencing.
Conclusions:
- Adaptive sampling (AS) with high-throughput sequencing is a promising approach for detecting and identifying genome-edited (GE) organisms in complex food mixtures.
- This method represents a significant advancement towards routine monitoring and enforcement of GE organism regulations in the food chain.
- Further development could facilitate regulatory compliance and ensure food safety and traceability.
