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Nannas Co-Authors Biolistic Transformation Study


Natalie Nannas
Natalie Nannas

A study on transgenics in maize by Assistant Professor of Biology Natalie Nannas and her colleagues at the University of Georgia was published in the journal Plant Cell earlier this year. “Genome-Scale Sequence Disruption Following Biolistic Transformation in Rice and Maize” presented the results of the group’s investigation of the effects of biolistic transformation – one of the two main techniques used to insert DNA into plant cells – on the plant genome.

The researchers looked at both maize and rice that were biolistically transformed with large fragments of viral transgenic DNA. Using whole genome sequencing, they found the transgenic DNA to be highly fragmented and rearranged, and the fragments were inserted all over the genome of both maize and rice. They also found evidence of large-scale chromosomal rearrangements.

Nannas said that she and her fellow researchers were surprised by the extent of the genome disruption. They noted that this finding highlights the need to refine the biolistic transformation method because many other off-target effects are occurring in the genome when this technique is used to introduce new DNA into plants.

Although the disruption is not dangerous for consumers, it could hinder the efforts of scientists and breeders to create new and useful genetically modified plants.

“If scientists are trying to introduce some beneficial new trait into a plant, such as ability to withstand drought, they might accidentally counteract that trait by breaking something important elsewhere in the genome,” Nannas and her team said. “When they look at the plants. It might seem as though the plant did not receive the new trait, but in reality they undid the very thing they are trying to create.

“It shows that we might be impeding our own aims and causing inefficiencies in making new GMOs. If we can modify the method of biolisitic transformation to be less damaging, we will be able to create new lines with beneficial traits faster and more efficiently,” Nannas and her colleagues concluded.

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