Reference: OC/EFSA/GMO/2021/01: Refinement of the Risk Assessment Methodology for Open Reading Frames in GMO Applications

A literature search was performed using PubMed to identify relevant studies on Open Reading Frames (ORFs) relevant to the risk assessment of GMOs. The collection of information on ORFs was steered by EFSA guidance for systematic reviews. The search queries allowed the retrieval a total of 15.484 non‐redundant references. The relevance of these documents was first assessed by screening titles and abstracts against specific inclusion and exclusion criteria related to risk assessment. This was followed by full‐text screening, which resulted in a total of 307 relevant documents. Information from these documents was extracted to emphasise criteria for the definition, prediction, and selection of ORFs, possibly highlighting the context of risk assessment of GMOs. Criteria such as codon identity, nucleotide composition, and mRNA secondary structure may be pertinent for developing new methods for risk assessment. However, the analysis revealed several limitations in the context of risk assessment, including the lack of structured data, diversity of application domains, paucity of information in food/feed, and the reliability of specific criteria for ORF definition, prediction and selection, among others. The analysis of prediction tools demonstrated that the generation of de novo experimental data or specific datasets is a critical factor. Nonetheless, certain features of ORF nucleotide sequences might prove useful in assessing the likelihood of expression of relevant ORFs for risk assessment of GMOs, but the criteria underlying this likelihood require further research and effort to be embedded in a tool. Bearing this in mind, and based on the information from the literature search, an evaluation was conducted regarding the potential of integrating various tools, their strengths and weaknesses and the challenge to integrate this knowledge into a single tool. A conceptual workflow is proposed for navigating these challenges and limitations and is presented as an attempt to integrate and streamline the tools and methods currently available.