Wang Lei, Haccou Patsy, Lu Bao-Rong
Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering, Department of Ecology and Evolutionary Biology, Fudan University, Handan Road 220, Shanghai 200433, China.
Leiden University College The Hague, P.O. Box 13228, 2501 EE The Hague, the Netherlands.
PLoS One. 2016 Mar 9;11(3):e0149563. doi: 10.1371/journal.pone.0149563. eCollection 2016.
Environmental impacts caused by transgene flow from genetically engineered (GE) crops to their wild relatives mediated by pollination are longstanding biosafety concerns worldwide. Mathematical modeling provides a useful tool for estimating frequencies of pollen-mediated gene flow (PMGF) that are critical for assessing such environmental impacts. However, most PMGF models are impractical for this purpose because their parameterization requires actual data from field experiments. In addition, most of these models are usually too general and ignored the important biological characteristics of concerned plant species; and therefore cannot provide accurate prediction for PMGF frequencies. It is necessary to develop more accurate PMGF models based on biological and climatic parameters that can be easily measured in situ. Here, we present a quasi-mechanistic PMGF model that only requires the input of biological and wind speed parameters without actual data from field experiments. Validation of the quasi-mechanistic model based on five sets of published data from field experiments showed significant correlations between the model-simulated and field experimental-generated PMGF frequencies. These results suggest accurate prediction for PMGF frequencies using this model, provided that the necessary biological parameters and wind speed data are available. This model can largely facilitate the assessment and management of environmental impacts caused by transgene flow, such as determining transgene flow frequencies at a particular spatial distance, and establishing spatial isolation between a GE crop and its coexisting non-GE counterparts and wild relatives.
由授粉介导的转基因作物与其野生近缘种之间的基因流动所造成的环境影响，是全球长期存在的生物安全问题。数学建模为估算花粉介导的基因流动（PMGF）频率提供了一个有用的工具，而该频率对于评估此类环境影响至关重要。然而，大多数PMGF模型在此目的上并不实用，因为其参数化需要来自田间试验的实际数据。此外，这些模型大多过于笼统，忽略了相关植物物种的重要生物学特性；因此无法为PMGF频率提供准确预测。有必要基于可在原位轻松测量的生物学和气候参数开发更准确的PMGF模型。在此，我们提出了一个准机制PMGF模型，该模型仅需要输入生物学和风速参数，而无需田间试验的实际数据。基于五组已发表的田间试验数据对准机制模型进行验证，结果表明模型模拟的和田间试验产生的PMGF频率之间存在显著相关性。这些结果表明，只要有必要的生物学参数和风速数据，使用该模型就能准确预测PMGF频率。该模型可极大地促进对转基因流动所造成的环境影响的评估和管理，例如确定特定空间距离处的转基因流动频率，以及在转基因作物与其共存的非转基因对应物和野生近缘种之间建立空间隔离。
