DNA metabarcoding for biodiversity monitoring in a national park: Screening for invasive and pest species

Enhancing amphibian biomonitoring through eDNA metabarcoding

Surveying biodiversity has taken a quantum leap with environmental DNA (eDNA) metabarcoding, an immensely powerful approach lauded for its efficiency, sensitivity, and non-invasiveness. This approach emerges as a game-changer for the elusive realm of endangered and rare species-think nocturnal, environmentally elusive amphibians. Here, we have established a framework for constructing a reliable metabarcoding pipeline for amphibians, covering primer design, performance evaluation, laboratory validation, and field validation processes. The Am250 primer, located on the mitochondrial 16S gene, was optimal for the eDNA monitoring of amphibians, which demonstrated higher taxonomic resolution, smaller species amplification bias, and more extraordinary detection ability compared to the other primers tested. Am250 primer exhibit an 83.8% species amplification rate and 75.4% accurate species identification rate for Chinese amphibians in the in silico PCR and successfully amplified all tested species of the standard samples in the in vitro assay. Furthermore, the field-based mesocosm experiment showed that DNA can still be detected by metabarcoding even days to weeks after organisms have been removed from the mesocosm. Moreover, field mesocosm findings indicate that eDNA metabarcoding primers exhibit different read abundances, which can affect the relative biomass of species. Thus, appropriate primers should be screened and evaluated by three experimental approaches: in silico PCR simulation, target DNA amplification, and mesocosm eDNA validation. The selection of a single primer set or multiple primers' combination should be based on the monitoring groups to improve the species detection rate and the credibility of results.

Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape

Context

Land use change drives both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting countryside biodiversity, public health, and livelihoods requires understanding the scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. Evidence increasingly shows that species richness for many taxa correlates with local tree cover.

Objectives

We investigated whether mosquito species richness, community composition, and presence of disease vector species responded to land use and tree cover - and if so, whether at spatial scales similar to other taxa.

Methods

We paired a field survey of mosquito communities in agricultural, residential, and forested lands in rural southern Costa Rica with remotely sensed tree cover data. We compared mosquito community responses to tree cover surrounding survey sites measured across scales, and analyzed community responses to land use and environmental gradients.

Results

Tree cover was positively correlated with mosquito species richness, and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus, particularly at small spatial scales of 80 - 200m. Land use predicted community composition and Ae. albopictus presence. Environmental gradients of tree cover, temperature, and elevation explained 7% of species turnover among survey sites.

Conclusions

The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa, including arthropods, and also confer protection against disease vector occurrence. The identified spatial range of tree cover benefits can inform land management for conservation and public health protection.

Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape

Context

Land use change drives both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting countryside biodiversity, public health, and livelihoods requires understanding the scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. Evidence increasingly shows that species richness for many taxa correlates with local tree cover.

Objectives

We investigated whether mosquito species richness, community composition, and presence of disease vector species responded to land use and tree cover - and if so, whether at spatial scales similar to other taxa.

Methods

We paired a field survey of mosquito communities in agricultural, residential, and forested lands in rural southern Costa Rica with remotely sensed tree cover data. We compared mosquito community responses to tree cover surrounding survey sites measured across scales, and analyzed community responses to land use and environmental gradients.

Results

Tree cover was positively correlated with mosquito species richness, and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus , particularly at small spatial scales of 80 - 200m. Land use predicted community composition and Ae. albopictus presence. Environmental gradients of tree cover, temperature, and elevation explained 7% of species turnover among survey sites.

Conclusions

The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa, including arthropods, and also confer protection against disease vector occurrence. The identified spatial range of tree cover benefits can inform land management for conservation and public health protection.

Non-destructive insect metabarcoding for surveillance and biosecurity in citrus orchards: recording the good, the bad and the psyllids

Background

The Australian citrus industry remains one of the few in the world to be unaffected by the African and the Asian citrus psyllids, Trioza erytreae Del Guercio and Diaphorina citri Kuwayama, respectively, and the diseases their vectored bacteria can cause. Surveillance, early detection, and strict quarantine measures are therefore fundamental to safeguard Australian citrus. However, long-term targeted surveillance for exotic citrus pests can be a time-consuming and expensive activity, often relying on manually screening large numbers of trap samples and morphological identification of specimens, which requires a high level of taxonomic knowledge.

Methods

Here we evaluated the use of non-destructive insect metabarcoding for exotic pest surveillance in citrus orchards. We conducted an 11-week field trial, between the months of December and February, at a horticultural research farm (SuniTAFE Smart Farm) in the Northwest of Victoria, Australia, and processed more than 250 samples collected from three types of invertebrate traps across four sites.

Results

The whole-community metabarcoding data enabled comparisons between different trapping methods, demonstrated the spatial variation of insect diversity across the same orchard, and highlighted how comprehensive assessment of insect biodiversity requires use of multiple complimentary trapping methods. In addition to revealing the diversity of native psyllid species in citrus orchards, the non-targeted metabarcoding approach identified a diversity of other pest and beneficial insects and arachnids within the trap bycatch, and recorded the presence of the triozid Casuarinicola cf warrigalensis for the first time in Victoria. Ultimately, this work highlights how a non-targeted surveillance approach for insect monitoring coupled with non-destructive DNA metabarcoding can provide accurate and high-throughput species identification for biosecurity and biodiversity monitoring.

Non-destructive insect metabarcoding as a surveillance tool for the Australian grains industry: a first trial for the iMapPESTS smart trap

Surveillance and long-term monitoring of insect pest populations are of paramount importance to limit dispersal and inform pest management. Molecular methods have been employed in diagnostics, surveillance and monitoring for the past few decades, often paired with more traditional techniques relying on morphological examinations. Within this context, the ‘iMapPESTS: Sentinel Surveillance for Agriculture’ project was conceptualised to enhance on-farm pest management decision-making via development and deployment of smart traps, able to collect insects, as well as recording associated environmental data. Here, we compared an iMapPESTS ‘Sentinel’ smart trap to an alternative suction trap over a 10-week period. We used a non-destructive insect metabarcoding approach complemented by insect morphological diagnostics to assess and compare aphid species presence and diversity across trap samples and time. Furthermore, we paired this with environmental data recorded throughout the sampling period. This methodology recorded a total of 497 different taxa from 70 traps over a 10-week period in the grain-growing region in western Victoria. This included not only the 14 aphid target species, but an additional 12 aphid species, including a new record for Victoria. Ultimately, with more than 450 bycatch species detected, this highlighted the value of insect metabarcoding, not only for pest surveillance, but also at a broader ecosystem level, with potential applications in integrated pest management and biocontrol.

Using DNA metabarcoding to assess insect diversity in citrus orchards

Background

DNA metabarcoding is rapidly emerging as a cost-effective approach for large-scale biodiversity assessment and pest monitoring. The current study employed metabarcoding to assess insect diversity in citrus orchards in Ganzhou City, Jiangxi, China in both 2018 and 2019. Insects were sampled using Malaise traps deployed in three citrus orchards producing a total of 43 pooled monthly samples.

Methods

The Malaise trap samples were sequenced following DNA metabarcoding workflow. Generated sequences were curated and analyzed using two cloud databases and analytical platforms, the barcode of life data system (BOLD) and multiplex barcode research and visualization environment (mBRAVE).

Results

These platforms assigned the sequences to 2,141 barcode index numbers (BINs), a species proxy. Most (63%) of the BINs were shared among the three sampling sites while BIN sharing between any two sites did not exceed 71%. Shannon diversity index (H') showed a similar pattern of BIN assortment at the three sampling sites. Beta diversity analysis by Jaccard similarity coefficient (J) and Bray-Curtis distance matrix (BC) revealed a high level of BIN similarity among the three sites (J = 0.67-0.68; BC = 0.19-0.20). Comparison of BIN records against all those on BOLD made it possible to identify 40% of the BINs to a species, 57% to a genus, 97% to a family and 99% to an order. BINs which received a species match on BOLD were placed in one of four categories based on this assignment: pest, parasitoid, predator, or pollinator. As this study provides the first baseline data on insect biodiversity in Chinese citrus plantations, it is a valuable resource for research in a broad range of areas such as pest management and monitoring beneficial insects in citrus gardens.

The efficiency of the COI gene as a DNA barcode and an overview of Orthoptera (Caelifera and Ensifera) sequences in the BOLD System

Orthoptera, among the oldest and most numerous insect lineages, is an excellent model for evolutionary studies but has numerous taxonomic problems. To mitigate these issues, the cytochrome c oxidase subunit I (COI), standardized with the DNA barcode for Metazoa, is increasingly used for specimen identification and species delimitation. We tested the performance of COI as a DNA barcode in Orthoptera, using two analyses based on intra- and interspecific distances, barcode gap and Probability of Correct Identification (PCI); and estimated species richness through Automatic Barcode Gap Discovery (ABGD) and Assemble Species by Automatic Partitioning (ASAP). We filtered all sequences of Orthoptera available in Barcode of Life Data System (BOLD) and used 11,605 COI sequences, covering 1,132 species, 226 genera, and 18 families. The overall average PCI was 73.86%. For 82.2% of genera the barcode gap boxplots were classified as good or intermediate, indicating that COI can be effective as a DNA barcode in Orthoptera, although with varying efficiency depending on the need for more information. ABGD and ASAP inferred species richness similar to labels informed by BOLD for the suborders Caelifera and Ensifera. The representation of Orthoptera in the BOLD database and the results of these analyses are discussed.

Reliability and Utility of Standard Gene Sequence Barcodes for the Identification and Differentiation of Cyst Nematodes of the Genus Heterodera

Difficulties inherent in the morphological identification of cyst nematodes of the genus Heterodera Schmidt, 1871, an important lineage of plant parasites, has led to broad adoption of molecular methods for diagnosing and differentiating species. The pool of publicly available sequence data has grown significantly over the past few decades, and over half of all known species of Heterodera have been characterized using one or more molecular markers commonly employed in DNA barcoding (18S, internal transcribed spacer [ITS], 28S, coxI). But how reliable are these data and how useful are these four markers for differentiating species? We downloaded all 18S, ITS, 28S, and coxI gene sequences available on the National Center for Biotechnology Information (NCBI) database, GenBank, for all species of Heterodera for which data were available. Using a combination of sequence comparison and tree-based phylogenetic methods, we evaluated this dataset for erroneous or otherwise problematic sequences and examined the utility of each molecular marker for the delineation of species. Although we find the rate of obviously erroneous sequences to be low, all four molecular markers failed to differentiate between at least one species pair. Our results suggest that while a combination of multiple markers is best for species identification, the coxI marker shows the most utility for species differentiation and should be favored over 18S, ITS, and 28S, where resources are limited. Presently, less than half the valid species of Heterodera have a sequence of coxI available, and only a third have more than one sequence of this marker.

Curation of a reference database of COI sequences for insect identification through DNA metabarcoding: COins

DNA metabarcoding is a widespread approach for the molecular identification of organisms. While the associated wet-lab and data processing procedures are well established and highly efficient, the reference databases for taxonomic assignment can be implemented to improve the accuracy of identifications. Insects are among the organisms for which DNA-based identification is most commonly used; yet, a DNA-metabarcoding reference database specifically curated for their species identification using software requiring local databases is lacking. Here, we present COins, a database of 5' region cytochrome c oxidase subunit I sequences (COI-5P) of insects that includes over 532 000 representative sequences of >106 000 species specifically formatted for the QIIME2 software platform. Through a combination of automated and manually curated steps, we developed this database starting from all COI sequences available in the Barcode of Life Data System for insects, focusing on sequences that comply with several standards, including a species-level identification. COins was validated on previously published DNA-metabarcoding sequences data (bulk samples from Malaise traps) and its efficiency compared with other publicly available reference databases (not specific for insects). COins can allow an increase of up to 30% of species-level identifications and thus can represent a valuable resource for the taxonomic assignment of insects' DNA-metabarcoding data, especially when species-level identification is needed https://doi.org/10.6084/m9.figshare.19130465.v1.

DNA barcodes reveal striking arthropod diversity and unveil seasonal patterns of variation in the southern Atlantic Forest

The Atlantic Forest harbors 7% of global biodiversity and possesses high levels of endemism, but many of its component taxa remain unstudied. Due to the importance of tropical forests and the urgency to protect them, there is a compelling need to address this knowledge gap. To provide more information on its arthropod fauna, a Malaise trap was deployed for 12 months in a semi-degraded area of the southern Upper Paraná ecoregion of the Atlantic Forest. All specimens were DNA barcoded and the Barcode Index Number (BIN) system was employed to assign each specimen to a species proxy. DNA barcodes were obtained from 75,500 arthropods that included representatives of 8,651 BINs. Nearly 81% of these BINs were first records, highlighting the high rates of endemism and lack of study of arthropods from the Atlantic Forest. Diptera was the most abundant order, followed by Hemiptera, Lepidoptera and Hymenoptera. Diptera was also the most species-rich order, followed by Hymenoptera, Lepidoptera, and Coleoptera, a result consistent with studies in other biogeographic regions. Insects were most abundant in winter and most diverse in autumn and winter. This pattern, however, was caused mainly by the dynamics of dipteran diversity as other orders differed in their seasonal variation. The BIN composition of the insect community varied sharply through the year and also differed between the two consecutive summers included in the sampling period. The study of the 38 commonest BINs showed that seasonal patterns of abundance were not order-specific. Temperature had the strongest impact on seasonal abundance variation. Our results highlight the striking and understudied arthropod diversity of the highly fragmented Atlantic Forest, the predominance of dipterans, and the fact that abundance and richness in this insect community peak in the coolest months. Standardized studies like this generate fast and reliable biodiversity inventories and unveil ecological patterns, thus providing valuable information for conservation programs.

A novel approach for reliable qualitative and quantitative prey spectra identification of carnivorous plants combining DNA metabarcoding and macro photography

Prey spectra (the number and composition of captured arthropods) represent a crucial aspect of carnivorous plant ecology, yet remain poorly studied. Traditional morphology-based approaches for prey identification are time-intensive, require specialists with considerable knowledge of arthropod taxonomy, and are hampered by high numbers of unidentifiable (i.e., heavily digested) prey items. We examined prey spectra of three species of closely-related annual Drosera (Droseraceae, sundews) from tropical northern Australia using a novel DNA metabarcoding approach with in-situ macro photography as a plausibility control and to facilitate prey quantity estimations. This new method facilitated accurate analyses of carnivorous plant prey spectra (even of heavily digested prey lacking characteristic morphological features) at a taxonomic resolution and level of completeness far exceeding morphology-based methods and approaching the 100% mark at arthropod order level. Although the three studied species exhibited significant differences in detected prey spectra, little prey specialisation was observed and habitat or plant population density variations were likely the main drivers of prey spectra dissimilarity.

Harmonizing Forest Conservation Policies with Essential Biodiversity Variables Incorporating Remote Sensing and Environmental DNA Technologies

It remains difficult to compare the state of conservation of forests of different nations. Essential Biodiversity Variables (EBVs) are a set of variables designed as a framework for harmonizing biodiversity monitoring. Methods to monitor forest biodiversity are traditional monitoring (according to conservation policy requirements), remote sensing, environmental DNA, and the information products that are derived from them (RS/eDNA biodiversity products). However, it is not clear to what extent indicators from conservation policies align with EBVs and RS/eDNA biodiversity products. This research evaluated current gaps in harmonization between EBVs, RS/eDNA biodiversity products and forest conservation indicators. We compared two sets of biodiversity variables: (1) forest conservation indicators and (2) RS/eDNA biodiversity products, within the context of the Essential Biodiversity Variables framework. Indicators derived from policy documents can mostly be categorized within the EBV ‘ecosystem vertical profile’, while ‘ecosystem function’ remains underrepresented. RS/eDNA biodiversity products, however, can provide information about ‘ecosystem function’. Integrating RS/eDNA biodiversity products that monitor ecosystem functioning into monitoring programs will lead to a more comprehensive and balanced reporting on forest biodiversity. In addition, using the same variables and similar RS/eDNA products for forest biodiversity and conservation policies is a requirement for harmonization and international policy reporting.

DNA Metabarcoding Enables High-Throughput Detection of Spotted Wing Drosophila (Drosophila suzukii) Within Unsorted Trap Catches

