Trap-based surveillance strategies are widely used for monitoring of invasive insect species, aiming to detect newly arrived exotic taxa as well as track the population levels of established or endemic pests. Where these surveillance traps have low specificity and capture non-target endemic species in excess of the target pests, the need for extensive specimen sorting and identification creates a major diagnostic bottleneck. While the recent development of standardized molecular diagnostics has partly alleviated this requirement, the single specimen per reaction nature of these methods does not readily scale to the sheer number of insects trapped in surveillance programmes. Consequently, target lists are often restricted to a few high-priority pests, allowing unanticipated species to avoid detection and potentially establish populations. DNA metabarcoding has recently emerged as a method for conducting simultaneous, multi-species identification of complex mixed communities and may lend itself ideally to rapid diagnostics of bulk insect trap samples. Moreover, the high-throughput nature of recent sequencing platforms could enable the multiplexing of hundreds of diverse trap samples on a single flow cell, thereby providing the means to dramatically scale up insect surveillance in terms of both the quantity of traps that can be processed concurrently and number of pest species that can be targeted. In this review of the metabarcoding literature, we explore how DNA metabarcoding could be tailored to the detection of invasive insects in a surveillance context and highlight the unique technical and regulatory challenges that must be considered when implementing high-throughput sequencing technologies into sensitive diagnostic applications.

Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance

Invasion, expansion, and control of Bactrocera dorsalis (Hendel) in China

Management of non-indigenous invasive species (NIS) is challenging owing in part to limitations of early detection and identification. The advent of environmental DNA (eDNA) techniques provides an efficient way to detect NIS when their abundance is extremely low. However, eDNA-based methods often suffer from uncertain detection sensitivity, which requires detailed testing before applying these methods in the field. Here we developed an eDNA tool for early detection of the highly invasive golden mussel, Limnoperna fortunei, based on the mitochondrial cytochrome c oxidase subunit I gene (COI). Further, we tested technical issues, including sampling strategy and detection sensitivity, based on a laboratory experiment. We then applied the method to field samples collected from water bodies in China where this mussel has or is expected to colonize. Results showed that the detection limit varied extensively among our newly developed primer pairs, ranging from 4 × 10−2 to 4 × 10−6 ng of total genomic DNA. Laboratory detection was affected by the availability of eDNA (i.e., both mussel abundance and incubation time). Detection capacity was higher in laboratory samples containing re-suspended matter from the bottom layer versus that collected from the surface. Among 25 field sites, detection was 100% at sites with high mussel abundance and as low as 40% at sites with low abundance when tested using our most sensitive primer pair. Early detection of NIS present at low abundance in nature requires not only sensitive primers, but also an optimized sampling strategy to reduce the occurrence of false negatives. Careful selection and detailed testing of primer pairs ensures effective eDNA-based species detection in surveillance and management programs.

Early detection of a highly invasive bivalve based on environmental DNA (eDNA)

Molecular techniques are powerful tools that can address many research problems in insect ecology. Mitochondrial DNA (mtDNA) is a widely used molecular marker. It is easy to use and has favorable biological properties, such as near-neutrality, lack of recombination, and a clock-like evolutionary rate. However, there are some issues involved when using mtDNA data in population genetics, species delimitation, and estimating the evolutionary history of populations and species. Exceptions to the simplicity of mitochondrial inheritance and other limitations include small effective population sizes, maternal inheritance, and complex evolutionary processes. Combining mtDNA and nuclear DNA markers can improve the power of molecular data to test phylogenetic and phylogeographic hypotheses. We review the applications of mtDNA in insect ecology and conclude that a better understanding of the properties of mitochondria is essential for the application of mtDNA.

/pdf/mitochondrial-dna-as-a-molecular-marker-in-insect-ecology-o16nryvcnd.pdf

Mitochondrial DNA as a Molecular Marker in Insect Ecology: Current Status and Future Prospects

Background 

Bactrocera dorsalis s.s. is a pestiferous tephritid fruit fly distributed from Pakistan to the Pacific, with the Thai/Malay peninsula its southern limit. Sister pest taxa, B. papayae and B. philippinensis, occur in the southeast Asian archipelago and the Philippines, respectively. The relationship among these species is unclear due to their high molecular and morphological similarity. This study analysed population structure of these three species within a southeast Asian biogeographical context to assess potential dispersal patterns and the validity of their current taxonomic status. Results 

Geometric morphometric results generated from 15 landmarks for wings of 169 flies revealed significant differences in wing shape between almost all sites following canonical variate analysis. For the combined data set there was a greater isolation-by-distance (IBD) effect under a ‘non-Euclidean’ scenario which used geographical distances within a biogeographical ‘Sundaland context’ (r2 = 0.772, P < 0.0001) as compared to a ‘Euclidean’ scenario for which direct geographic distances between sample sites was used (r2 = 0.217, P < 0.01). COI sequence data were obtained for 156 individuals and yielded 83 unique haplotypes with no correlation to current taxonomic designations via a minimum spanning network. BEAST analysis provided a root age and location of 540kya in northern Thailand, with migration of B. dorsalis s.l. into Malaysia 470kya and Sumatra 270kya. Two migration events into the Philippines are inferred. Sequence data revealed a weak but significant IBD effect under the ‘non-Euclidean’ scenario (r2 = 0.110, P < 0.05), with no historical migration evident between Taiwan and the Philippines. Results are consistent with those expected at the intra-specific level. Conclusions 

Bactrocera dorsalis s.s., B. papayae and B. philippinensis likely represent one species structured around the South China Sea, having migrated from northern Thailand into the southeast Asian archipelago and across into the Philippines. No migration is apparent between the Philippines and Taiwan. This information has implications for quarantine, trade and pest management.

Population structure of Bactrocera dorsalis s.s., B. papayae and B. philippinensis (Diptera: Tephritidae) in southeast Asia: evidence for a single species hypothesis using mitochondrial DNA and wingshape data

The invention discloses an integrated fluidic chip for identification of a fruit fly type and a use thereof The integrated microfluidic chip comprises specific primers for fruit fly type identification and a TaqMan-MGB probe The invention provides a fruit fly type molecular identification technology utilizing the integrated fluidic chip A test proves that the integrated microfluidic chip-based molecular identification technology realizes fast identification of a fruit fly type, has good specificity, high flux, a low cost and simple processes, realizes identification of a type of non-adult fruit fly or fruit fly adult residual body, provides a fast identification tool and technology for import and export plant quarantine and nationwide fruit fly epidemic monitoring, effectively prevents invasion and diffusion of dangerous fruit fly, protects agricultural production and ecological safety and promotes trade and economic development in China

Integrated fluidic chip for identification of fruit fly type and use thereof

Fruit flies in the family Tephritidae are the economically important pests that have many species complexes. DNA barcoding has gradually been verified as an effective tool for identifying species in a wide range of taxonomic groups, and there are several publications on rapid and accurate identification of fruit flies based on this technique; however, comprehensive analyses of large and new taxa for the effectiveness of DNA barcoding for fruit flies identification have been rare. In this study, we evaluated the COI barcode sequences for the diagnosis of fruit flies using 1426 sequences for 73 species of Bactrocera distributed worldwide. Tree-based [neighbour-joining (NJ)]; distance-based, such as Best Match (BM), Best Close Match (BCM) and Minimum Distance (MD); and character-based methods were used to evaluate the barcoding success rates obtained with maintaining the species complex in the data set, treating a species complex as a single taxon unit, and removing the species complex. Our results indicate that the average divergence between species was 14.04% (0.00-25.16%), whereas within a species this was 0.81% (0.00-9.71%); the existence of species complexes largely reduced the barcoding success for Tephritidae, for example relatively low success rates (74.4% based on BM and BCM and 84.8% based on MD) were obtained when the sequences from species complexes were included in the analysis, whereas significantly higher success rates were achieved if the species complexes were treated as a single taxon or removed from the data set - BM (98.9%), BCM (98.5%) and MD (97.5%), or BM (98.1%), BCM (97.4%) and MD (98.2%).

Existence of species complex largely reduced barcoding success for invasive species of Tephritidae: a case study in Bactrocera spp.

Invasive species can be detrimental to a nation's ecology, economy and human health Rapid and accurate diagnostics are critical to limit the establishment and spread of exotic organisms The increasing rate of biological invasions relative to the taxonomic expertise available generates a demand for high-throughput, DNA-based diagnostics methods for identification We designed species-specific qPCR primer and probe combinations for 27 economically important tephritidae species in six genera (Anastrepha, Bactrocera, Carpomya, Ceratitis, Dacus and Rhagoletis) based on 935 COI DNA barcode haplotypes from 181 fruit fly species publically available in BOLD, and then tested the specificity for each primer pair and probe through qPCR of 35 of those species We then developed a standardization reaction system for detecting the 27 target species based on a microfluidic dynamic array and also applied the method to identify unknown immature samples from port interceptions and field monitoring This method led to a specific and simultaneous detection for all 27 species in 75 h, using only 02 μL of reaction system in each reaction chamber The approach successfully discriminated among species within complexes that had genetic similarities of up to 9848%, while it also identified all immature samples consistent with the subsequent results of morphological examination of adults which were reared from larvae of cohorts from the same samples We present an accurate, rapid and high-throughput innovative approach for detecting fruit flies of quarantine concern This is a new method which has broad potential to be one of international standards for plant quarantine and invasive species detection

A high-throughput detection method for invasive fruit fly (Diptera: Tephritidae) species based on microfluidic dynamic array.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Fan Jiang

Author Tools

Chat about Author

Papers

Integrated fluidic chip for identification of fruit fly type and use thereof

Existence of species complex largely reduced barcoding success for invasive species of Tephritidae: a case study in Bactrocera spp.

A high-throughput detection method for invasive fruit fly (Diptera: Tephritidae) species based on microfluidic dynamic array.