Biology subjects

Hebert, P. D. N.

Publications and source records attributed to Hebert, P. D. N..

At least 19 recordsLinked to original sources

bioRxiv2026

The Barcode Inference Pipeline (BIP): From Sequencer Output to DNA Barcodes

DNA barcoding involves the recovery of a DNA sequence for a target gene region from its source specimen. This process gains complexity when multiple sequences are recovered from a specimen, as is often the case when data are generated by high-throughput sequencers. This diversity can reflect both methodological artifacts (e.g., chimeras, PCR errors, sequencing errors, tag jumps) and real template diversity in the DNA extract (e.g., contamination, endosymbionts, NUMTs, parasites). To support analysis of the sequence data from three million specimens annually, the Centre for Biodiversity Genomics (CBG) has developed BIP, the Barcode Inference Pipeline. Compatible with all sequencing platforms, BIP processes .fastq files and returns both target DNA barcodes and non-target sequences. To generate results, BIP implements quality and size filtration, demultiplexing, primer trimming, chimera scanning, sequence error correction, OTU delineation, and sequence identification. When analysis targets the cytochrome c oxidase 1 (COI) barcode region, BIP also assigns each OTU to a known BIN or identifies its nearest neighbour BIN. As final output, BIP returns summary files ready for upload to BOLD or for other downstream analyses. They include a taxonomic assignment for each OTU, generated by comparison with a DNA barcode reference library. We describe BIPs flexibility and structure, then demonstrate its functionality by analyzing COI sequence data from 100K specimens. Because of its capacity to disentangle target and non-target sequences, BIP outperforms an alternative software package, ONTbarcoder, in several important ways. To ease access, installation, and functionality, BIP is provided as a Docker container (github.com/cbg-innov/BIP).

bioinformatics↗

bioRxiv2026

The Metabarcoding Analysis Pipeline (MAP): Simple, accurate, and flexible metabarcoding

Current metabarcoding pipelines are inflexible with respect to study design and are poorly suited to long-read sequence data. To address these limitations, we developed MAP, the Metabarcoding Analysis Pipeline, which is a sequence-to-answer workflow supporting the analysis of amplicons from highly multiplexed and replicated study designs. Although MAP can analyze amplicons of any length from any genetic marker, it includes several features tailored to long-read COI metabarcoding. MAP installs from a Docker container and requires only sequence data, a parameters file, and a reference library. It produces intuitive reports, enabling users to evaluate their data immediately after analysis. We validate MAP by showing that it generates biodiversity estimates that correspond closely to a ground-truth dataset of single-specimen DNA barcode data and by demonstrating that it outperforms alternative platforms for COI metabarcoding. MAP is free, open-source, and available from: https://github.com/cbg-innov/MAP.

bioinformatics↗

bioRxiv2026

Predicting global biodiversity via Hubbell regression

Understanding global biodiversity patterns and their drivers is a prerequisite for countering the biodiversity crisis. In this paper, we introduce a novel generalized linear model, Hubbell regression, to estimate a key biodiversity descriptor, the fundamental biodiversity number. This can be converted into a set of biodiversity descriptors, including Shannon and Simpson indices, and more. Hence, quantifying the impact of environmental conditions on the fundamental biodiversity number allows us to predict the general properties of local biodiversity in any setting. In addition to having a strong mathematical foundation, Hubbell regression consistently outperformed current state-of-the-art models in predicting global biodiversity. We apply the method to arthropods, which account for the majority of terrestrial biodiversity. By parameterizing the models using samples of 1.78 million arthropods from 2415 samples collected at 135 sites spanning all continents, we pinpoint the drivers of arthropod biodiversity and its features at the global scale. We find that actual evapotranspiration is the single largest predictor of arthropod diversity and explains nearly 30% of the variation in richness. Moreover, we infer that high human activity has led to a 21.3 % and 29.2% decrease in potential insect richness in tropical and dry zones, respectively, but increased insect richness in polar regions. These insights bring a new foundation for biodiversity research and action.

ecology↗

bioRxiv2025

RAMBO: Resolving Amplicons in Mixed Samples for Accurate DNA Barcoding with Oxford Nanopore