The spotted wing drosophila (Drosophila suzukii, Matsumara) is a rapidly spreading global pest of soft and stone fruit production. Due to the similarity of many of its life stages to other cosmopolitan drosophilids, surveillance for this pest is currently bottlenecked by the laborious sorting and morphological identification of large mixed trap catches. DNA metabarcoding presents an alternative high-throughput sequencing (HTS) approach for multi-species identification, which may lend itself ideally to rapid and scalable diagnostics of D. suzukii within unsorted trap samples. In this study, we compared the qualitative (identification accuracy) and quantitative (bias toward each species) performance of four metabarcoding primer pairs on D. suzukii and its close relatives. We then determined the sensitivity of a non-destructive metabarcoding assay (i.e., which retains intact specimens) by spiking whole specimens of target species into mock communities of increasing specimen number, as well as 29 field-sampled communities from a cherry and a stone fruit orchard. Metabarcoding successfully detected D. suzukii and its close relatives Drosophila subpulchrella and Drosophila biarmipes in the spiked communities with an accuracy of 96, 100, and 100% respectively, and identified a further 57 non-target arthropods collected as bycatch by D. suzukii surveillance methods in a field scenario. While the non-destructive DNA extraction retained intact voucher specimens, dropouts of single species and entire technical replicates suggests that these protocols behave more similarly to environmental DNA than homogenized tissue metabarcoding and may require increased technical replication to reliably detect low-abundance taxa. Adoption of high-throughput metabarcoding assays for screening bulk trap samples could enable a substantial increase in the geographic scale and intensity of D. suzukii surveillance, and thus likelihood of detecting a new introduction. Trap designs and surveillance protocols will, however, need to be optimized to adequately preserve specimen DNA for molecular identification.

Arthropod dark taxa provide new insights into diversity responses to bark beetle infestations

Natural disturbances are increasing around the globe, also impacting protected areas. Although previous studies have indicated that natural disturbances result in mainly positive effects on biodiversity, these analyses mostly focused on a few well established taxonomic groups, and thus uncertainty remains regarding the comprehensive impact of natural disturbances on biodiversity. Using Malaise traps and meta-barcoding, we studied a broad range of arthropod taxa, including dark and cryptic taxa, along a gradient of bark beetle disturbance severities in five European national parks. We identified order-level community thresholds of disturbance severity and classified barcode index numbers (BINs; a cluster system for DNA sequences, where each cluster corresponds to a species) as negative or positive disturbance indicators. Negative indicator BINs decreased above thresholds of low to medium disturbance severity (20%-30% of trees killed), whereas positive indicator BINs benefited from high disturbance severity (76%-98%). BINs allocated to a species name contained nearly as many positive as negative disturbance indicators, but dark and cryptic taxa, particularly Diptera and Hymenoptera in our data, contained higher numbers of negative disturbance indicator BINs. Analyses of changes in the richness of BINs showed variable responses of arthropods to disturbance severity at lower taxonomic levels, whereas no significant signal was detected at the order level due to the compensatory responses of the underlying taxa. We conclude that the analyses of dark taxa can offer new insights into biodiversity responses to disturbances. Our results suggest considerable potential for forest management to foster arthropod diversity, for example by maintaining both closed-canopy forests (>70% cover) and open forests (<30% cover) on the landscape.

eDNA biomonitoring revealed the ecological effects of water diversion projects between Yangtze River and Tai Lake

Water diversion has been widely used to address water shortages and security issues. However, its long-term ecological impacts, particularly on the biodiversity and structure of the local community, have often been neglected due to limitations of conventional biomonitoring. Taking the water diversion projects from Yangtze River to Tai Lake (WDYT) as examples, environmental DNA (eDNA) metabarcoding was used to investigate the potential ecological impact of water diversion on the connected basins. Firstly, 136 phytoplankton genera/species, including 31 cyanobacteria and 105 eukaryotic phytoplankton (Euk-phytoplankton), were identified from 26 sites by metabarcoding of 16S rDNA V3 and 18S rDNA V9 regions. eDNA metabarcoding showed an obvious advantage in detecting nano/pico-plankton (< 20 μm in size) compared with the morphological approach. Secondly, more shared taxa and higher similarity of community composition were observed in Gonghu Bay/Zhushan Bay with its connected river than with the center of Tai Lake, indicating that water diversions were accelerating the biotic homogenization between different waterbodies. Skeletonema potamos, the native species of Yangtze River (4.04% of the total Euk-phytoplankton reads) was detected in different connecting regions of Tai Lake (0.03%-0.54% of the total Euk-phytoplankton reads), where its relative abundance was consistent with the influence of water diversion from Yangtze River. Furthermore, the introduction of S. potamos significantly affected the local community compositions of phytoplankton in Tai Lake. Finally, the ecological effect (e.g., taxa richness, community composition and species invasion) of the WDYT on phytoplankton in the west of Tai Lake was more significant than that in the east, which was consistent with the scale (volume and duration) of the water diversion projects. Overall, this study highlights the value of eDNA biomonitoring in the ecological impact assessment of water transfer projects.

Surprisingly high genetic divergence of the mitochondrial DNA barcode fragment (COI) within Central European woodlice species (Crustacea, Isopoda, Oniscidea)

DNA barcoding has become the most popular approach for species identification in recent years. As part of the German Barcode of Life project, the first DNA barcode library for terrestrial and freshwater isopods from Germany is presented. The analyzed barcode library included 38 terrestrial (78% of the documented species of Germany) and five freshwater (63%) species. A total of 513 new barcodes was generated and 518 DNA barcodes were analyzed. This analysis revealed surprisingly high intraspecific genetic distances for numerous species, with a maximum of 29.4% for Platyarthrus hoffmannseggii Brandt, 1833. The number of BINs per species ranged from one (32 species, 68%) to a maximum of six for Trachelipus rathkii (Brandt, 1833). In spite of such high intraspecific variability, interspecific distances with values between 12.6% and 29.8% allowed a valid species assignment of all analyzed isopods. The observed high intraspecific distances presumably result from phylogeographic events, Wolbachia infections, atypical mitochondrial DNAs, heteroplasmy, or various combinations of these factors. Our study represents the first step in generating an extensive reference library of DNA barcodes for terrestrial and freshwater isopods for future molecular biodiversity assessment studies.

Pooling size sorted Malaise trap fractions to maximize taxon recovery with metabarcoding

Background

Small and rare specimens can remain undetected when metabarcoding is applied on bulk samples with a high specimen size heterogeneity. This is especially critical for Malaise trap samples, where most of the biodiversity is contributed by small taxa with low biomass. The separation of samples in different size fractions for downstream analysis is one possibility to increase detection of small and rare taxa. However, experiments systematically testing different size sorting approaches and subsequent proportional pooling of fractions are lacking, but would provide important information for the optimization of metabarcoding protocols. We set out to find a size sorting strategy for Malaise trap samples that maximizes taxonomic recovery but remains scalable and time efficient.

Methods

Three Malaise trap samples were sorted into four size classes using dry sieving. Each fraction was homogenized and lysed. The corresponding lysates were pooled to simulate unsorted samples. Pooling was additionally conducted in equal proportions and in four different proportions enriching the small size fraction of samples. DNA from the individual size classes as well as the pooled fractions was extracted and metabarcoded using the FwhF2 and Fol-degen-rev primer set. Additionally, alternative wet sieving strategies were explored.

Results

The small size fractions harboured the highest diversity and were best represented when pooling in favour of small specimens. Metabarcoding of unsorted samples decreases taxon recovery compared to size sorted samples. A size separation into only two fractions (below 4 mm and above) can double taxon recovery compared to not size sorting. However, increasing the sequencing depth 3- to 4-fold can also increase taxon recovery to levels comparable with size sorting, but remains biased towards biomass rich taxa in the sample.

Conclusion

We demonstrate that size fractionation of Malaise trap bulk samples can increase taxon recovery. While results show distinct patterns, the lack of statistical support due to the limited number of samples processed is a limitation. Due to increased speed and lower risk of cross-contamination as well as specimen damage we recommend wet sieving and proportional pooling of the lysates in favour of the small size fraction (80–90% volume). However, for large-scale projects with time constraints, increasing sequencing depth is an alternative solution.

DNA barcoding of phytopathogens for disease diagnostics and bio-surveillance

DNA barcoding has proven to be a versatile tool for plant disease diagnostics in the genomics era. As the mass parallel and next generation sequencing techniques gained importance, the role of specific barcodes came under immense scrutiny. Identification and accurate classification of phytopathogens need a universal approach which has been the main application area of the concept of barcode. The present review entails a detailed description of the present status of barcode application in plant disease diagnostics. A case study on the application of Internal Transcribed Spacer (ITS) as barcode for Aspergillus and Fusarium spp. sheds light on the requirement of other potential candidates as barcodes for accurate identification. The challenges faced while barcoding novel pathogens have also been discussed with a comprehensive outline of integrating more recent technologies like meta-barcoding and genome skimming for detecting plant pathogens.