ReviewInternational journal of molecular sciences2026
Application of SNV Detection Methods for Market Control of Food Products from New Genomic Techniques.
Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
Abstract
The detection of single-nucleotide variants (SNVs) is an important challenge in modern genomics, with broad applications in medicine, diagnostics, and agricultural biotechnology. Current detection approaches include PCR-based techniques with high-affinity probes, ligase-based strategies, and sequencing approaches, each with varying degrees of sensitivity, specificity, and practicality. Despite advances in SNV analysis in the medical field, their implementation in the official control and monitoring of genetically modified organisms (GMOs) remains limited. This challenge has gained priority with the advent of new genomic techniques (NGTs), such as CRISPR-Cas nucleases, which allow precise genome editing, including subtle changes at the nucleotide level without introducing foreign DNA. Therefore, traditional methods of GMO detection targeting transgene sequences may not be sufficient to monitor such GMOs. In the European Union, GMO legislation requires distinguishing between conventionally bred and genetically modified plants. The planned introduction of new regulatory categories of NGT plants (NGT1 and NGT2) with different surveillance requirements emphasizes the need for robust, sensitive, and cost-effective SNV detection methods suitable for distinguishing between GMOs, particularly in the context of food and feed safety, traceability, and compliance.
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Registered trials
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