Dataset Information

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

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.

SUBMITTER: Sow A

PROVIDER: S-EPMC6403368 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Sow Ahmadou A Brévault Thierry T Benoit Laure L Chapuis Marie-Pierre MP Galan Maxime M Coeur d'acier Armelle A Delvare Gérard G Sembène Mbacké M Haran Julien J

Scientific reports 20190306 1

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 be ...[more]

PMID: 30842584

Similar Datasets

Project description:Understanding interactions between herbivores and parasitoids is essential for successful biodiversity protection and monitoring and for biological pest control. Morphological identifications employ insect rearing and are complicated by insects' high diversity and crypsis. DNA barcoding has been successfully used in studies of host-parasitoid interactions as it can substantially increase the recovered real host-parasitoid diversity distorted by overlooked species complexes, or by species with slight morphological differences. However, this approach does not allow the simultaneous detection and identification of host(s) and parasitoid(s). Recently, high-throughput sequencing has shown high potential for surveying ecological communities and trophic interactions. Using mock samples comprising insect larvae and their parasitoids, we tested the potential of DNA metabarcoding for identifying individuals involved in host-parasitoid interactions to different taxonomic levels, and compared it to standard DNA barcoding and morphological approaches. For DNA metabarcoding, we targeted the standard barcoding marker cytochrome oxidase subunit I using highly degenerate primers, 2*300 bp sequencing on a MiSeq platform, and RTAX classification using paired-end reads. Additionally, using a large host-parasitoid dataset from a Central European floodplain forest, we assess the completeness and usability of a local reference library by confronting the number of Barcoding Index Numbers obtained by standard barcoding with the number of morphotypes. Overall, metabarcoding recovery was high, identifying 92.8% of the taxa present in mock samples, and identification success within individual taxonomic levels did not significantly differ among metabarcoding, standard barcoding, and morphology. Based on the current local reference library, 39.4% parasitoid and 90.7% host taxa were identified to the species level. DNA barcoding estimated higher parasitoid diversity than morphotyping, especially in groups with high level of crypsis. This study suggests the potential of metabarcoding for effectively recovering host-parasitoid diversity, together with more accurate identifications obtained from building reliable and comprehensive reference libraries, especially for parasitoids.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets