Single-Event Transgene Product Levels Predict Levels in Genetically Modified Breeding Stacks

Area of Science:

• Agricultural biotechnology
• Molecular biology
• Genetics

Background:

• Genetically modified (GM) crop assessments require measuring transgene product concentrations.
• Regulatory bodies often require data on stacked GM events, which combine multiple GM events.
• Evaluating potential unexpected transgene interactions in stacked events is crucial for risk assessment.

Purpose of the Study:

• To determine if transgene product concentrations in single GM events can predict concentrations in breeding stacks composed of those events.
• To provide data supporting the regulatory assessment of stacked GM events.

Main Methods:

• Compared transgene product concentrations in maize, soybean, and cotton breeding stacks with their respective single GM events.
• Analyzed concentrations across different plant tissue types and within grain/seed.
• Utilized scatter plots and calculated the coefficient of identity (I²).

Main Results:

• Transgene product concentrations in single GM events showed a strong correlation with concentrations in the breeding stacks containing them.
• The coefficient of identity (I²) analysis indicated that single-event data reliably predicts stacked-event expression levels.
• Variability in expression was well-accounted for by the line of identity (y=x).

Conclusions:

• Transgene product concentrations measured in single GM events are generally applicable to breeding stacks composed of those events.
• This finding supports the use of single-event data for food, feed, and environmental risk assessments of stacked GM crops.
• Streamlines the regulatory assessment process for complex GM events.