Dataset Information

Determining plant-leaf miner-parasitoid interactions: a DNA barcoding approach.

ABSTRACT: A major challenge in network ecology is to describe the full-range of species interactions in a community to create highly-resolved food-webs. We developed a molecular approach based on DNA full barcoding and mini-barcoding to describe difficult to observe plant-leaf miner-parasitoid interactions, consisting of animals commonly regarded as agricultural pests and their natural enemies. We tested the ability of universal primers to amplify the remaining DNA inside leaf miner mines after the emergence of the insect. We compared the results of a) morphological identification of adult specimens; b) identification based on the shape of the mines; c) the COI Mini-barcode (130 bp) and d) the COI full barcode (658 bp) fragments to accurately identify the leaf-miner species. We used the molecular approach to build and analyse a tri-partite ecological network of plant-leaf miner-parasitoid interactions. We were able to detect the DNA of leaf-mining insects within their feeding mines on a range of host plants using mini-barcoding primers: 6% for the leaves collected empty and 33% success after we observed the emergence of the leaf miner. We suggest that the low amplification success of leaf mines collected empty was mainly due to the time since the adult emerged and discuss methodological improvements. Nevertheless our approach provided new species-interaction data for the ecological network. We found that the 130 bp fragment is variable enough to identify all the species included in this study. Both COI fragments reveal that some leaf miner species could be composed of cryptic species. The network built using the molecular approach was more accurate in describing tri-partite interactions compared with traditional approaches based on morphological criteria.

SUBMITTER: Derocles SA

PROVIDER: S-EPMC4339730 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Determining plant-leaf miner-parasitoid interactions: a DNA barcoding approach.

Derocles Stéphane A P SA Evans Darren M DM Nichols Paul C PC Evans S Aifionn SA Lunt David H DH

PloS one 20150224 2

A major challenge in network ecology is to describe the full-range of species interactions in a community to create highly-resolved food-webs. We developed a molecular approach based on DNA full barcoding and mini-barcoding to describe difficult to observe plant-leaf miner-parasitoid interactions, consisting of animals commonly regarded as agricultural pests and their natural enemies. We tested the ability of universal primers to amplify the remaining DNA inside leaf miner mines after the emerge ...[more]

PMID: 25710377

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

Determining plant-leaf miner-parasitoid interactions: a DNA barcoding approach.

Publications

Determining plant-leaf miner-parasitoid interactions: a DNA barcoding approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets