A high-throughput amplicon sequencing approach for population-wide species diversity and composition survey.

Management of agricultural pests requires an understanding of pest species diversity, their interactions with beneficial insects and spatial-temporal patterns of pest abundance. Invasive and agriculturally important insect pests can build up very high populations, especially in cropping landscapes. Traditionally, sampling effort for species identification involves small sample sizes and is labour intensive. Here, we describe a multiprimer high throughput sequencing (HTS) metabarcoding method and associated analytical workflow for a rapid, intensive, high-volume survey of pest species compositions. We demonstrate our method using the taxonomically challenging Bemisia pest cryptic species complex as examples. The whiteflies Bemisia including the"tabaci" species are agriculturally important capable of vectoring diverse plant viruses that cause diseases and crop losses. Our multiprimer metabarcoding HTS amplicon approach simultaneously process high volumes of whitefly individuals, with efficiency to detect rare (i.e., 1%) test-species, while our improved whitefly primers for metabarcoding also detected beneficial hymenopteran parasitoid species from whitefly nymphs. Field-testing our redesigned Bemisia metabarcoding primer sets across the Tanzania, Uganda and Malawi cassava cultivation landscapes, we identified the sub-Saharan Africa 1 Bemisia putative species as the dominant pest species, with other cryptic Bemisia species being detected at various abundances. We also provide evidence that Bemisia species compositions can be affected by host crops and sampling techniques that target either nymphs or adults. Our multiprimer HTS metabarcoding method incorporated two overlapping amplicons of 472 bp and 518 bp that spanned the entire 657 bp 3' barcoding region for Bemisia, and is particularly suitable to molecular diagnostic surveys of this highly cryptic insect pest species complex that also typically exhibited high population densities in heavy crop infestation episodes. Our approach can be adopted to understand species biodiversity across landscapes, with broad implications for improving transboundary biosecurity preparedness, thus contributing to molecular ecological knowledge and the development of control strategies for high-density, cryptic, pest-species complexes.

Non-additive gene interactions underpin molecular and phenotypic responses in honey bee larvae exposed to imidacloprid and thymol.

Understanding the cumulative risk of chemical mixtures at environmentally realistic concentrations is a key challenge in honey bee ecotoxicology. Ecotoxicogenomics, including transcriptomics, measures responses in individual organisms at the molecular level which can provide insights into the mechanisms underlying phenotypic responses induced by one or more stressors and link impacts on individuals to populations. Here, fifth instar honey bee larvae were sampled from a previously reported field experiment exploring the phenotypic impacts of environmentally realistic chronic exposures of the pesticide imidacloprid (5 µg.kg-1 for six weeks) and the acaricide thymol (250 g.kg-1 applied via Apiguard gel in-hive for four weeks), both separately and in combination. RNA-seq was used to discover individual and interactive chemical effects on larval gene expression and to uncover molecular mechanisms linked to reported adult and colony phenotypes. The separate and combined treatments had distinct gene expression profiles which represented differentially affected signaling and metabolic pathways. The molecular signature of the mixture was characterised by additive interactions in canonical stress responses associated with oxidative stress and detoxification, and non-additive interactions in secondary responses including developmental, neurological, and immune pathways. Novel emergent impacts on eye development genes correlated with long-term defects in visual learning performance as adults. This is consistent with these chemicals working through independent modes of action that combine to impact common downstream pathways, and highlights the importance of establishing mechanistic links between molecular and phenotypic responses when predicting effects of chemical mixtures on ecologically relevant population outcomes.

Standardized molecular diagnostic tool for the identification of cryptic species within the Bemisia tabaci complex.

BACKGROUND: The whitefly Bemisia tabaci complex harbours over 40 cryptic species that have been placed in 11 phylogenetically distinct clades based on the molecular characterization of partial mitochondrial DNA COI (mtCOI) gene region. Four cryptic species are currently within the invasive clade, i.e. MED, MEAM1, MEAM2 and IO. Correct identification of these species is a critical step towards implementing reliable measures for plant biosecurity and border protection; however, no standardized B. tabaci-specific primers are currently available which has caused inconsistencies in the species identification processes. RESULTS: We report three sets of polymerase chain reaction (PCR) primers developed to amplify the mtCOI region which can be used for genotyping MED, MEAM1 and IO species, and tested these primers on 91 MED, 35 MEAM1 and five IO individuals. PCR and sequencing of amplicons identified a total of 21, six and one haplotypes in MED, MEAM1 and IO respectively, of which six haplotypes were new to the B. tabaci database. CONCLUSION: These primer pairs enabled standardization and robust molecular species identification via mtCOI screening of the targeted invasive cryptic species and will improve quarantine decisions. Use of this diagnostic tool could be extended to other species within the complex. © 2017 Society of Chemical Industry.

The Trouble with MEAM2: Implications of Pseudogenes on Species Delimitation in the Globally Invasive Bemisia tabaci (Hemiptera: Aleyrodidae) Cryptic Species Complex.

Molecular species identification using suboptimal PCR primers can over-estimate species diversity due to coamplification of nuclear mitochondrial (NUMT) DNA/pseudogenes. For the agriculturally important whitefly Bemisia tabaci cryptic pest species complex, species identification depends primarily on characterization of the mitochondrial DNA cytochrome oxidase I (mtDNA COI) gene. The lack of robust PCR primers for the mtDNA COI gene can undermine correct species identification which in turn compromises management strategies. This problem is identified in the B. tabaci Africa/Middle East/Asia Minor clade which comprises the globally invasive Mediterranean (MED) and Middle East Asia Minor I (MEAM1) species, Middle East Asia Minor 2 (MEAM2), and the Indian Ocean (IO) species. Initially identified from the Indian Ocean island of Réunion, MEAM2 has since been reported from Japan, Peru, Turkey and Iraq. We identified MEAM2 individuals from a Peruvian population via Sanger sequencing of the mtDNA COI gene. In attempting to characterize the MEAM2 mitogenome, we instead characterized mitogenomes of MEAM1. We also report on the mitogenomes of MED, AUS, and IO thereby increasing genomic resources for members of this complex. Gene synteny (i.e., same gene composition and orientation) was observed with published B. tabaci cryptic species mitogenomes. Pseudogene fragments matching MEAM2 partial mtDNA COI gene exhibited low frequency single nucleotide polymorphisms that matched low copy number DNA fragments (<3%) of MEAM1 genomes, whereas presence of internal stop codons, loss of expected stop codons and poor primer annealing sites, all suggested MEAM2 as a pseudogene artifact and so not a real species.

Complete mitochondrial genome of the European Grapevine moth (EGVM) Lobesia botrana (Lepidoptera: Tortricidae).

The Lobesia botrana larvae feed on grapevine (Vitis vinifera L.), thereby reducing crop yield and increasing crop susceptibility to fungal and bacterial attacks. We determined the circular mitochondrial genome of L. botrana as 15 229 bp (GenBank KP677508) and contained 13 protein coding genes (PCG's), 22 transfer RNAs (tRNA), and two ribosomal RNAs. All tRNAs have the "clover-shaped" 2-D structures, while the tRNA-Ile which has the TψC-stem but lacked the TψC-loop. Knowledge of L. botrana mitochondrial genome represents a valuable molecular resource for developing effective DNA identification tools for biosecurity purposes and will contribute to better understanding of its evolutionary and population genetics.

Metabarcoding of benthic eukaryote communities predicts the ecological condition of estuaries.

DNA-derived measurements of biological composition have the potential to produce data covering all of life, and provide a tantalizing proposition for researchers and managers. We used metabarcoding to compare benthic eukaryote composition from five estuaries of varying condition. In contrast to traditional studies, we found biotic richness was greatest in the most disturbed estuary, with this being due to the large volume of extraneous material (i.e. run-off from aquaculture, agriculture and other catchment activities) being deposited in the system. In addition, we found strong correlations between composition and a number of environmental variables, including nutrients, pH and turbidity. A wide range of taxa responded to these environmental gradients, providing new insights into their sensitivities to natural and anthropogenic stressors. Metabarcoding has the capacity to bolster current monitoring techniques, enabling the decisions regarding ecological condition to be based on a more holistic view of biodiversity.

Discrimination of plant-parasitic nematodes from complex soil communities using ecometagenetics.

Many plant pathogens are microscopic, cryptic, and difficult to diagnose. The new approach of ecometagenetics, involving ultrasequencing, bioinformatics, and biostatistics, has the potential to improve diagnoses of plant pathogens such as nematodes from the complex mixtures found in many agricultural and biosecurity situations. We tested this approach on a gradient of complexity ranging from a few individuals from a few species of known nematode pathogens in a relatively defined substrate to a complex and poorly known suite of nematode pathogens in a complex forest soil, including its associated biota of unknown protists, fungi, and other microscopic eukaryotes. We added three known but contrasting species (Pratylenchus neglectus, the closely related P. thornei, and Heterodera avenae) to half the set of substrates, leaving the other half without them. We then tested whether all nematode pathogens-known and unknown, indigenous, and experimentally added-were detected consistently present or absent. We always detected the Pratylenchus spp. correctly and with the number of sequence reads proportional to the numbers added. However, a single cyst of H. avenae was only identified approximately half the time it was present. Other plant-parasitic nematodes and nematodes from other trophic groups were detected well but other eukaryotes were detected less consistently. DNA sampling errors or informatic errors or both were involved in misidentification of H. avenae; however, the proportions of each varied in the different bioinformatic pipelines and with different parameters used. To a large extent, false-positive and false-negative errors were complementary: pipelines and parameters with the highest false-positive rates had the lowest false-negative rates and vice versa. Sources of error identified included assumptions in the bioinformatic pipelines, slight differences in primer regions, the number of sequence reads regarded as the minimum threshold for inclusion in analysis, and inaccessible DNA in resistant life stages. Identification of the sources of error allows us to suggest ways to improve identification using ecometagenetics.

Improved inference of taxonomic richness from environmental DNA.

Accurate estimation of biological diversity in environmental DNA samples using high-throughput amplicon pyrosequencing must account for errors generated by PCR and sequencing. We describe a novel approach to distinguish the underlying sequence diversity in environmental DNA samples from errors that uses information on the abundance distribution of similar sequences across independent samples, as well as the frequency and diversity of sequences within individual samples. We have further refined this approach into a bioinformatics pipeline, Amplicon Pyrosequence Denoising Program (APDP) that is able to process raw sequence datasets into a set of validated sequences in formats compatible with commonly used downstream analyses packages. We demonstrate, by sequencing complex environmental samples and mock communities, that APDP is effective for removing errors from deeply sequenced datasets comprising biological and technical replicates, and can efficiently denoise single-sample datasets. APDP provides more conservative diversity estimates for complex datasets than other approaches; however, for some applications this may provide a more accurate and appropriate level of resolution, and result in greater confidence that returned sequences reflect the diversity of the underlying sample.

Impacts of inundation and drought on eukaryote biodiversity in semi-arid floodplain soils.

Floodplain ecosystems are characterized by alternating wet and dry phases and periodic inundation defines their ecological character. Climate change, river regulation and the construction of levees have substantially altered natural flooding and drying regimes worldwide with uncertain effects on key biotic groups. In southern Australia, we hypothesized that soil eukaryotic communities in climate change affected areas of a semi-arid floodplain would transition towards comprising mainly dry-soil specialist species with increasing drought severity. Here, we used 18S rRNA amplicon pyrosequencing to measure the eukaryote community composition in soils that had been depleted of water to varying degrees to confirm that reproducible transitional changes occur in eukaryotic biodiversity on this floodplain. Interflood community structures (3 years post-flood) were dominated by persistent rather than either aquatic or dry-specialist organisms. Only 2% of taxa were unique to dry locations by 8 years post-flood, and 10% were restricted to wet locations (inundated a year to 2 weeks post-flood). Almost half (48%) of the total soil biota were detected in both these environments. The discovery of a large suite of organisms able to survive nearly a decade of drought, and up to a year submerged supports the concept of inherent resilience of Australian semi-arid floodplain soil communities under increasing pressure from climatic induced changes in water availability.