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.

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

“…First, we used a R preprocessing script (Sow et al., 2019) to merge paired‐end sequences into contigs with FLASH v.1.2.11 (Magoč & Salzberg, 2011) and to trim primers with CUTADAPT v.1.9.1 (Martin, 2011). We then used the FROGS pipeline (“Find Rapidly OTU with Galaxy Solution”; Escudié et al., 2018) to create an abundance table for each variant.…”

The impact of intragenomic rRNA variation on metabarcoding‐derived diversity estimates: A case study from marine nematodes

“…Degraded nematode specimens and low-quality host DNA may increase the chance of amplifying microbial associates, relic DNA, and gut contents, as well as be impacted by potential primer biases which may promote recovery of certain taxa over others (Lanner, Curto, Pachinger, Neumüller, & Meimberg, 2019;Sow et al, 2019).…”

In silicoand empirical evaluation of twelve COI & 16S metabarcoding primer sets for insectivorous diet analyses

“…First, we used a R pre-processing script (Sow et al, 2019) to merge pair sequences into contigs with FLASH v.1.2.11 (Magoc and Salzberg, 2011) and to trim primers with CUTADAPT v.1.9.1 (Martin, 2011). We then used the FROGS pipeline (‘Find Rapidly OTU with Galaxy Solution’, Escudié et al, 2018) to create an abundance table for each variant.…”