DNA barcoding, the use of short genetic markers to identify and differentiate species, is a foundational tool for ecological and taxonomic research. The method has been scaled rapidly with next-generation sequencing technologies enabling the processing of thousands of specimens in parallel. Nanopore sequencing not only offers a flexible, low cost alternative to other platforms but produces full-length reads in real time and can be used in remote settings. However, its comparatively high error rate complicates downstream processing, particularly when PCR amplifies multiple templates from a single specimen, reflecting pseudogenes, paralogs, or contaminants. We present a novel pipeline for DNA barcoding that resolves mixed sequence signals from Nanopore reads using unsupervised clustering and staged consensus generation, without relying on curated reference databases, taxonomic priors, or error models. While existing methods to curate Nanopore sequence data assume a single dominant amplicon per sample or require deep sequence divergence among amplicons, our pipeline can distinguish variants differing by as little as 0.15 percent. It combines column-weighted encodings, UMAP projection, and HDBSCAN clustering, followed by conservative consensus refinement. The pipeline was benchmarked and validated using datasets with known composition, including high-fidelity PacBio sequences. The results show that Nanopore barcoding, when paired with appropriate analysis, can recover biologically meaningful variation even in technically complex samples. The pipeline is particularly suited for specimens where divergent templates are co-amplified, including mitochondrial pseudogenes or multicopy nuclear regions like ITS. As such, it provides a generalizable framework for high-resolution Nanopore analysis of complex amplicon mixtures.

bioinformatics↗

bioRxiv2025

Incidence and attributes of chimeric COI and 18S sequences derived from nematode-infected arthropods

High-throughput sequencing is speeding the discovery of new species and making it possible to quantify the species richness of bulk samples. However, chimeric sequences can lead to both type I errors (true species mistakenly rejected) and type II errors (chimeras incorrectly viewed as valid species). This study employed nanopore sequencing to examine the incidence and nature of chimeric sequences recovered from 531 arthropod specimens infected with nematodes. Specifically, it examined chimera formation in two gene regions: the 658 bp segment of mitochondrial COI employed as the barcode region for the animal kingdom, and a 900 bp segment of nuclear 18S often employed to discriminate lineages of nematodes. This work revealed chimeras for both gene regions despite the deep sequence divergences between members of these two phyla. However, the incidence of chimeric molecules was higher for 18S than COI, with chimera formation correlating with local variation in DNA stability and conserved regions between parent sequences. Aside from demonstrating that chimeras can arise from distantly related organisms, this study provides insights into the mechanisms underlying their formation.

molecular biology↗

bioRxiv2024

HAPLODIPOIDY ACCELERATES MITOGENOME EVOLUTION IN INSECTS

Rates of mitogenome evolution differ among animal lineages, variation which has been linked to life history, ecological traits, and potentially to breeding system. Insects are a good model for examining the latter impacts as, although most are diplodiploids (DD), some lineages reproduce by haplodiploidy (HD) or thelytoky. In this study, we ask if breeding system influences patterns of evolution in the mitogenome using the 658 bp barcode region of the cytochrome c oxidase I (COI) gene as a sentinel. Specifically, we ask if the incidence of amino acid substitutions and indels is linked to breeding system. We investigated this matter by examining COI sequences from specimens assigned to 1332 BINs, a species proxy. Belonging to 513 families and 26 orders, these BINs included representatives of roughly half of all insect families. Most are DD, but ten lineages, varying in rank from tribe to order, are HD. Our analysis reveals that HD lineages show higher rates of amino acid substitution than DD. In addition, indels are frequent in HD lineages but are absent in DD taxa with one exception. Among DD, the Strepsiptera is an outlier; its COI shows very rapid amino acid evolution and frequent indels. The accelerated rates of mitogenome evolution in HD lineages suggest that this breeding system facilitates coevolution between the nuclear and mitochondrial genomes.

evolutionary biology↗

bioRxiv2024

Common to rare transfer learning (CORAL) enables inference and prediction for a quarter million rare Malagasy arthropods

Modern DNA-based biodiversity surveys result in massive-scale data, including up to millions of species - of which most are rare. Making the most of such data for inference and prediction requires modelling approaches that can relate species occurrences to environmental and spatial predictors, while incorporating information about their taxonomic or phylogenetic placement. Even if the scalability of joint species distribution models to large communities has greatly advanced, incorporating hundreds of thousands of species has not been feasible to date, leading to compromised analyses. Here we present a novel "common to rare transfer learning" approach (CORAL), based on borrowing information from the common species to enable statistically and computationally efficient modelling of both common and rare species. We illustrate that CORAL leads to much improved prediction and inference in the context of DNA metabarcoding data from Madagascar, comprising 255,188 arthropod species detected in 2874 samples.

ecology↗

bioRxiv2024

Towards a Taxonomy Machine. A Training Set of 5.6 Million Arthropod Images

The taxonomic identification of organisms from images is an active research area within the machine learning community. Current algorithms are very effective for object recognition and discrimination, but they require extensive training datasets to generate reliable assignments. This study releases 5.6 million images with representatives from 10 arthropod classes and 26 insect orders. All images were taken using a Keyence VHX-7000 Digital Microscope system with an automatic stage to permit high-resolution (4K) microphotography. Providing phenotypic data for 324,000 species derived from 48 countries, this release represents, by far, the largest dataset of standardized arthropod images. As such, this dataset is well suited for testing the efficacy of machine learning algorithms for identifying specimens to higher taxonomic categories.

bioinformatics↗

bioRxiv2024

Building a Collaborative DNA Barcode Library for the Diptera of Churchill, Canada: A Resource for Northern Research

Churchill, Manitoba, Canada is a diverse subarctic region that has been the focus of DNA barcoding efforts and research for decades. Despite this effort, there are still taxa in this region that are underrepresented in public databases, particularly hyper diverse insect groups. We present a collaborative large-scale DNA barcode reference library for Diptera based on molecular data and expert taxonomic identification, and we explore habitat occupancy, biogeographic patterns, and molecular evolution. The reference library contains 16786 specimens sampled around Churchill from 2005 to 2011. Selected specimens were identified by morphological means, sequenced for the animal barcode marker, and sorted into 2225 Molecular Operational Taxonomic Units (using Barcode Index Numbers: BINs) representing 68 families and 1216 named species. Eighty-five species shared a BIN with another species, 143 species were split across several BINs, and 990 species were assigned to a unique BIN, including 129 BINs new to the Barcode of Life Data System. The intraspecific and nearest neighbour distances varied across families, but most species can be easily distinguished from their nearest neighbours. By combining molecular data with taxonomic expertise, the barcode library provides species-level information for 12608 specimens, supplying future researchers with detailed taxonomic information and the opportunity to perform barcode-based specimen identifications for large-scale studies through sequence matching. Comparison of the Diptera composition of Churchill to other subarctic regions reflected likely postglacial colonization northwards as well as a Beringian and circumpolar component. This study also provides an initial investigation of molecular evolution in the best-represented species and finds variability in the rate of molecular evolution, opening intriguing avenues for further investigation. This study provides a publicly available, detailed reference library for use in future research, as well as new insights into the current diversity and taxonomic composition of Diptera present among the diverse habitats of Churchill.

molecular biology↗

bioRxiv2023

Barcode 100K Specimens: In a Single Nanopore Run

It is a global priority to better manage the biosphere, but action needs to be informed by monitoring shifts in the abundance and distribution of species across the domains of life. The acquisition of such information is currently constrained by the limited knowledge of biodiversity. Among the 20 million or more species of eukaryotes, just a tenth have scientific names. DNA barcoding can speed the registration of unknown animal species, the most diverse kingdom of eukaryotes, as the BIN system automates their recognition. However, inexpensive analytical protocols are critical as the census of all animal species will require processing a billion or more specimens. Barcoding involves DNA extraction followed by PCR and sequencing with the last step dominating costs until 2017. By recovering barcodes from highly multiplexed samples, the Sequel platforms from Pacific BioSciences slashed costs by 90%, but these instruments are only deployed in core facilities because of their expense. Sequencers from Oxford Nanopore Technologies provide an escape from high capital and service costs, but their low sequence fidelity has, until now, kept analytical cost above Sequel. However, the improved performance of its latest flow cells (R10.4.1) might erase this differential. This study demonstrates that a regular MinION flow cell can characterize an amplicon pool derived from 100,000 specimens while a Flongle flow cell can process one derived from several thousand. At $0.01 per specimen, DNA sequencing is now the least expensive step in the barcode workflow. By coupling simplified protocols for DNA extraction with ultra-low volume PCRs, it will be possible to move from specimen to DNA barcode for $0.10, a price point that will enable the census of all species within two decades.

molecular biology↗

bioRxiv2022

Phylogenomics Illuminates the Evolutionary History of Wild Silkmoths in Space and Time (Lepidoptera: Saturniidae)

