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Deciphering host-parasitoid interactions and parasitism rates of crop pests using DNA metabarcoding

Sow Ahmadou, Brévault Thierry, Benoit Laure, Chapuis Marie Pierre, Galan Maxime, Coeur d'Acier Armelle, Delvare Gérard, Sembene Mbacké, Haran Julien. 2019. Deciphering host-parasitoid interactions and parasitism rates of crop pests using DNA metabarcoding. Scientific Reports, 9:3646, 12 p.

Journal article ; Article de recherche ; Article de revue à facteur d'impact Revue en libre accès total
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31. Sow et al. 2019 Parasitism rate crop pest metabarcoding_Sci-Rep.pdf

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Quartile : Q1, Sujet : MULTIDISCIPLINARY SCIENCES

Abstract : An accurate estimation of parasitism rates and diversity of parasitoids of crop insect pests is a prerequisite for exploring processes leading to efficient natural biocontrol. Traditional methods such as rearing have been often limited by taxonomic identification, insect mortality and intensive work, but the advent of high-throughput sequencing (HTS) techniques, such as DNA metabarcoding, is increasingly seen as a reliable and powerful alternative approach. Little has been done to explore the benefits of such an approach for estimating parasitism rates and parasitoid diversity in an agricultural context. In this study, we compared the composition of parasitoid species and parasitism rates between rearing and DNA metabarcoding of host eggs and larvae of the millet head miner, Heliocheilus albipunctella De Joannis (Lepidoptera, Noctuidae), collected from millet fields in Senegal. We first assessed the detection threshold for the main ten endoparasitoids, by sequencing PCR products obtained from artificial dilution gradients of the parasitoid DNAs in the host moth. We then assessed the potential of DNA metabarcoding for diagnosing parasitism rates in samples collected from the field. Under controlled conditions, our results showed that relatively small quantities of parasitoid DNA (0.07 ng) were successfully detected within an eight-fold larger quantity of host DNA. Parasitoid diversity and parasitism rate estimates were always higher for DNA metabarcoding than for host rearing. Furthermore, metabarcoding detected multi-parasitism, cryptic parasitoid species and differences in parasitism rates between two different sampling sites. Metabarcoding shows promise for gaining a clearer understanding of the importance and complexity of host-parasitoid interactions in agro-ecosystems, with a view to improving pest biocontrol strategies.

Mots-clés géographiques Agrovoc : Sénégal

Classification Agris : H10 - Pests of plants
L10 - Animal genetics and breeding

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Auteurs et affiliations

  • Sow Ahmadou, CIRAD-BIOS-UMR CBGP (FRA) - auteur correspondant
  • Brévault Thierry, CIRAD-PERSYST-UPR AIDA (SEN) ORCID: 0000-0003-0159-3509
  • Benoit Laure, CIRAD-BIOS-UMR CBGP (FRA)
  • Chapuis Marie Pierre, CIRAD-BIOS-UMR CBGP (FRA)
  • Galan Maxime, INRA (FRA)
  • Coeur d'Acier Armelle, INRA (FRA)
  • Delvare Gérard, CIRAD-BIOS-UMR CBGP (FRA)
  • Sembene Mbacké, University Cheikh Anta Diop of Dakar (SEN)
  • Haran Julien, CIRAD-BIOS-UMR CBGP (ZAF)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/591544/)

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