675 Research Article Received: 3 February 2014 Revised: 18 April 2014 Accepted article published: 28 April 2014 Published online in Wiley Online Library: 27 May 2014 (wileyonlinelibrary.com) DOI 10.1002/ps.3818 Using next-generation sequencing to detect mutations endowing resistance to pesticides: application to acetolactate-synthase (ALS)-based resistance in barnyard grass, a polyploid grass weed Christophe Délye, a* Romain Causse, a Véronique Gautier, b Charles Poncet b and Séverine Michel a Abstract BACKGROUND: Next-generation sequencing (NGS) technologies offer tremendous possibilities for accurate detection of muta- tions endowing pesticide resistance, yet their use for this purpose has not emerged in crop protection. This study aims at promoting NGS use for pesticide resistance diagnosis. It describes a simple procedure accessible to virtually any scientist and implementing freely accessible programs for the analysis of NGS data. RESULTS: Three PCR amplicons encompassing seven codons of the acetolactate-synthase gene crucial for herbicide resistance were sequenced using non-quantified pools of crude DNA extracts from 40 plants in each of 28 field populations of barnyard grass, a polyploid weed. A total of 63959 quality NGS sequence runs were obtained using the 454 technology. Three herbicide-resistance-endowing mutations (Pro-197-Ser, Pro-197-Leu and/or Trp-574-Leu) were identified in seven populations. The NGS results were confirmed by individual plant Sanger sequencing. CONCLUSION: This work demonstrated the feasibility of NGS-based detection of pesticide resistance, and the advantages of NGS compared with other molecular biology techniques for analysing large numbers of individuals. NGS-based resistance diagnosis has the potential to play a substantial role in monitoring resistance, maintaining pesticide efficacy and optimising pesticide applications. © 2014 Society of Chemical Industry Keywords: resistance; pesticide; herbicide; diagnosis; next-generation sequencing; Echinochloa 1 INTRODUCTION Weeds, pests and pathogens are the major causes of agricultural crop yield losses worldwide, and crop protection is essential to safeguard food production. 1 Globally, crop protection currently relies largely on pesticide applications. However, the evolution of resistances to pesticides in a number of organisms is an increas- ing challenge to pesticide-based crop protection. 2 – 4 Resistance detection for the purpose of guidance of crop protection and/or resistance monitoring is crucial for resistance management 5 – 7 and demands effective and reliable methods. Resistance to pesticides evolves in weeds, pests and pathogens essentially as a result of adaptive selection of mutations conferring a decreased sensitivity to pesticides. 2 – 4 In the case of pesticide resistance, these mutations can cause a structural modification in the spatial structure of a pesticide target protein that will lead to a decrease in the efficacy of pesticide(s) (e.g. mutations causing an amino acid substitution at the pesticide-binding site of a target protein). Alternatively, mutations at the active site of a metabolic enzyme or a transporter protein can improve the activity of these proteins in pesticide neutralisation. Other resistance-endowing mutations can occur in gene regulatory regions and modify the expression of the pesticide target protein (i.e. overexpres- sion, which compensates for the pesticide inhibitory action), of pesticide-metabolising enzyme(s) or of transporter proteins in a way causing an increase in pesticide degradation or compartment- ing away from its site of action. 2 – 4 Mutations are thus the basis of pesticide resistance, and past research has identified quite a few resistance-endowing mutations. 3,8 Such mutations have long been a target of choice for DNA-based resistance detection assays, because such assays are reliable and allow rapid resistance diag- nosis and within-season adaptation of the spraying programme to avoid further selection of resistance. 3,9 However, the techniques ∗ Correspondence to: Christophe Délye, INRA, UMR1347 Agroécologie, 17 rue Sully, F-21000 Dijon, France. E-mail: delye@dijon.inra.fr a INRA, UMR1347 Agroécologie, Dijon, France b INRA, UMR1095 Génétique, Diversité et Écophysiologie des Céréales, Clermont-Ferrand, France Pest Manag Sci 2015; 71: 675–685 www.soci.org © 2014 Society of Chemical Industry