Unbiased probabilistic taxonomic classification for DNA barcoding

Somervuo, Panu; Koskela, Sonja; Pennanen, J.; Nilsson, R. Henrik; Ovaskainen, Otso

doi:10.1093/bioinformatics/btw346

Cited by 87 publications

(148 citation statements)

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“…). The taxonomic assignment was complemented with a probabilistic taxonomic assignment method, PROTAXSomervuo, Koskela, Pennanen, Henrik Nilsson, & Ovaskainen, 2016), using the weighted model, which uses a list of the expected vertebrate species for each locality (script available from URL https ://github. It does so by identifying and merging the artifactual OTUs with factual abundant OTUs that are similar in sequence and that consistently co-occur.The OTU sequences were compared against the NCBI Genbank database (www.ncbi.nlm.nih.gov/) using BLASTn, and the output was imported into MEGAN Community Edition version 6.12.7(Huson et al, 2016) using a weighted LCA algorithm with 90 as percent to cover, top percent of 2, and a min score of 150.…”

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Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

et al. 2019

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Background: Thousands of bulk arthropod samples are collected globally every year for monitoring programs, conservation efforts, and ecosystem assessments. The taxonomic contents of these samples can be assessed either morphologically or molecularly using DNA metabarcoding coupled with high-throughput sequencing, the latter of which has gained popularity in recent years. In a related field, only vertebrateingesting invertebrates, such as carrion flies and blood-feeding leeches, are targeted for collection, and metabarcoding is carried out on the vertebrate DNA in their gut contents to provide information on vertebrate diversity (invertebrate-derived DNA, iDNA). Aims:Here, we show that the two approaches can be combined, that is, that vertebrate DNA can be detected through metabarcoding of bulk arthropod samples.Materials and Methods: Two metabarcoding primer sets were used to PCR amplify mammal and vertebrate DNA in DNA extracted from bulk arthropod samples collected with pitfall and Malaise traps in tropical forests in Brazil and Tanzania. Results:In total, 32 vertebrate taxa were detected representing mammals, amphibians, and birds. Detected taxa were within, or close to, their known geographical distributions. Conclusion:This study demonstrates that with a relatively small additional investment, information on vertebrate diversity can be obtained from bulk arthropod samples. This is of particular interest in projects where bulk arthropod samples are collected and extracted with the aim to use metabarcoding to assess arthropod taxa.In such studies, the additional information on vertebrates can further inform ecological assessments and monitoring programs and function as a supplement to traditional survey methods of vertebrates.

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Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

et al. 2019

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“…While the results of Somervuo et al . () suggest that a combination of similarity‐based and phylogenetic‐based predictors yields the best performance both for simulated and real data, in this study we used solely similarity‐based predictors using LAST (Kielbasa et al . ), which is fast and does not require multiple sequence alignment.…”

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Quantifying uncertainty of taxonomic placement in DNA barcoding and metabarcoding

Somervuo

et al. 2017

Methods Ecol Evol

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“…Relatively few studies have characterized the strengths and weaknesses of 52 different bioinformatic sequence classification protocols (Porter et al 2012; Bengtsson-Palme et 53 al. 2015; Peabody et al 2015;Somervuo et al 2016;Richardson et al 2017). Further, 54 researchers continue to utilize a diversity of methods to draw taxonomic inferences from 55 amplicon sequence data.…”

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“…Relative to alignment-based nearest-neighbor and lowest common 56 ancestor-type classification approaches, methods involving hierarchical classification of DNA 57 sequences are popular as they are often designed to estimate the probabilistic confidence of 58 taxonomic inferences at each taxonomic rank. However, studies explicitly examining the 59 accuracy of classification confidence estimates are rare (Somervuo et al 2016 Bengtsson-Palme et al 2015). Thus, it is important to identify and manage reference sequence 73 database artifacts during curation for optimal downstream classification performance.…”

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“…Relative to alignment-based nearest-neighbor and lowest common 56 ancestor-type classification approaches, methods involving hierarchical classification of DNA 57 sequences are popular as they are often designed to estimate the probabilistic confidence of 58 taxonomic inferences at each taxonomic rank. However, studies explicitly examining the 59 accuracy of classification confidence estimates are rare (Somervuo et al 2016 To assess the degree to which our amplicon sequence extraction, dereplication and 139 curation procedures worked, we took inventory of the number of sequences per species and 140 genera present in the data at three points during curation: 1) in the initial input data, 2) following 141 Metaxa2 database builder-based amplicon sequence extraction and 3) in the final database 142 following dereplication and taxonomic curation.…”

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A reference cytochrome c oxidase subunit I database curated for hierarchical classification of arthropod metabarcoding data

Richardson

Bengtsson‐Palme

Gardiner

2018

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Abstract16 Metabarcoding is a popular application which warrants continued methods optimization. To 17 maximize barcoding inferences, hierarchy-based sequence classification methods are 18 increasingly common. We present methods for the construction and curation of a database 19 designed for hierarchical classification of a 157 bp barcoding region of the arthropod cytochrome 20 c oxidase subunit I (COI) locus. We produced a comprehensive arthropod COI amplicon dataset 21 including annotated arthropod COI sequences and COI sequences extracted from arthropod 22 whole mitochondrion genomes, which provided the only source of representation for Zoraptera, 23 Callipodida and Holothyrida. The database contains extracted sequences of the target amplicon 24 from all major arthropod clades, including all insect orders, all arthropod classes and 25 Onychophora, Tardigrada and Mollusca outgroups. During curation, we extracted the COI region 26 of interest from approximately 81 percent of the input sequences, corresponding to 73 percent of 27 the genus-level diversity found in the input data. Further, our analysis revealed a high degree of 28 sequence redundancy within the NCBI nucleotide database, with a mean of approximately 11 29 sequence entries per species in the input data. The curated, low-redundancy database is included 30 in the Metaxa2 sequence classification software (http://microbiology.se/software/metaxa2/).31 Using this database with the Metaxa2 classifier, we characterized the relationship between the 32 Metaxa2 reliability score, an estimate of classification confidence, and classification error 33 probability. We used this analysis to select a reliability score threshold which minimized error. 34 We then estimated classification sensitivity, false discovery rate and overclassification, the 35 propensity to classify sequences from taxa not represented in the reference database. Our work 36 will help researchers design and evaluate classification databases and conduct metabarcoding on 37 arthropods and alternate taxa. Introduction 39With the increasing availability of high-throughput DNA sequencing, scientists with a 40 wide diversity of backgrounds and interests are increasingly utilizing this technology to achieve 41 a variety of goals. One growing area of interest involves the use of metabarcoding, or amplicon 42 sequencing, for biomonitoring, biodiversity assessment and community composition inference 43 (Yu et al. 2012; Guardiola et al. 2015; Richardson et al. 2015). Using universal primers designed 44 to amplify conserved genomic regions across a broad diversity of taxonomic groups of interest, 45 researchers are afforded the opportunity to survey biological communities at previously 46 unprecedented scales. While such advancements hold great promise for improving our 47 knowledge of the biological world, they also represent new challenges to the scientific 48 community. 49Given that bioinformatic methods for taxonomic inference of metabarcoding sequence 50 data are relatively new, the development, val...

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Unbiased probabilistic taxonomic classification for DNA barcoding

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 87 publications

References 26 publications

Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

Quantifying uncertainty of taxonomic placement in DNA barcoding and metabarcoding

A reference cytochrome c oxidase subunit I database curated for hierarchical classification of arthropod metabarcoding data

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