Abstract

Transgenes encoding for insecticidal crystal (Cry) proteins from the soil-dwelling bacterium Bacillus Thuringiensis have been widely introduced into Genetically Modified (GM) crops to confer protection against insect pests. Concern that these transgenes may also harm beneficial or otherwise valued insects (so-called Non Target Organisms, NTOs) represents a major element of the Environmental Risk Assessments (ERAs) used by all countries prior to commercial release. Compiling a comprehensive list of potentially susceptible NTOs is therefore a necessary part of an ERA for any Cry toxin-containing GM crop. In partly-characterised and biodiverse countries, NTO identification is slowed by the need for taxonomic expertise and time to enable morphological identifications. This limitation represents a potentially serious barrier to timely adoption of GM technology in some developing countries. We consider Bt Cry1A cowpea (Vigna unguiculata) in Nigeria as an exemplar to demonstrate how COI barcoding can provide a simple and cost-effective means of addressing this problem. Over a period of eight weeks, we collected 163 insects from cowpea flowers across the agroecological and geographic range of the crop in Nigeria. These individuals included 32 Operational Taxonomic Units (OTUs) spanning four Orders and that could mostly be assigned to genus or species level. They included 12 Lepidopterans and two Coleopterans (both potentially sensitive to different groups of Cry proteins). Thus, barcode-assisted diagnoses were highly harmonised across groups (typically to genus or species level) and so were insensitive to expertise or knowledge gaps. Decisively, the entire study was completed within four months at a cost of less than 10,000 US$. The broader implications of the findings for food security and the capacity for safe adoption of GM technology are briefly explored.

Highlights

  • Agriculture is one of the key driving forces of the Nigerian economy [1] and ranks second only to the oil industry for the generation of foreign exchange income [2]

  • A single Neighbor Joining (NJ) tree featuring all field-captured insect COI sequences along with reference barcodes from ncbi and the CBOL databases comprised four major clusters corresponding to the Hymenoptera, Coleoptera, Diptera and Lepidoptera, and four subclusters within the Hymenopteran clade corresponding to bees within Xylocopa, Apis, Coelioxys/Megachile and Vespidae (Fig. 1)

  • NJ trees were generated for each cluster separately, and distances within and between species being calculated relative to barcode reference samples (Figs. 2, 3, 4, 5, 6)

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Summary

Introduction

Agriculture is one of the key driving forces of the Nigerian economy [1] and ranks second only to the oil industry for the generation of foreign exchange income [2]. This importance has led to an increasing desire to stimulate new growth into the Nigerian agricultural sector through technological advancement [3]. The possibility of adopting a biotechnological solution to the problem emerged recently following the production of a GM cowpea line that expresses the Cry1AB protein derived from Bacillus Thuringiensis (Bt) and is resistant to attack by Maruca [13]

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