ABSTRACT
Mexico is the center of origin of maize and one of the phenomena that imperil maize conservation is transgene presence. Although previous studies have documented transgene presence in Mexican landraces, to date there is no countrywide transgene monitoring protocol, nor systematic analyses assessing which factors could be related with transgene presence and dispersal. In this work, we propose a geographically representative sampling protocol and present empirical data from three sampled states: Mexico City, Oaxaca and Chiapas. To further investigate which environmental and social variables could be associated with transgene presence, we carried out a data mining approach. To assess transgene presence in collected maize samples, we used Real-Time PCR, finding that transgenes were widely distributed across sampled localities: 33% of the localities in Chiapas, 25% in Mexico City and 11% in Oaxaca. The data mining approach allowed us to identify state-specific spatial associations in Chiapas and Oaxaca. In Chiapas, a higher probability of transgene presence appeared related to the coexistence of industrialized maize agriculture, while in Oaxaca it was related with seed exchange. We discuss the importance of implementing a national biomonitoring protocol to increase our understanding of the sources that enable transgene presence and dispersal.
Highlights
A geographic-based nationwide sampling protocol was proposed for maize in Mexico; this approach could be adapted for transgene biomonitoring in other crops and other countries.
We applied this sampling protocol in three states, finding that transgenes are widely distributed across the analyzed states: Chiapas (33% of localities), Mexico City (25%), and Oaxaca (11%).
This is the first time that transgenes are detected in Chiapas, which is one of the most agrodiverse areas of Mesoamerica.
A data mining approach suggests that transgenes in Chiapas are spatially associated with irrigated agriculture, while in Oaxaca they seem to be related with seed exchange dynamics.
Acknowledgments
To all the farmers, peasants, students, colleagues, and field and lab technicians that collaborated in this study. We would like to thank CONABIO for helping us collect environmental and social variables for the analysis. We also thank the two anonymous reviewers for their comments and suggestions, which helped improve this work. This research was supported by grants INECC/A1-003/2017, INECC/A1-006/2016 and CONACYT 2015-01-687 to E.R.A.B.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/21683565.2022.2146252