Development and Evaluation of Qualitative Detection Methods for Unapproved Genetically Modified Rice (LLRice)

Development of a rapid detection method for genetically modified rice using the ultra-fast PCR system

Genetically modified (GM) rice varieties containing traits such as tolerance to abiotic stress and resistance against pests and diseases continue to be developed. However, contamination incidents from unauthorized GM rice varieties have been encountered. To date, no GM rice crop has been authorized for consumption and/or commercialization in Korea. Therefore, to enhance safety management of unauthorized genetically modified organisms (GMOs), accurate and reliable detection methods are needed to identify GMOs in crops or products. In this study, we developed rapid detection methods for GM rice events (Bt63, KMD1, Kefeng6, Kefeng8, and LLRice62) using ultra-fast PCR system. Ultra-fast PCR is a state-of-the-art technology and decreases PCR run-times dramatically. However, the ultra-fast PCR is not widely used in GMO analysis. Thus, we designed a detection method for five events of GM rice and confirmed them by performing specificity, sensitivity, and applicability assays. All results demonstrate that the ultra-fast PCR system is a specific, sensitive, and reliable method to identify and monitor GM rice events. Additionally, it can be utilized as a rapid and simple method for GMO analysis in crops or processed products. This study can be used as a reference for future research on new analysis methods of unauthorized GMOs.

Detection and identification of multiple genetically modified events using DNA insert fingerprinting

Current screening and event-specific polymerase chain reaction (PCR) assays for the detection and identification of genetically modified organisms (GMOs) in samples of unknown composition or for the detection of non-regulated GMOs have limitations, and alternative approaches are required. A transgenic DNA fingerprinting methodology using restriction enzyme digestion, adaptor ligation, and nested PCR was developed where individual GMOs are distinguished by the characteristic fingerprint pattern of the fragments generated. The inter-laboratory reproducibility of the amplified fragment sizes using different capillary electrophoresis platforms was compared, and reproducible patterns were obtained with an average difference in fragment size of 2.4 bp. DNA insert fingerprints for 12 different maize events, including two maize hybrids and one soy event, were generated that reflected the composition of the transgenic DNA constructs. Once produced, the fingerprint profiles were added to a database which can be readily exchanged and shared between laboratories. This approach should facilitate the process of GMO identification and characterization.

[Development of new software (GiMlet) to analyze real-time PCR data based on TaqMan Chemistry and examination of factors affecting variance of the Ct values]

The primary data obtained from real-time PCR is the fluorescence intensity. We developed new software, GiMlet, to analyze the fluorescence data more effectively. To examine factors affecting the variance of the Ct values calculated from the fluorescence data, we conducted measurements of the same test solutions containing defined numbers of copies of the targeted DNA sequence using three kinds of real-time PCR equipment, namely, ABI PRISM 7500, 7700 and 7900HT, under consistent conditions, and analyzed the obtained fluorescence data using GiMlet. We also introduced a new baseline correction algorithm in GiMlet and examined the effect of this correction on the measurement results. The results revealed that the variances of the measured values and the PCR efficiency differed among the three kinds of real-time PCR equipment used and also according to the well-position of the PCR plate. The fluorescence data could be analyzed more precisely using the new algorithm.

[Factors affecting the variance of copy numbers in real-time PCR as estimated from calibration curves]

The distribution interval of calibration curves in real-time PCR was successfully predicted from the variance of the Ct values, and the predicted distribution interval was consistent with the interval of the actual calibration curves. Although the width of the 95% confidence interval at the lower end was about 1%, the copy number estimated from individual calibration curves was distributed over a wider range, and the 95% confidence interval of the estimates of 20 copies was +/-40%. The variances of the Ct values at 20 copies were significantly larger than those at higher copy numbers, and this large variation increased the distribution interval of the calibration curves. The variation, however, can be attributed to the probabilistic distribution of copy numbers in the measurement system, and is impossible to reduce by improvement of the analytical methodology. The 95% confidence interval of the calibration curves obtained after omitting 20 copies was decreased and the measurement precision was improved.