A new data-driven statistical model that incorporates the surrounding landscape in unprecedented detail describes the transfer of an inserted bacterial gene via pollen and seed dispersal in cotton plants more accurately than previously available methods.

Shannon Heuberger, a graduate student at the University of Arizona's College of Agriculture and Life Sciences, and her co-workers published their findings in the open access journal, PLoS ONE.

The transfer of genes from genetically modified crop plants is a hotly debated issue. Many consumers are concerned about the possibility of genetic material from transgenic plants mixing with non-transgenic plants on nearby fields. Producers, on the other side, have a strong interest in knowing whether the varieties they are growing are free from unwanted genetic traits.

Up until now, realistic models were lacking that could help growers and legislators assess and predict gene flow between genetically modified and non-genetically modified crops with satisfactory detail.

Likely to improve assessment of the transfer of genes between other plants

This study is the first to analyze gene flow of a genetically modified trait at such a comprehensive level. The new approach is likely to improve assessment of the transfer of genes between plants other than cotton as well.

"The most important finding was that gene flow in an agricultural landscape is complex and influenced by many factors that previous field studies have not measured," said Heuberger. "Our goal was to put a tool in the hands of growers, managers and legislators that allows them to realistically assess the factors that affect gene flow rates and then be able to extrapolate from that and decide how they can manage gene flow."

The researchers measured many factors in the field and developed a geographic information system-based analysis that takes into account the whole landscape surrounding a field to evaluate how it influences the transfer of genes between fields. Genes can be transferred in several ways, for example by pollinators such as bees, or through accidental seed mixing during farming operations.