Abstract

DNA-based methodology employing quantitative polymerase chain reaction (qPCR) has been successfully used to examine the incidence of genetically modified (GM) maize in Mali. This study aims to ascertain whether screening elements could also be used to detect GM maize. Fourteen maize varieties and one unknown dark color seeded variety from Mali were tested. DNA was extracted from three seeds of each variety. Three screening elements were used for qPCR amplification, the 35s promoter of the Cauliflower mosaic virus (CaMV), the nopaline synthase (NOS terminator) from Agrobacterium tumefaciens and the 35s promoter from the Figwort mosaic virus (FMV). The 14 varieties were negative for P35s CaMV (forward) and T-NOS (reverse) markers. In contrast, the unknown dark color seeded variety was positive with 94 bp PCR product. While, no DNA fragments were amplified using the FMV as the screening element. These data were supported by Ct values in which the 14 varieties had values above 50; whereas, the unknown variety showed values of 24.5 for P-35s-CaMV and 30 for the T-NOS. The study demonstrates the ability in detecting GM maize using screening elements and the usefulness of our laboratory in training and reinforcing regional concern about GMO circulation. Key words: Genetically modified organism (GMO) detection, quantitative polymerase chain reaction (qPCR), capacity building, maize, Mali.

Highlights

  • The human population in Sub-Saharan Africa is increasing at the rate of 2% per year and estimated at 1,061 billion in 2017

  • This study aims to ascertain whether screening elements could be used to detect genetically modified (GM) maize

  • Three screening elements were used for quantitative polymerase chain reaction (qPCR) amplification, the 35s promoter of the Cauliflower mosaic virus (CaMV), the nopaline synthase (NOS terminator) from Agrobacterium tumefaciens and the 35s promoter from the Figwort mosaic virus (FMV)

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Summary

Introduction

The human population in Sub-Saharan Africa is increasing at the rate of 2% per year (https://data.worldbank.org/region/sub-saharan-africa) and estimated at 1,061 billion in 2017 (https://data.worldbank.org/region/sub-saharan-africa). This exponential population growth in addition to erratic. Year of introduction Origin Djigui Fa. IITA Ibadan-Nigeria no release OPVs Appolo CIMMYT/IITA OPVs SotubaKa

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