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O'Rourke DR, Mangan MT, Mangan KE, Bokulich NA, MacManes MD, Foster JT. Lord of the Diptera (and Moths and a Spider): Molecular Diet Analyses and Foraging Ecology of Indiana Bats in Illinois. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.623655] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Effective management of endangered or threatened wildlife requires an understanding of how foraging habitats are used by those populations. Molecular diet analysis of fecal samples offers a cost-effective and non-invasive method to investigate how diets of wild populations vary with respect to spatial and temporal factors. For the federally endangered Indiana bat (Myotis sodalis), documenting its preferred food sources can provide critical information to promote effective conservation of this federally endangered species. Using cytochrome oxidase I amplicon sequence data from Indiana bat guano samples collected at two roosting areas in Cypress Creek National Wildlife Refuge, we found that dipteran taxa (i.e., flies) associated with riparian habitats were the most frequently detected taxon and represented the majority of the sequence diversity among the arthropods sampled. A select few arthropods from other taxa—especially spiders—are also likely important to Indiana bat diets in this refuge. A supervised learning analysis of diet components suggest only a small fraction of the frequently detected taxa are important contributors to spatial and temporal variation. Overall, these data depict the Indiana bat as a generalist consumer whose diet includes some prey items associated with particular seasonal or spatial components, along with other taxa repeatedly consumed throughout the entire foraging season. These molecular diet analyses suggest that protecting foraging resources specifically associated with the riparian habitat of Cypress Creek National Wildlife Refuge is essential to promote effective Indiana bat conservation.
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Integration of DNA-Based Approaches in Aquatic Ecological Assessment Using Benthic Macroinvertebrates. WATER 2021. [DOI: 10.3390/w13030331] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Benthic macroinvertebrates are among the most used biological quality elements for assessing the condition of all types of aquatic ecosystems worldwide (i.e., fresh water, transitional, and marine). Current morphology-based assessments have several limitations that may be circumvented by using DNA-based approaches. Here, we present a comprehensive review of 90 publications on the use of DNA metabarcoding of benthic macroinvertebrates in aquatic ecosystems bioassessments. Metabarcoding of bulk macrozoobenthos has been preferentially used in fresh waters, whereas in marine waters, environmental DNA (eDNA) from sediment and bulk communities from deployed artificial structures has been favored. DNA extraction has been done predominantly through commercial kits, and cytochrome c oxidase subunit I (COI) has been, by far, the most used marker, occasionally combined with others, namely, the 18S rRNA gene. Current limitations include the lack of standardized protocols and broad-coverage primers, the incompleteness of reference libraries, and the inability to reliably extrapolate abundance data. In addition, morphology versus DNA benchmarking of ecological status and biotic indexes are required to allow general worldwide implementation and higher end-user confidence. The increased sensitivity, high throughput, and faster execution of DNA metabarcoding can provide much higher spatial and temporal data resolution on aquatic ecological status, thereby being more responsive to immediate management needs.
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53
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Nugent CM, Adamowicz SJ. Alignment-free classification of COI DNA barcode data with the Python package Alfie. METABARCODING AND METAGENOMICS 2020. [DOI: 10.3897/mbmg.4.55815] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Characterization of biodiversity from environmental DNA samples and bulk metabarcoding data is hampered by off-target sequences that can confound conclusions about a taxonomic group of interest. Existing methods for isolation of target sequences rely on alignment to existing reference barcodes, but this can bias results against novel genetic variants. Effectively parsing targeted DNA barcode data from off-target noise improves the quality of biodiversity estimates and biological conclusions by limiting subsequent analyses to a relevant subset of available data. Here, we present Alfie, a Python package for the alignment-free classification of cytochrome c oxidase subunit I (COI) DNA barcode sequences to taxonomic kingdoms. The package determines k-mer frequencies of DNA sequences, and the frequencies serve as input for a neural network classifier that was trained and tested using ~58,000 publicly available COI sequences. The classifier was designed and optimized through a series of tests that allowed for the optimal set of DNA k-mer features and optimal machine learning algorithm to be selected. The neural network classifier rapidly assigns COI sequences of varying lengths to kingdoms with greater than 99% accuracy and is shown to generalize effectively and make accurate predictions about data from previously unseen taxonomic classes. The package contains an application programming interface that allows the Alfie package’s functionality to be extended to different DNA sequence classification tasks to suit a user’s need, including classification of different genes and barcodes, and classification to different taxonomic levels. Alfie is free and publicly available through GitHub (https://github.com/CNuge/alfie) and the Python package index (https://pypi.org/project/alfie/).
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Hao M, Jin Q, Meng G, Yang C, Yang S, Shi Z, Tang M, Liu S, Li Y, Li J, Zhang D, Su X, Shih C, Sun Y, Wilson JJ, Zhou X, Zhang A. Using full-length metabarcoding and DNA barcoding to infer community assembly for speciose taxonomic groups: a case study. Evol Ecol 2020. [DOI: 10.1007/s10682-020-10072-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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O'Rourke DR, Bokulich NA, Jusino MA, MacManes MD, Foster JT. A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses. Ecol Evol 2020; 10:9721-9739. [PMID: 33005342 PMCID: PMC7520210 DOI: 10.1002/ece3.6594] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 06/29/2020] [Accepted: 07/01/2020] [Indexed: 01/01/2023] Open
Abstract
Metabarcoding studies provide a powerful approach to estimate the diversity and abundance of organisms in mixed communities in nature. While strategies exist for optimizing sample and sequence library preparation, best practices for bioinformatic processing of amplicon sequence data are lacking in animal diet studies. Here we evaluate how decisions made in core bioinformatic processes, including sequence filtering, database design, and classification, can influence animal metabarcoding results. We show that denoising methods have lower error rates compared to traditional clustering methods, although these differences are largely mitigated by removing low-abundance sequence variants. We also found that available reference datasets from GenBank and BOLD for the animal marker gene cytochrome oxidase I (COI) can be complementary, and we discuss methods to improve existing databases to include versioned releases. Taxonomic classification methods can dramatically affect results. For example, the commonly used Barcode of Life Database (BOLD) Classification API assigned fewer names to samples from order through species levels using both a mock community and bat guano samples compared to all other classifiers (vsearch-SINTAX and q2-feature-classifier's BLAST + LCA, VSEARCH + LCA, and Naive Bayes classifiers). The lack of consensus on bioinformatics best practices limits comparisons among studies and may introduce biases. Our work suggests that biological mock communities offer a useful standard to evaluate the myriad computational decisions impacting animal metabarcoding accuracy. Further, these comparisons highlight the need for continual evaluations as new tools are adopted to ensure that the inferences drawn reflect meaningful biology instead of digital artifacts.
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Affiliation(s)
- Devon R. O'Rourke
- Department of Molecular, Cellular, and Biomedical SciencesUniversity of New HampshireDurhamNHUSA
- Pathogen and Microbiome InstituteNorthern Arizona UniversityFlagstaffAZUSA
| | - Nicholas A. Bokulich
- Laboratory of Food Systems BiotechnologyInstitute of Food, Nutrition, and HealthETH ZurichZurichSwitzerland
| | - Michelle A. Jusino
- Biology DepartmentWilliam & MaryWilliamsburgVAUSA
- Center for Forest Mycology ResearchUSDA Forest ServiceNorthern Research StationMadisonUSA
| | - Matthew D. MacManes
- Department of Molecular, Cellular, and Biomedical SciencesUniversity of New HampshireDurhamNHUSA
| | - Jeffrey T. Foster
- Department of Molecular, Cellular, and Biomedical SciencesUniversity of New HampshireDurhamNHUSA
- Pathogen and Microbiome InstituteNorthern Arizona UniversityFlagstaffAZUSA
- Department of Biological SciencesNorthern Arizona UniversityFlagstaffAZUSA
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56
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Porter TM, Hajibabaei M. Putting COI Metabarcoding in Context: The Utility of Exact Sequence Variants (ESVs) in Biodiversity Analysis. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00248] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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57
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Tournayre O, Leuchtmann M, Filippi‐Codaccioni O, Trillat M, Piry S, Pontier D, Charbonnel N, Galan M. In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses. Ecol Evol 2020; 10:6310-6332. [PMID: 32724515 PMCID: PMC7381572 DOI: 10.1002/ece3.6362] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/20/2020] [Accepted: 04/22/2020] [Indexed: 12/28/2022] Open
Abstract
During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo-mock community (33 arthropod taxa from 16 orders), and guano-based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano-based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one-third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.
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Affiliation(s)
- Orianne Tournayre
- CBGPINRAECIRADIRDMontpellier SupAgroUniversité de MontpellierMontpellierFrance
| | | | - Ondine Filippi‐Codaccioni
- LabEx ECOFECT “Ecoevolutionary Dynamics of Infectious DiseasesUniversité de LyonLyonFrance
- CNRSLaboratoire de Biométrie et Biologie ÉvolutiveUMR5558Université de LyonUniversité Lyon 1VilleurbanneFrance
| | - Marine Trillat
- CBGPINRAECIRADIRDMontpellier SupAgroUniversité de MontpellierMontpellierFrance
| | - Sylvain Piry
- CBGPINRAECIRADIRDMontpellier SupAgroUniversité de MontpellierMontpellierFrance
| | - Dominique Pontier
- LabEx ECOFECT “Ecoevolutionary Dynamics of Infectious DiseasesUniversité de LyonLyonFrance
- CNRSLaboratoire de Biométrie et Biologie ÉvolutiveUMR5558Université de LyonUniversité Lyon 1VilleurbanneFrance
| | - Nathalie Charbonnel
- CBGPINRAECIRADIRDMontpellier SupAgroUniversité de MontpellierMontpellierFrance
| | - Maxime Galan
- CBGPINRAECIRADIRDMontpellier SupAgroUniversité de MontpellierMontpellierFrance
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58
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Yang CQ, Lv Q, Zhang AB. Sixteen Years of DNA Barcoding in China: What Has Been Done? What Can Be Done? Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00057] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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59
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DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness. Proc Natl Acad Sci U S A 2020; 117:8539-8545. [PMID: 32217735 PMCID: PMC7165428 DOI: 10.1073/pnas.1918741117] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large scales. The Peace-Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification and DNA metabarcoding. By using multispecies occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera and quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were nearly random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.
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60
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Phillips JD, French SH, Hanner RH, Gillis DJ. HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves. PeerJ Comput Sci 2020; 6:e243. [PMID: 33816897 PMCID: PMC7924493 DOI: 10.7717/peerj-cs.243] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 11/07/2019] [Indexed: 05/25/2023]
Abstract
Assessing levels of standing genetic variation within species requires a robust sampling for the purpose of accurate specimen identification using molecular techniques such as DNA barcoding; however, statistical estimators for what constitutes a robust sample are currently lacking. Moreover, such estimates are needed because most species are currently represented by only one or a few sequences in existing databases, which can safely be assumed to be undersampled. Unfortunately, sample sizes of 5-10 specimens per species typically seen in DNA barcoding studies are often insufficient to adequately capture within-species genetic diversity. Here, we introduce a novel iterative extrapolation simulation algorithm of haplotype accumulation curves, called HACSim (Haplotype Accumulation Curve Simulator) that can be employed to calculate likely sample sizes needed to observe the full range of DNA barcode haplotype variation that exists for a species. Using uniform haplotype and non-uniform haplotype frequency distributions, the notion of sampling sufficiency (the sample size at which sampling accuracy is maximized and above which no new sampling information is likely to be gained) can be gleaned. HACSim can be employed in two primary ways to estimate specimen sample sizes: (1) to simulate haplotype sampling in hypothetical species, and (2) to simulate haplotype sampling in real species mined from public reference sequence databases like the Barcode of Life Data Systems (BOLD) or GenBank for any genomic marker of interest. While our algorithm is globally convergent, runtime is heavily dependent on initial sample sizes and skewness of the corresponding haplotype frequency distribution.
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Affiliation(s)
| | - Steven H. French
- School of Computer Science, University of Guelph, Guelph, Ontario, Canada
| | - Robert H. Hanner
- Department of Integrative Biology, Biodiversity Institute of Ontario, University of Guelph, Guelph, Ontario, Canada
| | - Daniel J. Gillis
- School of Computer Science, University of Guelph, Guelph, Ontario, Canada
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61
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deWaard JR, Ratnasingham S, Zakharov EV, Borisenko AV, Steinke D, Telfer AC, Perez KHJ, Sones JE, Young MR, Levesque-Beaudin V, Sobel CN, Abrahamyan A, Bessonov K, Blagoev G, deWaard SL, Ho C, Ivanova NV, Layton KKS, Lu L, Manjunath R, McKeown JTA, Milton MA, Miskie R, Monkhouse N, Naik S, Nikolova N, Pentinsaari M, Prosser SWJ, Radulovici AE, Steinke C, Warne CP, Hebert PDN. A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples. Sci Data 2019; 6:308. [PMID: 31811161 PMCID: PMC6897906 DOI: 10.1038/s41597-019-0320-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 11/11/2019] [Indexed: 01/08/2023] Open
Abstract
The reliable taxonomic identification of organisms through DNA sequence data requires a well parameterized library of curated reference sequences. However, it is estimated that just 15% of described animal species are represented in public sequence repositories. To begin to address this deficiency, we provide DNA barcodes for 1,500,003 animal specimens collected from 23 terrestrial and aquatic ecozones at sites across Canada, a nation that comprises 7% of the planet's land surface. In total, 14 phyla, 43 classes, 163 orders, 1123 families, 6186 genera, and 64,264 Barcode Index Numbers (BINs; a proxy for species) are represented. Species-level taxonomy was available for 38% of the specimens, but higher proportions were assigned to a genus (69.5%) and a family (99.9%). Voucher specimens and DNA extracts are archived at the Centre for Biodiversity Genomics where they are available for further research. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, and the Global Genome Biodiversity Network Data Portal.
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Affiliation(s)
- Jeremy R deWaard
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | | | - Evgeny V Zakharov
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Alex V Borisenko
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Dirk Steinke
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Angela C Telfer
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Kate H J Perez
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Jayme E Sones
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Monica R Young
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | | | - Crystal N Sobel
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Arusyak Abrahamyan
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Kyrylo Bessonov
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
- Public Health Agency of Canada, Guelph, Ontario, Canada
| | - Gergin Blagoev
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Stephanie L deWaard
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Chris Ho
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Natalia V Ivanova
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Kara K S Layton
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
- Ocean Frontier Institute, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Liuqiong Lu
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Ramya Manjunath
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Jaclyn T A McKeown
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Megan A Milton
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Renee Miskie
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Norm Monkhouse
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Suresh Naik
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Nadya Nikolova
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Mikko Pentinsaari
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Sean W J Prosser
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | | | - Claudia Steinke
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Connor P Warne
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Paul D N Hebert
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada.
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62
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Elbrecht V, Braukmann TW, Ivanova NV, Prosser SW, Hajibabaei M, Wright M, Zakharov EV, Hebert PD, Steinke D. Validation of COI metabarcoding primers for terrestrial arthropods. PeerJ 2019; 7:e7745. [PMID: 31608170 PMCID: PMC6786254 DOI: 10.7717/peerj.7745] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 08/25/2019] [Indexed: 01/08/2023] Open
Abstract
Metabarcoding can rapidly determine the species composition of bulk samples and thus aids biodiversity and ecosystem assessment. However, it is essential to use primer sets that minimize amplification bias among taxa to maximize species recovery. Despite this fact, the performance of primer sets employed for metabarcoding terrestrial arthropods has not been sufficiently evaluated. This study tests the performance of 36 primer sets on a mock community containing 374 insect species. Amplification success was assessed with gradient PCRs and the 21 most promising primer sets selected for metabarcoding. These 21 primer sets were also tested by metabarcoding a Malaise trap sample. We identified eight primer sets, mainly those including inosine and/or high degeneracy, that recovered more than 95% of the species in the mock community. Results from the Malaise trap sample were congruent with the mock community, but primer sets generating short amplicons produced potential false positives. Taxon recovery from both mock community and Malaise trap sample metabarcoding were used to select four primer sets for additional evaluation at different annealing temperatures (40-60 °C) using the mock community. The effect of temperature varied by primer pair but overall it only had a minor effect on taxon recovery. This study reveals the weak performance of some primer sets employed in past studies. It also demonstrates that certain primer sets can recover most taxa in a diverse species assemblage. Thus, based our experimental set up, there is no need to employ several primer sets targeting the same gene region. We identify several suitable primer sets for arthropod metabarcoding, and specifically recommend BF3 + BR2, as it is not affected by primer slippage and provides maximal taxonomic resolution. The fwhF2 + fwhR2n primer set amplifies a shorter fragment and is therefore ideal when targeting degraded DNA (e.g., from gut contents).
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Affiliation(s)
- Vasco Elbrecht
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | | | - Natalia V. Ivanova
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
- Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
| | - Sean W.J. Prosser
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
| | - Mehrdad Hajibabaei
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
- Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
| | - Michael Wright
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
- Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
| | - Evgeny V. Zakharov
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
- Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
| | - Paul D.N. Hebert
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
- Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
| | - Dirk Steinke
- Centre for Biodiversity Genomics, University of Guelph, Guelph, ON, Canada
- Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
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63
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Kelly RP, Shelton AO, Gallego R. Understanding PCR Processes to Draw Meaningful Conclusions from Environmental DNA Studies. Sci Rep 2019; 9:12133. [PMID: 31431641 PMCID: PMC6702206 DOI: 10.1038/s41598-019-48546-x] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 08/05/2019] [Indexed: 11/08/2022] Open
Abstract
As environmental DNA (eDNA) studies have grown in popularity for use in ecological applications, it has become clear that their results differ in significant ways from those of traditional, non-PCR-based surveys. In general, eDNA studies that rely on amplicon sequencing may detect hundreds of species present in a sampled environment, but the resulting species composition can be idiosyncratic, reflecting species' true biomass abundances poorly or not at all. Here, we use a set of simulations to develop a mechanistic understanding of the processes leading to the kinds of results common in mixed-template PCR-based (metabarcoding) studies. In particular, we focus on the effects of PCR cycle number and primer amplification efficiency on the results of diversity metrics in sequencing studies. We then show that proportional indices of amplicon reads capture trends in taxon biomass with high accuracy, particularly where amplification efficiency is high (median correlation up to 0.97). Our results explain much of the observed behavior of PCR-based studies, and lead to recommendations for best practices in the field.
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Affiliation(s)
- Ryan P Kelly
- University of Washington, School of Marine and Environmental Affairs, Seattle, Washington, USA.
| | - Andrew Olaf Shelton
- Northwest Fisheries Science Center, NOAA Fisheries, Seattle, Washington, USA
| | - Ramón Gallego
- University of Washington, School of Marine and Environmental Affairs, Seattle, Washington, USA
- Northwest Fisheries Science Center, NOAA Fisheries, Seattle, Washington, USA
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64
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Piper AM, Batovska J, Cogan NOI, Weiss J, Cunningham JP, Rodoni BC, Blacket MJ. Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance. Gigascience 2019; 8:giz092. [PMID: 31363753 PMCID: PMC6667344 DOI: 10.1093/gigascience/giz092] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 06/25/2019] [Accepted: 07/09/2019] [Indexed: 12/21/2022] Open
Abstract
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.
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Affiliation(s)
- Alexander M Piper
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora 3083, VIC, Australia
| | - Jana Batovska
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora 3083, VIC, Australia
| | - Noel O I Cogan
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora 3083, VIC, Australia
| | - John Weiss
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
| | - John Paul Cunningham
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
| | - Brendan C Rodoni
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora 3083, VIC, Australia
| | - Mark J Blacket
- Agriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora 3083, VIC, Australia
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65
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Braukmann TWA, Ivanova NV, Prosser SWJ, Elbrecht V, Steinke D, Ratnasingham S, de Waard JR, Sones JE, Zakharov EV, Hebert PDN. Metabarcoding a diverse arthropod mock community. Mol Ecol Resour 2019; 19:711-727. [PMID: 30779309 PMCID: PMC6850013 DOI: 10.1111/1755-0998.13008] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 02/13/2019] [Indexed: 12/31/2022]
Abstract
Although DNA metabarcoding is an attractive approach for monitoring biodiversity, it is often difficult to detect all the species present in a bulk sample. In particular, sequence recovery for a given species depends on its biomass and mitome copy number as well as the primer set employed for PCR. To examine these variables, we constructed a mock community of terrestrial arthropods comprised of 374 species. We used this community to examine how species recovery was impacted when amplicon pools were constructed in four ways. The first two protocols involved the construction of bulk DNA extracts from different body segments (Bulk Abdomen, Bulk Leg). The other protocols involved the production of DNA extracts from single legs which were then merged prior to PCR (Composite Leg) or PCR‐amplified separately (Single Leg) and then pooled. The amplicons generated by these four treatments were then sequenced on three platforms (Illumina MiSeq, Ion Torrent PGM and Ion Torrent S5). The choice of sequencing platform did not substantially influence species recovery, although the Miseq delivered the highest sequence quality. As expected, species recovery was most efficient from the Single Leg treatment because amplicon abundance varied little among taxa. Among the three treatments where PCR occurred after pooling, the Bulk Abdomen treatment produced a more uniform read abundance than the Bulk Leg or Composite Leg treatment. Primer choice also influenced species recovery and evenness. Our results reveal how variation in protocols can have substantial impacts on perceived diversity unless sequencing coverage is sufficient to reach an asymptote.
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Affiliation(s)
| | - Natalia V Ivanova
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Sean W J Prosser
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Vasco Elbrecht
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Dirk Steinke
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada.,Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
| | | | - Jeremy R de Waard
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada.,School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Jayme E Sones
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Evgeny V Zakharov
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Paul D N Hebert
- Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada.,Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
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