Abstract
Nucleotide sequences reference collections or databases are fundamental components in DNA barcoding and metabarcoding data analyses pipelines. In such analyses, the accurate taxonomic assignment is a crucial aspect, relying directly on the availability of comprehensive and curated reference sequence collection and its taxonomy information. The currently wide use of the mitochondrial cytochrome oxidase subunit-I (COXI) as a standard DNA barcode marker in metazoan biodiversity studies highlights the need to shed light on the availability of the related relevant information from different data sources and their eventual integration. To adequately address data integration process, many aspects should be markedly considered starting from DNA sequence curation followed by taxonomy alignment with solid reference backbone and metadata harmonization according to universal standards. Here, we present MetaCOXI, an integrated collection of curated metazoan COXI DNA sequences with their associated harmonized taxonomy and metadata. This collection was built on the two most extensive available data resources, namely the European Nucleotide Archive (ENA) and the Barcode of Life Data System (BOLD). The current release contains more than 5.6 million entries (39.1% unique to BOLD, 3.6% unique to ENA, and 57.2% shared between both), their related taxonomic classification based on NCBI reference taxonomy, and their available main metadata relevant to environmental DNA studies, such as geographical coordinates, sampling country and host species. MetaCOXI is available in standard universal formats (‘fasta’ for sequences & ‘tsv’ for taxonomy and metadata), which can be easily incorporated in standard or specific DNA barcoding and/or metabarcoding data analysis pipelines. Database URL: https://github.com/bachob5/MetaCOXI
Highlights
A critical aspect of environmental DNA research is the capacity to collectively characterize the genetic material of a variety of living or even dead organisms in a given sample at taxonomic and functional levels [1,2,3]. The use of such an approach is currently spanned over different scientific disciplines, including biodiversity monitoring programmes, ecosystem services conservation and recovery, environmental health and biomedical research [4, 5]. eDNA is the core object of a common DNA metabarcoding experiment aiming at the massive reading of a DNA barcode marker using high-throughput sequencing (HTS) technologies that enables to explore the taxonomic diversity in an environment/habitat of interest mostly at species level [6, 7]
We present MetaCOXI, an integrated collection of Metazoan cytochrome oxidase subunit-I (COXI) DNA sequences originated from both European Nucleotide Archive (ENA) and Barcode of Life Data System (BOLD) data entries, generated following an internal data processing workflow, which applies sequence quality assessment, removes entries redundancy, and provides a harmonized taxonomic classification, according to NCBI reference backbone [25] at the main seven levels, with nine associated metadata
This indicates that the approach of using the COXI profile-specific cutoff threshold had an additional conservative effect, which increased the accuracy of determining a true positive match by 0.14%. Apart from those not satisfying the applied TC threshold, additional investigation revealed that some of the rejected BOLD entries [916] presented one or more internal stop codons in their amino acid sequences. Such assessment was not possible to conduct on ENA sequences as their identity of coding for COXI gene was inferred through the present analyses
Summary
A critical aspect of environmental DNA (eDNA) research is the capacity to collectively characterize the genetic material (intracellular or extracellular) of a variety of living or even dead organisms (e.g. ancient eDNA) in a given sample at taxonomic and functional levels [1,2,3]. The use of such an approach is currently spanned over different scientific disciplines, including biodiversity monitoring programmes, ecosystem services conservation and recovery, environmental health and biomedical research [4, 5]. Enhancing the comprehensiveness of such databases would be among the solutions to fill those gaps in many environmental ecosystem research contexts (e.g. sea water) even at different gradients or habitats [14]
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