Evaluation of Gene Flow from GM to Non-GM Rice

Abstract

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT Gene flow events from genetically modified (GM) rice to adjacent non-GM rice lines naturally happen in the field. GM rice lines containing desirable agronomic traits such as tolerance to abiotic stresses and resistance to biotic stresses can be used to cross with non-GM cultivated rice and also to wild species of rice. This event can eventually lead to offspring which possess traits that allows a better chance of survival in the field. However this phenomenon has the possibility to produce undesirable effect in the environment surrounding the rice field. The objective of this study was to determine the out-crossing rate of GM rice to cultivated rice. Transgenic rice, Hwangkembyeo (containing beta-carotene enhancing gene and bar gene) and cultivated rice, Nakdongbyeo (mother plant of Hwangkembyeo) were used in this study. Results showed that most gene flow events occurred within 1 m range. In particular, gene flow events mostly happened within 30 cm, while it was rarely observed beyond 90 cm range. The maximum distance for gene flow event was observed at 6 m range however the sharp cut point distance was observed at 60-90 cm range. The prevailing gene flow direction was Northwest (NW) which coincided with the prevailing wind of Southeastern (SE) direction. Wind direction and distance were found to be the most important factors for determining rice out-crossing rate. But for more accurate prevention of GM gene flow, many factors should be considered like the local weather condition, wind direction, wind speed and flowering time.

Model-based calculating tool for pollen-mediated gene flow frequencies in plants

“…Because this tool is based on the deterministic model and include determined parameters for PMGF calculation, the calculated PMGF frequencies are determined for different distances, without confidence intervals. The model predicted PMGF frequencies (0.46, 0.32, 0.22 and 0.12 %) at the distance intervals of 0.3, 1.2, 2.4 and 6 m based on the calculating tool are similar to those (0.30–0.97, 0.05–0.33, 0.02–0.22 and 0.02–0.07 %) obtained from the PMGF experiments at the corresponding distance intervals (see Table 3 in Bae et al 2013).

Figure 3Gene flow in rice case study.

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“…PMGE frequencies of rice . Using rice crop-to-crop gene flow as an example, we estimated PMGF frequencies of this crop by including five parameters obtained from published results: pollen diameter to be 40 μm, pollen release height to be 0.5 m, outcrossing rate to be 1 %, crossability as 90 % and wind speed to be 1 m s − 1 ( Bae et al 2013 ; Wang et al 2016 ).…”

“…To examine the predicting power of the calculating tool, we compared the crop-to-crop PMGF frequencies generated from this model-based tool and those obtained from published PMGF experiments, using rice, wheat and maize as case studies ( Weekes et al 2007 ; Beckie et al 2011 ; Bae et al 2013 ). We found that the predicted PMGF frequencies are similar to those from field experiments.…”

A study on the establishment of isolation distances for environmental release of biotech crops

“…(Ko et al, 2016), 환경방출 모니터링 (Lee et al, 2014a;Lee et al, 2014b;Han et al, 2016), 비표적생물체에 대한 영향 평가 (Oh et al, 2016 a, b) 등 다양한 분야에서 수행되어 졌다. 화분비산을 통한 유전자이동 관련 연구는 작물별로 콩 (Kim, 2014;Lee et al, 2015), 벼 (An and Cho, 2009;Chun et al, 2011;Bae et al, 2014;Han et al, 2015), 고추 (Kim et al, 2009 a, b…”