BOLDigger – a Python package to identify and organise sequences with the Barcode of Life Data systems

Buchner, Dominik; Leese, Florian

doi:10.3897/mbmg.4.53535

Cited by 101 publications

(60 citation statements)

References 13 publications

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“…OTUs with a minimal read abundance of 0.01% in at least one sample were retained for further analyses, while other OTUs were discarded. Sequences were compared to the BOLD database sequences using BOLDigger 1.1.4 (Buchner & Leese, 2020). For the whole dataset, a similarity threshold of 85% to a reference sequence in BOLD was required to include the OTU into further analysis.…”

Section: Methodsmentioning

confidence: 99%

Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification

et al. 2020

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DNA metabarcoding of freshwater communities typically relies on PCR amplification of a fragment of the mitochondrial cytochrome c oxidase I (COI) gene with degenerate primers. The advantage of COI is its taxonomic resolution and the availability of an extensive reference database. However, when universal primers are used on environmental DNA (eDNA) isolated from water, benthic invertebrate read and OTU numbers are typically “watered down,” that is, under represented, compared to whole specimen “bulk samples” due to greater co‐amplification of abundant nontarget taxa (e.g., fungi, algae, and bacteria). Because benthic stream invertebrate taxa are of prime importance for regulatory biomonitoring, more effective ways to capture their diversity via eDNA isolated from water are important. In this study, we aimed to improve benthic invertebrate assessment from eDNA by minimizing nontarget amplification. Therefore, we generated eDNA data using universal primers BF2/BR2 on samples collected throughout 15 months from a German Long‐Term Ecological Research site (Rhine‐Main‐Observatory, Kinzig River) to identify most abundant nontarget taxa. Based on these data, we designed a new reverse primer (EPTDr2n) with 3’‐specificity toward benthic invertebrate taxa and validated its specificity in silico together with universal forward primer fwhF2 using available data from GenBank and BOLD. We then performed in situ tests using 20 Kinzig River eDNA samples. We found that the percentage of target reads was much higher for the new primer combination compared to two universal benthic invertebrate primer pairs, BF2/BR2 and fwhF2/fwhR2n (99.6% versus 25.89% and 39.04%, respectively). Likewise, the number of detected benthic invertebrate species was substantially higher (305 versus 113 and 185) and exceeded the number of 153 species identified by expert taxonomists at nearby sites across two decades of sampling. While few taxa, such as flatworms, were not detected, we show that the optimized primer avoids the nontarget amplification bias and thus significantly improves benthic invertebrate detection from eDNA.

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Section: Methodsmentioning

confidence: 99%

Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification

et al. 2020

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“…This naive Bayesian classifier was trained on a curated set of COI sequences from BOLD and GenBank to make rapid, accurate taxonomic assignments (Altschul et al, 1997;Wang et al, 2007;Porter and Hajibabaei, 2018a). Recently, a python package called BOLDigger has been developed to help automate batch query submissions to the BOLD identification engine and can be used to identify COI, ITS, rbcL, and matK sequences (Buchner and Leese, 2020). For each of these methods, there are trade-offs in terms of ease of use, speed, and rigor.…”

Section: Why Do We Cluster Metabarcode Reads?mentioning

confidence: 99%

Putting COI Metabarcoding in Context: The Utility of Exact Sequence Variants (ESVs) in Biodiversity Analysis

Porter

Hajibabaei

2020

Front. Ecol. Evol.

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DNA barcoding and metabarcoding are techniques that focus on signature genomic regions that in theory provide species level resolution, but in practice this is not always possible. We place animal-focused COI metabarcoding in context with respect to the use of marker gene sequencing in microbial and fungal ecology. We focus on three specific aspects of metabarcodes: (1) the process of metabarcode sequence clustering, (2) how metabarcode cluster types affect the results of biodiversity analyses, and (3) the current state of reference sequence databases used for metabarcode identification. Using examples from the arthropod COI metabarcode literature, we show that exact sequence variants (ESVs) detect more unique taxa than operational taxonomic units (OTUs) but with similar patterns in taxonomic resolution. We also show that the difference between ordinations based on ESVs or OTUs recover similar groupings. We compile a list of reference sequence databases useful for multi-marker metabarcoding and present a list of reference sequence databases specifically formatted for use with a naive Bayesian classifier for rigorous metabarcode taxonomic assignments. Sophisticated tools and reference databases are available for analyzing COI sequences, and these compare favorably with those available for other metabarcode markers such as the ribosomal RNA genes used to target microbes and fungi.

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“…After this quality filtering step, the reads of the two technical replicates per sample were summed up to build the final dataset. Quality filtered reads were assigned to species using the BOLD database (Ratnasingham & Hebert, 2007) with the BOLDigger tool (Buchner & Leese, 2020). The following identity thresholds were used for assigning taxonomic ranks: species 98%; genus 95%; family 93%; order 90%; class 85%.…”

Section: Bioinformatic Processingmentioning

confidence: 99%

Metabarcoding reveals different zooplankton communities in northern and southern areas of the North Sea

Macher

Hoorn

Peijnenburg

et al. 2020

Preprint

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Zooplankton are key players in marine ecosystems, linking primary production to higher trophic levels. The high abundance and high taxonomic diversity renders zooplankton ideal for biodiversity monitoring. However, taxonomic identification of the zooplankton assemblage is challenging due to its high diversity, subtle morphological differences and the presence of many meroplanktonic species, especially in coastal seas. Molecular techniques such as metabarcoding can help with rapid processing and identification of taxa in complex samples, and are therefore promising tools for identifying zooplankton communities. In this study, we applied metabarcoding of the mitochondrial cytochrome c oxidase I gene to zooplankton samples collected along a latitudinal transect in the North Sea, a shelf sea of the Atlantic Ocean. Northern regions of the North Sea are influenced by inflow of oceanic Atlantic waters, whereas the southern parts are characterised by more coastal waters. Our metabarcoding results indicated strong differences in zooplankton community composition between northern and southern areas of the North Sea, particularly in the classes Copepoda, Actinopterygii (ray-finned fishes) and Polychaeta. We compared these results to the known distributions of species reported in previous studies, and by comparing the abundance of copepods to data obtained from the Continuous Plankton Recorder (CPR). We found that our metabarcoding results are mostly congruent with the reported distribution and abundance patterns of zooplankton species in the North Sea. Our results highlight the power of metabarcoding to rapidly assess complex zooplankton samples, and we suggest that the technique could be used in future monitoring campaigns and biodiversity assessments.HighlightsZooplankton communities are different in northern and southern areas of the North SeaMetabarcoding results are consistent with known species distributions and abundanceMetabarcoding allows for fast identification of meroplanktonic species

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BOLDigger – a Python package to identify and organise sequences with the Barcode of Life Data systems

Cited by 101 publications

References 13 publications

Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification

Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification

Putting COI Metabarcoding in Context: The Utility of Exact Sequence Variants (ESVs) in Biodiversity Analysis

Metabarcoding reveals different zooplankton communities in northern and southern areas of the North Sea

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