High-throughput detection of ALS-based resistance in the tetraploid common groundsel (<em>Senecio vulgaris</em>)

Abstract

International audienceThe Next Generation Sequencing (NGS) technologies offer tremendous possibilities for detecting and quantifying mutations endowing herbicide resistance in numerous samples. This would greatly assist resistance management by allowing monitoring numerous fields and/or analysing massive numbers of individual weeds. Yet, NGS use for herbicide resistance diagnosis purpose is very slow to emerge. Herein, we assessed the feasibility of herbicide resistance diagnosis using Illumina sequencing that is currently one of the leading NGS technology. Three PCR amplicons encompassing the eight ALS codons crucial for herbicide resistance (122, 197, 205, 376, 377, 574, 653 and 654) were amplified for both S. vulgaris ALS genes in each of 96 non-quantified DNA pools. Each pool consisted of DNA crudely extracted from 50 plants collected in one agricultural field where resistance was suspected (i.e., a total of 4,800 individual plants). The 96 pools were analysed in one single Illumina MiSeq run. A total of 20.8 million quality 250 nucleotide-long paired sequence reads were obtained. Mutant ALS alleles were identified in 61 of the 96 pools. Three previously characterised herbicide resistance-endowing mutations (Pro-197-Leu, Pro-197-Ser and/or Pro-197-Thr) were detected on ALS1 and four (Pro-197-Arg, Pro-197-Leu, Pro-197-Ser and/or Pro-197-Thr) on ALS2. To check the accuracy of NGS-based quantification of mutant ALS alleles, all individual plants in 34 of the 96 pools were individually submitted to ALS Sanger sequencing. The 34 pools were selected to represent the range of mutant ALS frequencies and the diversity of alleles identified using NGS. ALS alleles identified by Sanger sequencing were the same as those identified by NGS. Frequencies of mutant ALS alleles detected by NGS and by Sanger sequencing were very highly correlated (R²=0.986). This work demonstrated the feasibility and the reliability of NGS-based detection of mutations endowing herbicide resistance, and the interest of this approach for analysing large numbers of samples