Development of a CTAB buffer-based automated gDNA extraction method for the surveillance of GMO in seed

Efficient genetic transformation method for Eucalyptus genome editing

Plantation forestry of Eucalyptus urophylla × Eucalyptus grandis supplies high-quality raw material for pulp, paper, wood, and energy and thereby reduces the pressures on native forests and their associated biodiversity. Nevertheless, owing to the heterozygosity of the E. urophylla × E. grandis genetic background, germplasm improvement by crossbreeding tends to be inefficient. As an alternative approach, genetic engineering of Eucalyptus can be used to effectively improve germplasm resources. From a strategic standpoint, increasing the plantation productivity and wood quality by transgenic technology has become increasingly important for forest industry. In this study, we established a fluorescence labelling method using CRISPR/Cas9 technology to obtain positive transformed progenies. The positive transformed progenies were easily obtained from the genetically modified population via fluorescence screening. This system can be used as a plant genome site-specific editing tool and may be useful for improving Eucalyptus genetic resources.

A simple and accurate PCR method for detection of genetically modified rice

BACKGROUND

Legislation regulating for labeling and use of genetically modified (GM) crops are increased considerably worldwide in order to health and safety assurance of consumers. For this purpose, a polymerase chain reaction (PCR) method has been developed for detection of GM rice in people's food diet.

METHODS

In this study, eighty-one non-labeled rice samples were collected randomly from different market sites of Tehran, Iran. In order to analysis, rice genomic DNA was extracted using MBST DNA extraction kit and subsequently, sucrose phosphate synthase (SPS) gene was used to confirm the quality of extracted DNA. Then, cauliflower mosaic virus (CaMV) 35S promoter and Agrobacterium nopaline synthase (NOS) terminator were selected as screening targets for detection of GM rice sequences by PCR.

RESULTS

According to our results, 2 out of 81 (2.4%) samples tested were positive for CaMV 35S promoter while no positive result was detected for NOS terminator.

CONCLUSION

The obtained data indicated that this method is capable to identify the GM rice varieties. Furthermore, it can demonstrate the possibility of the presence of GM rice in Tehran's market, thus putting emphasis on the requirement for developing a precise approach to evaluate this product.

Development of event-specific qPCR detection methods for genetically modified alfalfa events J101, J163 and KK179

Genetically modified alfalfa is authorized for cultivation in several countries since 2005. On the other hand, cultivation in or export to the European Union is not allowed and thus neither certified reference material nor official event-specific detection methods are available. Therefore, based on patent sequence information, event-specific real-time PCR detection methods targeting the junction sequence of the alfalfa genome and the transgenic insert of the respective events J101, J163 and KK179 were developed. Newly developed plasmids were used as reference material for assay optimization and in-house validation. Plasmid standards were quantified using digital droplet PCR and LOD95%, PCR efficiency, robustness and specificity of the assays were determined using real-time PCR. A LOD95% of 10 copies per PCR reaction was observed and PCR efficiencies of 95-97 % were achieved. Different real-time PCR instruments and PCR conditions were applied to test for robustness of the assays using DNA at a concentration of 30 copies per μL for each gm alfalfa event. All replicates were positive independent of the instrument or the PCR condition. DNA from certified reference material of different genetically modified crops as well as reference materials of the three events was used to experimentally test for specificity. No unspecific amplification signal was observed for any of the assays. Validation results were in line with the "Minimum Performance Requirements for Analytical Methods of GMO Testing" of the European Network of GMO Laboratories. Furthermore, an inter-laboratory comparison study was conducted to show the transferability and applicability of the methods and to verify the assay performance parameters.

Optimization of digital droplet polymerase chain reaction for quantification of genetically modified organisms

•

Experience matrix condenses ddPCR performance parameters in graphical presentation.

•

Assay separation value based on absolute fluorescence signal distance and variation.

•

Separation value and experience matrix simplify choice of best assay parameters.

•

Influence of oligonucleotide concentration and annealing/extension temperature.

Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called ‘rain’. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis.

We developed an Excel based ‘experience matrix’ that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations.

The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

A statistical approach to quantification of genetically modified organisms (GMO) using frequency distributions

Background

According to Regulation (EU) No 619/2011, trace amounts of non-authorised genetically modified organisms (GMO) in feed are tolerated within the EU if certain prerequisites are met. Tolerable traces must not exceed the so-called ‘minimum required performance limit’ (MRPL), which was defined according to the mentioned regulation to correspond to 0.1% mass fraction per ingredient. Therefore, not yet authorised GMO (and some GMO whose approvals have expired) have to be quantified at very low level following the qualitative detection in genomic DNA extracted from feed samples. As the results of quantitative analysis can imply severe legal and financial consequences for producers or distributors of feed, the quantification results need to be utterly reliable.

Results

We developed a statistical approach to investigate the experimental measurement variability within one 96-well PCR plate. This approach visualises the frequency distribution as zygosity-corrected relative content of genetically modified material resulting from different combinations of transgene and reference gene Cq values. One application of it is the simulation of the consequences of varying parameters on measurement results. Parameters could be for example replicate numbers or baseline and threshold settings, measurement results could be for example median (class) and relative standard deviation (RSD). All calculations can be done using the built-in functions of Excel without any need for programming. The developed Excel spreadsheets are available (see section ‘Availability of supporting data’ for details). In most cases, the combination of four PCR replicates for each of the two DNA isolations already resulted in a relative standard deviation of 15% or less.

Conclusions

The aims of the study are scientifically based suggestions for minimisation of uncertainty of measurement especially in —but not limited to— the field of GMO quantification at low concentration levels. Four PCR replicates for each of the two DNA isolations seem to be a reasonable minimum number to narrow down the possible spread of results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0407-x) contains supplementary material, which is available to authorized users.