Assessment of a direct hybridization microarray strategy for comprehensive monitoring of genetically modified organisms (GMOs)

GMOIT: a tool for effective screening of genetically modified crops

BACKGROUND

Advancement in agricultural biotechnology has resulted in increasing numbers of commercial varieties of genetically modified (GM) crops worldwide. Though several databases on GM crops are available, these databases generally focus on collecting and providing information on transgenic crops rather than on screening strategies. To overcome this, we constructed a novel tool named, Genetically Modified Organisms Identification Tool (GMOIT), designed to integrate basic and genetic information on genetic modification events and detection methods.

RESULTS

At present, data for each element from 118 independent genetic modification events in soybean, maize, canola, and rice were included in the database. Particularly, GMOIT allows users to customize assay ranges and thus obtain the corresponding optimized screening strategies using common elements or specific locations as the detection targets with high flexibility. Using the 118 genetic modification events currently included in GMOIT as the range and algorithm selection results, a "6 + 4" protocol (six exogenous elements and four endogenous reference genes as the detection targets) covering 108 events for the four crops was established. Plasmids pGMOIT-1 and pGMOIT-2 were constructed as positive controls or calibrators in qualitative and quantitative transgene detection.

CONCLUSIONS

Our study provides a simple, practical tool for selecting, detecting, and screening strategies for a sustainable and efficient application of genetic modification.

Research Progress of Nucleic Acid Detection Technology for Genetically Modified Maize

Genetically modified (GM) maize is one of the earliest GM crops to have achieved large-scale commercial cultivation globally, and it is of great significance to excel in the development and implementation of safety policy regarding GM, and in its technical oversight. This article describes the general situation regarding genetically modified maize, including its varieties, applications, relevant laws and regulations, and so on. From a technical point of view, we summarize and critically analyze the existing methods for detecting nucleic acid levels in genetically modified maize. The nucleic acid extraction technology used for maize is explained, and the introduction of traditional detection techniques, which cover variable-temperature and isothermal amplification detection technology and gene chip technology, applications in maize are described. Moreover, new technologies are proposed, with special attention paid to nucleic acid detection methods using sensors. Finally, we review the current limitations and challenges of GM maize nucleic acid testing and share our vision for the future direction of this field.

Review of CRISPR/Cas Systems on Detection of Nucleotide Sequences

Nowadays, with the rapid development of biotechnology, the CRISPR/Cas technology in particular has produced many new traits and products. Therefore, rapid and high-resolution detection methods for biotechnology products are urgently needed, which is extremely important for safety regulation. Recently, in addition to being gene editing tools, CRISPR/Cas systems have also been used in detection of various targets. CRISPR/Cas systems can be successfully used to detect nucleic acids, proteins, metal ions and others in combination with a variety of technologies, with great application prospects in the future. However, there are still some challenges need to be addressed. In this review, we will list some detection methods of genetically modified (GM) crops, gene-edited crops and single-nucleotide polymorphisms (SNPs) based on CRISPR/Cas systems, hoping to bring some inspiration or ideas to readers.

Development of an inclusive 580K SNP array and its application for genomic selection and genome-wide association studies in rice

Rice is a globally cultivated crop and is primarily a staple food source for more than half of the world's population. Various single-nucleotide polymorphism (SNP) arrays have been developed and utilized as standard genotyping methods for rice breeding research. Considering the importance of SNP arrays with more inclusive genetic information for GWAS and genomic selection, we integrated SNPs from eight different data resources: resequencing data from the Korean World Rice Collection (KRICE) of 475 accessions, 3,000 rice genome project (3 K-RGP) data, 700 K high-density rice array, Affymetrix 44 K SNP array, QTARO, Reactome, and plastid and GMO information. The collected SNPs were filtered and selected based on the breeder's interest, covering all key traits or research areas to develop an integrated array system representing inclusive genomic polymorphisms. A total of 581,006 high-quality SNPs were synthesized with an average distance of 200 bp between adjacent SNPs, generating a 580 K Axiom Rice Genotyping Chip (580 K _ KNU chip). Further validation of this array on 4,720 genotypes revealed robust and highly efficient genotyping. This has also been demonstrated in genome-wide association studies (GWAS) and genomic selection (GS) of three traits: clum length, heading date, and panicle length. Several SNPs significantly associated with cut-off, -log₁₀ p-value >7.0, were detected in GWAS, and the GS predictabilities for the three traits were more than 0.5, in both rrBLUP and convolutional neural network (CNN) models. The Axiom 580 K Genotyping array will provide a cost-effective genotyping platform and accelerate rice GWAS and GS studies.

Quantitative analysis of genetically modified soya using multiple reaction monitoring mass spectrometry with endogenous peptides as internal standards

A simple label-free method was developed for the quantification of the herbicide-resistant gene-related protein 5-enolpyruvylshikimate-3-phosphate synthase using multiple reaction monitoring liquid chromatography-mass spectrometry. Sample pretreatment procedures including ion exchange chromatography and CaCl2 precipitation were used to purify the 5-enolpyruvylshikimate-3-phosphate synthase protein. Quantification of various percentages of genetically modified soya (0.5-100%) was performed by selecting suitable endogenous soybean peptides as internal standards. Results indicated that Gly P (QGDVFVVPR) and Lec P (LQLNK) are useful internal standards for the quantification of low and high percentages of genetically modified soya, respectively. Linear regression analysis of both calibration curves yielded good linearity with R2 of 0.99. This approach is a convenient and accurate quantification method for genetically modified soya at a level as low as 0.5% (less than the current EU threshold for labeling genetically modified soya).

