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


Sow, Ahmadou et al. (2019), Data from: Deciphering host-parasitoid interactions and parasitism rates of crop pests using DNA metabarcoding, Dryad, Dataset,


An accurate estimation of parasitism rate and diversity in insect pests is a prerequisite to explore processes leading to efficient natural biocontrol. While traditional methods, such as rearing, is often limited to taxonomic identification, mortality and intensive work. The advent of high-throughput sequencing (HTS) techniques, such as DNA metabarcoding, is increasingly seen as a reliable and powerful alternative approach. However, benefits from such an approach to estimate parasitism rate and diversity in an agricultural context have been poorly explored. In this study, we compared the parasitoid species composition and parasitism rates between rearing and DNA metabarcoding of host eggs and larvae of the millet head miner, Heliocheilus albipunctella (de Joannis), collected from millet fields in Senegal. We first assessed the detection threshold of ten main endoparasitoids by sequencing PCR products of artificial dilution gradients of the DNA target in host DNA. We then assessed the potential of DNA metabarcoding, to diagnose parasitism rates from field-collected samples. Our results showed that, under controlled conditions, relative low quantities of parasitoid DNA were successfully detected within a eight-fold higher quantity of host DNA. Parasitoid diversity and parasitism rates were always higher through DNA metabarcoding than that obtained from host rearing. Furthermore, metabarcoding detected multi-parasitism, cryptic parasitoid species, and differences of parasitism rate between two contrasted sampling sites. Metabarcoding is a promising avenue to better understand the importance and complexity of host-parasitoid interactions in agroecosystems, to improve pest biocontrol strategies.

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