AO_SCPLOWBSTRACTC_SCPLOWWild silkmoths (Saturniidae) are one of the most emblematic and most studied families of moths. Yet, the absence of a robust phylogenetic framework based on a comprehensive taxonomic sampling impedes our understanding of their evolutionary history. We analyzed 1,024 ultraconserved elements (UCEs) and their flanking regions to infer the relationships among 338 species of Saturniidae representing all described subfamilies, tribes, and genera. We investigated systematic biases in genomic data and performed dating and historical biogeographic analyses to reconstruct the evolutionary history of wild silkmoths in space and time. Using Gene Genealogy Interrogation, we showed that saturation of nucleotide sequence data blurred our understanding of early divergences and first biogeographic events. Our analyses support a Neotropical origin of saturniids, shortly after the Cretaceous-Paleogene extinction event (ca 64.0 [stem] - 52.0 [crown] Ma), and two independent colonization events of the Old World during the Eocene, presumably through the Bering Land Bridge. Early divergences strongly shaped the distribution of extant subfamilies as they showed very limited mobility across biogeographical regions, except for Saturniinae, a subfamily now present on all continents but Antarctica. Overall, our results provide a framework for in-depth investigations into the spatial and temporal dynamics of all saturniid lineages and for the integration of their evolutionary history into further global studies of biodiversity and conservation. Rather unexpectedly for a taxonomically well-known family such as Saturniidae, the proper alignment of taxonomic divisions and ranks with our phylogenetic results leads us to propose substantial rearrangements of the family classification, including the description of one new subfamily and two new tribes.

evolutionary biology↗

bioRxiv2021

Message in a Bottle, Metabarcoding Enables Biodiversity Comparisons Across Ecoregions

BackgroundTraditional biomonitoring approaches have delivered a basic understanding of biodiversity, but they cannot support the large-scale assessments required to manage and protect entire ecosystems. This study employed DNA metabarcoding to assess spatial and temporal variation in species richness and diversity in arthropod communities from 52 protected areas spanning three Canadian ecoregions. ResultsThis study revealed the presence of 26,263 arthropod species in the three ecoregions and indicated that at least another 3,000-5,000 await detection. Results further demonstrate that communities are more similar within than between ecoregions, even after controlling for geographical distance. Overall -diversity declined from east to west, reflecting a gradient in habitat disturbance. Shifts in species composition were high at every site with turnover greater than nestedness, suggesting the presence of many transient species. ConclusionsDifferences in species composition among their arthropod communities confirm that ecoregions are a useful synoptic for biogeographic patterns and for structuring conservation efforts. The present results also demonstrate that metabarcoding enables large-scale monitoring of shifts in species composition, making it possible to move beyond the biomass measurements that have been the key metric employed in prior efforts to track change in arthropod communities.

ecology↗

bioRxiv2021

debar, a sequence-by-sequence denoiser for COI-5P DNA barcode data

DNA barcoding and metabarcoding are now widely used to advance species discovery and biodiversity assessments. High-throughput sequencing (HTS) has expanded the volume and scope of these analyses, but elevated error rates introduce noise into sequence records that can inflate estimates of biodiversity. Denoising --the separation of biological signal from instrument (technical) noise--of barcode and metabarcode data currently employs abundance-based methods which do not capitalize on the highly conserved structure of the cytochrome c oxidase subunit I (COI) region employed as the animal barcode. This manuscript introduces debar, an R package that utilizes a profile hidden Markov model to denoise indel errors in COI sequences introduced by instrument error. In silico studies demonstrated that debar recognized 95% of artificially introduced indels in COI sequences. When applied to real-world data, debar reduced indel errors in circular consensus sequences obtained with the Sequel platform by 75%, and those generated on the Ion Torrent S5 by 94%. The false correction rate was less than 0.1%, indicating that debar is receptive to the majority of true COI variation in the animal kingdom. In conclusion, the debar package improves DNA barcode and metabarcode workflows by aiding the generation of more accurate sequences aiding the characterization of species diversity.

bioinformatics↗

bioRxiv2020

Assessment of current taxonomic assignment strategies for metabarcoding eukaryotes

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to a generic or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging. Researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities which vary in species number and specimen abundance, while holding upstream molecular and bioinformatic variables constant. It also evaluates the impact of parameter optimization on the quality of the predictions. Despite the general belief that BLAST top hit underperforms newer methods, our results indicate that it competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to the reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts which will influence the selection of appropriate software. We urge the usage of realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method used.

bioinformatics↗

bioRxiv2019

Forensics and DNA Barcodes - Do Identification Errors Arise in the Lab or in the Sequence Libraries?

Forensic studies often require the determination of biological materials to a species level. As such, DNA-based approaches to identification, particularly DNA barcoding, are attracting increased interest. The capacity of DNA barcodes to assign newly encountered specimens to a species relies upon access to informatics platforms, such as BOLD and GenBank, which host libraries of reference sequences and support the comparison of new sequences to them. As parameterization of these libraries expands, DNA barcoding has the potential to make valuable contributions in diverse forensic contexts. However, a recent publication called for caution after finding that both platforms performed poorly in identifying specimens of 17 common insect species. This study follows up on this concern by asking if the misidentifications reflected problems in the reference libraries or in the query sequences used to test them. Because this reanalysis revealed that missteps in acquiring and analyzing the query sequences were responsible for the misidentifications, a workflow is described to minimize such errors in future investigations. The present study also revealed the limitations imposed by the lack of a polished species-level taxonomy for many groups. In such cases, forensic applications can be strengthened by mapping the geographic distributions of sequence-based species proxies rather than waiting for the maturation of formal taxonomic systems based on morphology.

genetics↗

bioRxiv2019

BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)

DNA barcoding is highly effective for identifying specimens once a reference sequence library is available for the species assemblage targeted for analysis. Despite the great need for an improved capacity to identify the insect pests of crops, the use of DNA barcoding is constrained by the lack of a well-parameterized reference library. The current study begins to address this limitation by developing a DNA barcode reference library for the pest aphids of Pakistan. It also examines the affinities of these taxa with conspecific taxa from other geographic regions based on both conventional taxonomy and Barcode Index Numbers (BINs). A total of 809 aphids were collected from 123 plant species at 87 sites across Pakistan. Morphological study and DNA barcoding allowed 774 specimens to be identified to one of 42 species while the others were placed to a genus or subfamily. The 801 sequences obtained from these specimens were assigned to 52 BINs whose monophyly were supported by neighbor-joining (NJ) clustering and Bayesian inference. The 42 species were assigned to 41 BINs with 38 showing BIN concordance; one species (Rhopalosiphum padi) was assigned to two BINs, while two others (Aphis affinis, Aphis gossypii) were assigned to the same BIN, while one species (Aphis astragalina) lacked a qualifying sequence. The 42 Linnaean species were represented on BOLD by 7,870 records from 69 countries. Combining these records with those from Pakistan produced to 60 BINs with 12 species showing a BIN split and three a BIN merger. Geo-distance correlations showed that intraspecific divergence values for 18 of 37 species were not affected by the distance between populations. Forty four of the 52 BINs from Pakistan had counterparts in 73 countries across six continents, documenting the broad distributions of pest aphids.

ecology↗

bioRxiv2019

A reference library for the identification of Canadian invertebrates: 1.5 million DNA barcodes, voucher specimens, and genomic samples

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 planets 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.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC=\"FIGDIR/small/701805v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (17K):\norg.highwire.dtl.DTLVardef@5c6449org.highwire.dtl.DTLVardef@1bc0224org.highwire.dtl.DTLVardef@309dddorg.highwire.dtl.DTLVardef@1cc2cc8_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2018

Using eDNA to biomonitor the fish community in a tropical oligotrophic lake

Environmental DNA (eDNA) is an effective approach for detecting vertebrates and plants, especially in aquatic ecosystems, but prior studies have largely examined eDNA in cool temperate settings. By contrast, this study employs eDNA to survey the fish fauna in tropical Lake Bacalar (Mexico) with the additional goal of assessing the possible presence of invasive fishes, such as Amazon sailfin catfish. Sediment and water samples were collected from eight stations in Lake Bacalar on three occasions over a 4-month interval. Each sample was stored in the presence or absence of lysis buffer to compare eDNA recovery. Short fragments (184-187 bp) of the cytochrome c oxidase I (COI) gene were amplified using fusion primers and then sequenced on Ion Torrent PGM and S5 before their source species were determined using a custom reference sequence database constructed on BOLD. In total, eDNA sequences were recovered from 75 species of vertebrates including 47 fishes, 15 birds, 7 mammals, 5 reptiles, and 1 amphibian. Although all species are known from this region, 6 fish species represent new records for the study area, while 2 require verification. Sequences for five species (2 birds, 2 mammals, 1 reptile) were only detected from sediments, while sequences from 52 species were only recovered from water. Because DNA from the Amazon sailfin catfish was not detected, we used a mock eDNA experiment to confirm our methods were appropriate for its detection. We developed protocols that enabled the recovery of eDNA from tropical oligotrophic aquatic ecosystems, and confirmed their effectiveness in detecting diverse species of vertebrates including an invasive species of Amazon catfish.

molecular biology↗