4.7 Article

Harnessing the power of next-generation sequencing technologies to the purpose of high-throughput pesticide resistance diagnosis

期刊

PEST MANAGEMENT SCIENCE
卷 76, 期 2, 页码 543-552

出版社

JOHN WILEY & SONS LTD
DOI: 10.1002/ps.5543

关键词

acetolactate-synthase; diagnosis; genotyping-by-sequencing; herbicide; illumina; resistance

资金

  1. Bayer CropScience France
  2. ANSES via the system for monitoring the adverse effects of plant protection products
  3. BASF SAS France

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BACKGROUND Next Generation Sequencing (NGS) technologies offer tremendous possibilities for high-throughput pesticide resistance diagnosis via massive genotyping-by-sequencing. Herein, we used Illumina sequencing combined with a simple, non-commercial bioinformatics pipe-line to seek mutations involved in herbicide resistance in two weeds. RESULTS DNA was extracted from 96 pools of 50 plants for each species. Three amplicons encompassing 15 ALS (acetolactate-synthase) codons crucial for herbicide resistance were amplified from each DNA extract. Above 18 and 20 million quality 250-nucleotide sequence reads were obtained for groundsel (Senecio vulgaris, tetraploid) and ragweed (Ambrosia artemisiifolia, diploid), respectively. Herbicide resistance-endowing mutations were identified in 45 groundsel and in eight ragweed field populations. The mutations detected and their frequencies assessed by NGS were checked by individual plant genotyping or Sanger sequencing. NGS results were fully confirmed, except in three instances out of 12 where mutations present at a frequency of 1% were detected below the threshold set for reliable mutation detection. CONCLUSION Analyzing 9600 plants requested 192 DNA extractions followed by 1728 PCRs and two Illumina runs. Equivalent results obtained by individual analysis would have necessitated 9600 individual DNA extractions followed by 216 000 genotyping PCRs, or by 121 500 PCRs and 40 500 Sanger sequence runs. This clearly demonstrates the interest and power of NGS-based detection of pesticide resistance from pools of individuals for diagnosing resistance in massive numbers of individuals. (c) 2019 Society of Chemical Industry

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