High-Resolution Gene Flow Model for Assessing Environmental Impacts of Transgene Escape Based on Biological Parameters and Wind Speed.

Patsy Haccou,Lei Wang,Bao-Rong Lu

doi:10.1371/journal.pone.0149563

Patsy Haccou, Lei Wang + Show 1 more

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https://doi.org/10.1371/journal.pone.0149563

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Abstract

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.

Highlights

The potential environmental impact caused by transgene flow from a genetically engineered (GE) crop to its non-GE counterparts and to wild relatives through pollen-mediated gene flow (PMGF) has aroused great biosafety concerns worldwide, PLOS ONE | DOI:10.1371/journal.pone.0149563 March 9, 2016Accurate Gene Flow Model Based on Biological Parameters and Wind Speed as a result of the extensive global cultivation of GE crops [1,2]
Crop-to-wild PMGF is documented in wild/weedy relative species of rice [13,14], wheat [15], maize [16], sorghum [17], oilseed rape [18], sugar beet [19], soybean [20], and potato [21]. All these results indicate the potential of transgene escape to non-GE crops and wild relative species of the crops through PMGF, from which the undesired environmental impacts become a great concern with the commercialization of GE crops worldwide
We established a new pollen-mediated gene flow (PMGF) model based on the quasi-mechanistic model of Rong et al 2010 [26], by replacing the exponential function in the quasi-mechanistic model with the adjusted inverse Gaussian function of Katul et al 2005 [36]

Summary

Introduction

The potential environmental impact caused by transgene flow from a genetically engineered (GE) crop to its non-GE counterparts (crop-to-crop) and to wild relatives (crop-to-wild) through pollen-mediated gene flow (PMGF) has aroused great biosafety concerns worldwide, PLOS ONE | DOI:10.1371/journal.pone.0149563 March 9, 2016Accurate Gene Flow Model Based on Biological Parameters and Wind Speed as a result of the extensive global cultivation of GE crops [1,2]. Crop-to-wild PMGF is documented in wild/weedy relative species of rice [13,14], wheat [15], maize [16], sorghum [17], oilseed rape [18], sugar beet [19], soybean [20], and potato [21]. All these results indicate the potential of transgene escape to non-GE crops and wild relative species of the crops through PMGF, from which the undesired environmental impacts become a great concern with the commercialization of GE crops worldwide. The accurate measurement and prediction of PMGF frequencies becomes the key to assessing and managing the environmental impact from transgene escape, when crop wild relatives are involved in such (trans)gene flow [1,2,3,4]

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