Project Number: 3655-21000-043-00
Project Type: Appropriated

Start Date: Oct 03, 2006
End Date: Aug 31, 2011

Objective:
The area occupied by transgenic crops in commercial production has risen dramatically in the last decade. As their use increases, knowledge is needed about gene flow-both the rate of spread of the transgenes to non-transgenic crops and to wild plants, and the impact of those transgenes. Quantitative predictions of gene flow are currently impossible for most crops because of lack of understanding of the factors that affect it, requiring case-by-case empirical assessment. Systemization of the underlying science is necessary for reliable modeling of gene flow. Because insect pollination benefits a large variety of crops we examine how distinct insect pollinators disperse pollen from plant to plant and ultimately among populations (gene flow). Crops that depend upon or benefit from insect pollination include some hay crops such as alfalfa and clovers, some oil-producing crops such as canola, together with the vast majority of fruits, vegetables and nuts especially when one considers seed and fruit production. A better understanding of how pollinators disperse pollen would facilitate our likelihood estimation of gene escape for different crops while also facilitating our search for alternative pollinators. Because the variation in pollinators needed to pursue such studies is currently not known for crop species or their wild relatives, we study the impact of insect pollinators on gene dispersal in the rocky mountain columbine. Knowledge obtained from this system will be later applied to insect-pollinated crops. In addition to studying the impact of pollinators on gene flow, we examine the consequences of a disease resistance transgene as it introgresses into wild squash populations. We study both direct effects on wild squash fitness and indirect effects on a major herbivore and the non-target pathogen it transmits. These data are critical to the efficient evaluation by regulatory agencies of the potential risk of transgenes introduced into wild plant populations. Objective 1: Using an insect-pollinated model system, elucidate principles and data requirements for better predictions of gene flow via pollen in insect-pollinated crops. Objective 2: Using squash with transgenic resistance to viral pathogens as a model system develop a methodology to assess the impact of this transgene recently introduced into the genome of a wild species.

Approach:
The number, types and acreages planted to transgenic crops are increasing. Consequently, there is a need to predict the likelihood of gene escape for different crops and a need to develop methodology to determine the impact of a transgene as it introgresses into wild populations. Because many crops benefit from insect pollination, part of our research investigates how distinct insect pollinators disperse pollen from plant to plant and ultimately among populations (gene flow). A better understanding of the impact of pollinator type on pollen dispersal would help us evaluate the differential risk of gene escape for distinct insect-pollinated crops while increasing our ability to select alternative pollinators for specific crops in the event of a major honeybee decline. On the one hand we study the impact of pollinator group on pollen dispersal and gene flow using the blue columbine as a model system. Information developed using this system will later be applied to different crops. On the other hand we examine the consequences of a disease resistance transgene that confers resistance to three economically important squash viruses as it introgresses into wild populations. We determine both the direct effects of the transgene on the fitness of free-living Cucurbita pepo (wild squash) and the indirect effects on diabroticite beetles (the primary non-target herbivore) and bacterial wilt (the major disease that these beetles transmit). In addition we measure gene flow among wild squash populations and gather basic information on their pollination biology and mating system. These types of data are critical to the efficient evaluation by regulatory agencies of the potential risk of transgenes introduced into wild plant populations.