Dataset Information

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

ABSTRACT: Metabarcoding is a popular application which warrants continued methods optimization. To maximize barcoding inferences, hierarchy-based sequence classification methods are increasingly common. We present methods for the construction and curation of a database designed for hierarchical classification of a 157 bp barcoding region of the arthropod cytochrome c oxidase subunit I (COI) locus. We produced a comprehensive arthropod COI amplicon dataset including annotated arthropod COI sequences and COI sequences extracted from arthropod whole mitochondrion genomes, the latter of which provided the only source of representation for Zoraptera, Callipodida and Holothyrida. The database contains extracted sequences of the target amplicon from all major arthropod clades, including all insect orders, all arthropod classes and Onychophora, Tardigrada and Mollusca outgroups. During curation, we extracted the COI region of interest from approximately 81 percent of the input sequences, corresponding to 73 percent of the genus-level diversity found in the input data. Further, our analysis revealed a high degree of sequence redundancy within the NCBI nucleotide database, with a mean of approximately 11 sequence entries per species in the input data. The curated, low-redundancy database is included in the Metaxa2 sequence classification software (http://microbiology.se/software/metaxa2/). Using this database with the Metaxa2 classifier, we performed a cross-validation analysis to characterize the relationship between the Metaxa2 reliability score, an estimate of classification confidence, and classification error probability. We used this analysis to select a reliability score threshold which minimized error. We then estimated classification sensitivity, false discovery rate and overclassification, the propensity to classify sequences from taxa not represented in the reference database. Our work will help researchers design and evaluate classification databases and conduct metabarcoding on arthropods and alternate taxa.

SUBMITTER: Richardson RT

PROVIDER: S-EPMC6025149 | biostudies-other | 2018

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

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

Richardson Rodney T RT Bengtsson-Palme Johan J Gardiner Mary M MM Johnson Reed M RM

PeerJ 20180626

Metabarcoding is a popular application which warrants continued methods optimization. To maximize barcoding inferences, hierarchy-based sequence classification methods are increasingly common. We present methods for the construction and curation of a database designed for hierarchical classification of a 157 bp barcoding region of the arthropod cytochrome c oxidase subunit I (COI) locus. We produced a comprehensive arthropod COI amplicon dataset including annotated arthropod COI sequences and CO ...[more]

PMID: 29967752

Similar Datasets

Project description:High-throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species-level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum-specific species-level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read-merging and two clustering algorithms and the cluster-free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus-level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species-level detections, which were, however, associated with higher error rates compared to ASVs. Genus-level assignments using ASVs exhibited higher accuracy and lower error rates compared to species-level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets