Identification of resistance to the Ga1-m gametophyte factor in maize

Due to maize's wind-driven pollination, non-target pollen contamination is problematic for producers and breeders. Maize gametophyte factors, specifically gametophyte factor 1 (ga1), have long been used to produce selectively pollinating phenotypes. The use of these factors is a cornerstone of commercial popcorn production, and they are used for a large range of other purposes, including preventing contamination by genetically modified pollen in organic production. However this system is at great risk from another allele at the ga1 locus, Ga1-m, which overcomes the selectively pollinating phenotypes. To further complicate this problem, the risk posed by this allele has been under-assessed. Here we reinterpret the key study on Ga1-s and report genetic resistance to the Ga1-m allele in maize lines that carry dominant gametophyte factors. We identified genetic resistance to the allele segregating in lines derived from four landraces, showed the resistance is heritable, and that it acts in full-strength and attenuated versions. Additionally, we have suggested the validity of evolutionary-based inquiry into our plant genetic resources, and provided some validation of this effort. Our results provide the first report of effective genetic resistance to pollination by the Ga1-m allele, providing an option to continue the use of genetic barriers to non-target pollination. A source of resistance to the Ga1-m allele allows research to be conducted about the allele itself, allowing for research into the possible existence of multiple versions of the allele and their distributions. We anticipate our research will be a starting point for identification of additional sources of resistance to the Ga1-m allele, specifically in popcorn production, where it is most immediately needed to prevent pollen contamination, as well as the eventual localization and mapping of the resistance alleles. We also believe the suggestion of evolutionary-based inquiry into plant genetic resources will provide a highly effective method for identification of specific traits, but will need more extensive validation.