Inter-laboratory validation of visual loop-mediated isothermal amplification assays for GM contents screening

Loop-mediated isothermal amplification (LAMP) has been widely used in many fields of molecular diagnostics, including detection of genetically modified organisms (GMOs). Herein, we report a collaborative ring trial validation of three established visual LAMP assays targeting three common GM elements, namely CaMV35S promoter, FMV35S promoter and NOS terminator, respectively. The high specificity of each assay was confirmed in different GM events analyses, and the sensitivity of each was determined to be 10, 10, and 50 haploid genome equivalents (HGEs) for CaMV35S promoter, FMV35S promoter, and NOS terminator, respectively. The probability of detection was also determined based on specificity and sensitivity data from 10 participating laboratories that returned correct results for the practical sample tests. These results demonstrate that the three visual LAMP assays are sensitive and time-saving, with high application potential for on-spot testing and routine screening of GMOs.

Panorama general de los organismos genéticamente modificados en Colombia y en el mundo: Capacidad nacional de detección

Los organismos genéticamente modificados (OGM) y en particular los cultivos genéticamente modificados (GM), son el resultado de la modificación de la información genética de una especie a partir del uso de la biotecnología moderna para proporcionar nuevas características que su contraparte no modificada no posee, tales como resistencia a insectos, tolerancia a herbicidas, contenido de nutrientes entre otros. La mayor parte de estos cultivos se concentran en cuatro productos: soya (Glycine max), maíz (Zea Mays), canola (Brassica napus) y algodón (Gossypium hirsutum); y los principales productores son Estados Unidos, Brasil, Argentina, India y Canadá. Por su parte, Colombia ocupa el puesto 18 con cultivos de maíz, algodón y claveles azules. La introducción de estas especies en cualquier mercado está limitada por la legislación propia del país destino, así como por los estudios que permiten establecer su efecto sobre el medio ambiente, la salud humana y animal; en este sentido, la precisión y confianza de las técnicas analíticas empleadas en la evaluación del contenido de OGM son un elemento importante para la toma de decisiones basadas en evidencias objetivas, especialmente frente al debate en torno a su uso. Este documento presenta una revisión de las tecnologías de análisis más importantes disponibles a nivel mundial, frente a las capacidades nacionales para su detección.

Critical assessment of digital PCR for the detection and quantification of genetically modified organisms

The number of genetically modified organisms (GMOs) on the market is steadily increasing. Because of regulation of cultivation and trade of GMOs in several countries, there is pressure for their accurate detection and quantification. Today, DNA-based approaches are more popular for this purpose than protein-based methods, and real-time quantitative PCR (qPCR) is still the gold standard in GMO analytics. However, digital PCR (dPCR) offers several advantages over qPCR, making this new technique appealing also for GMO analysis. This critical review focuses on the use of dPCR for the purpose of GMO quantification and addresses parameters which are important for achieving accurate and reliable results, such as the quality and purity of DNA and reaction optimization. Three critical factors are explored and discussed in more depth: correct classification of partitions as positive, correctly determined partition volume, and dilution factor. This review could serve as a guide for all laboratories implementing dPCR. Most of the parameters discussed are applicable to fields other than purely GMO testing. Graphical abstract There are generally three different options for absolute quantification of genetically modified organisms (GMOs) using digital PCR: droplet- or chamber-based and droplets in chambers. All have in common the distribution of reaction mixture into several partitions, which are all subjected to PCR and scored at the end-point as positive or negative. Based on these results GMO content can be calculated.

Molecular Approaches for High Throughput Detection and Quantification of Genetically Modified Crops: A Review

As long as the genetically modified crops are gaining attention globally, their proper approval and commercialization need accurate and reliable diagnostic methods for the transgenic content. These diagnostic techniques are mainly divided into two major groups, i.e., identification of transgenic (1) DNA and (2) proteins from GMOs and their products. Conventional methods such as PCR (polymerase chain reaction) and enzyme-linked immunosorbent assay (ELISA) were routinely employed for DNA and protein based quantification respectively. Although, these Techniques (PCR and ELISA) are considered as significantly convenient and productive, but there is need for more advance technologies that allow for high throughput detection and the quantification of GM event as the production of more complex GMO is increasing day by day. Therefore, recent approaches like microarray, capillary gel electrophoresis, digital PCR and next generation sequencing are more promising due to their accuracy and precise detection of transgenic contents. The present article is a brief comparative study of all such detection techniques on the basis of their advent, feasibility, accuracy, and cost effectiveness. However, these emerging technologies have a lot to do with detection of a specific event, contamination of different events and determination of fusion as well as stacked gene protein are the critical issues to be addressed in future.

Monitoring the prevalence of genetically modified maize in commercial animal feeds and food products in Turkey

BACKGROUND

EU legislation strictly controls use of genetically modified (GM) crops in food and feed products, and requires them to be labelled if the total GM content is greater than 9 g kg(-1) (for approved GM crops). We screened maize-containing food and feed products from Turkey to assess the prevalence of GM material.

RESULTS

With this aim, 83 food and feed products - none labelled as containing GM material - were screened using multiplex real-time polymerase chain reaction (PCR) for four common GM elements (35S/NOS/bar/FMV). Of these, 18.2% of feeds and 6% of food samples tested positive for one or more of these elements, and were subjected to event-specific PCR to identify which GM organisms they contained. Most samples were negative for the approved GM events tested, suggesting that they may contain adventitious GM contaminants. One sample was shown to contain an unapproved GM event (MON810, along with GA21) at a concentration well above the statutory labelling requirement.

CONCLUSION

Current legislation has restricted the penetration of GM maize into the Turkish food industry but not eliminated it, and the proliferation of different GM events is making monitoring increasingly complex. Our results indicate that labelling requirements are not being followed in some cases. © 2015 Society of Chemical Industry.